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  • Poppy crop capsule volume estimation using UAS remote sensing and random forest regression
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-14
    Faheem Iqbal, Arko Lucieer, Karen Barry

    Improved prediction of poppy capsule volume is essential for optimal management of poppy crop. In order to estimate poppy capsule volume accurately using remotely sensed imagery, the selection of most appropriate models and predictor variables is essential. Multiple spectral indices with random forest (RF) regression were tested to estimate poppy capsule volume using an Unmanned Aircraft System (UAS). Data were collected from field-based physical measurements, in-field spectral measurements and from UAS flights with multispectral sensors over two poppy crops at Cambridge and Sorell in Tasmania, Australia. Field measured spectral signatures were convolved to the multispectral bands of a UAS mounted sensor. These convolved UAS spectral signatures were used to compute multiple spectral indices to develop the RF model, and select optimal model parameters based on root mean squared error (RMSE). In addition, the RF variable importance scores were used to rank the model variables, and to identify the best performing vegetation indices. In Cambridge, an RF model based on convolved UAS spectral signatures predicted capsule volume with an RMSE values ranging from 15.60 cm3 (10.27%) to 25.63 cm3 (14.45%) from training and validation dataset, respectively, indicating a strong relationship between SVIs and field measured capsule volume. An RF model trained on UAS multispectral data (measure not simulated) resulted an RMSE value of 19.39 cm3 (12.80%) based on training data set and an RMSE value of 26.85 cm3 (17.77%) with validation dataset. The Cambridge site model parameters and optimal variables were applied to the Sorell data, which showed a significant relationship between measured and predicted capsule volume (R2 0.72), with relative error of 26.25%. The results showed that the RF model developed using selected variables can help to predict capsule volume 2–3 weeks prior to harvest.

    更新日期:2018-07-15
  • Integrating airborne hyperspectral imagery and LiDAR for volcano mapping and monitoring through image classification
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-14
    G. Kereszturi, L.N. Schaefer, W.K. Schleiffarth, J. Procter, R.R. Pullanagari, S. Mead, Ben Kennedy

    Optical and laser remote sensing provide resources for monitoring volcanic activity and surface hydrothermal alteration. In particular, multispectral and hyperspectral imaging can be used for detecting lithologies and mineral alterations on the surface of actively degassing volcanoes. This paper proposes a novel workflow to integrate existing optical and laser remote sensing data for geological mapping after the 2012 Te Maari eruptions (Tongariro Volcanic Complex, New Zealand). The image classification is based on layer-stacking of image features (optical and textural) generated from high-resolution airborne hyperspectral imagery, Light Detection and Ranging data (LiDAR) derived terrain models, and aerial photography. The images were classified using a Random Forest algorithm where input images were added from multiple sensors. Maximum image classification accuracy (overall accuracy = 85%) was achieved by adding textural information (e.g. mean, homogeneity and entropy) to the hyperspectral and LiDAR data. This workflow returned a total surface alteration area of ∼0.4 km2 at Te Maari, which was confirmed by field work, lab-spectroscopy and backscatter electron imaging. Hydrothermal alteration on volcanoes forms precipitation crusts on the surface that can mislead image classification. Therefore, we also applied spectral matching algorithms to discriminate between fresh, crust altered, and completely altered volcanic rocks. This workflow confidently recognized areas with only surface alteration, establishing a new tool for mapping structurally controlled hydrothermal alteration, evolving debris flow and hydrothermal eruption hazards. We show that data fusion of remotely sensed data can be automated to map volcanoes and significantly benefit the understanding of volcanic processes and their hazards.

    更新日期:2018-07-15
  • MODIS ocean color product downscaling via spatio-temporal fusion and regression: The case of chlorophyll-a in coastal waters
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-14
    Shanxin Guo, Bo Sun, Hankui K. Zhang, Jing Liu, Jinsong Chen, Jiujuan Wang, Xiaoli Jiang, Yan Yang

    Detailed and accurate information on the spatial variation of chlorophyll-a concentration in coastal waters is a critical component of ocean ecology and environmental research. The daily MODIS chlorophyll-a products provided by NASA, with 1 km spatial resolution, are suitable for monitoring this variation globally, but these products are too coarse to apply in practice to obtain detailed information over coastal waters. Early studies have shown that spatiotemporal data fusion techniques can be used to predict higher spatial resolution land-cover data based on time-series information in MODIS and the detailed texture from Landsat. However, this technology hasn’t been tested to determine whether it can be used to predict higher spatial-resolution data in coastal waters with rapid water movement. This study aims to answer this question by providing a method to downscale the MODIS chlorophyll-a products from 1 km spatial resolution to 30 m. The spatiotemporal data fusion model U-STFM and the regression model NASA OC2M-HI were used to combine the texture and chlorophyll-a information from Landsat and MODIS. An area with rapid water movement in Bohai Bay of the Bohai Sea, northeast China, was selected for this study. Twelve matched images from MODIS in Aqua platform and Landsat 8, taken over a period of five years (2013–2017), were used to better predict detailed remote-sensing reflectance (Rrs) on the targeted days. Landsat 8 Rrs was used as ground-truth data to assess the output. The results on Mar 10th, 2016, show: 1) The downscaled results (30 m) from the U-STFM model indicate a more stable prediction of Rrs with RMSE of 0.00177 and 0.00202 and R-squared of 0.868 and 0.881 for the blue and green bands, respectively. Results from STARFM and ESTARFM fusion models are also compared in this study. 2) High correlation between log10(U-STFM Blue/ U-STFM Green) and log10(MODIS Chl) captured by OC2M-HI regression model at 1 km scale with R-squared up to 0.85 and RMSE up to 0.742 mg/m^3. This correlation was further used to predict the final chlorophyll-a concentration prediction at 30 m scale on Mar 10th, 2016; 3) The Landsat 8 chlorophyll-a product was used as reference data to evaluate the final chlorophyll-a concentration prediction (30 m) and the original MODIS chlorophyll-a product. The result shows the final prediction (30 m) maintains the accuracy of MODIS chlorophyll-a product and highly improved the local texture details near coastal waters. Predictions on nine other targeted dates with similar conclusions were also evaluated in this paper. The results in this study suggest that low spatial-resolution (1 km) daily MODIS chlorophyll-a products can be downscaled to higher resolution (30 m) products based on the U-STFM image fusion model and NASA’s OC2M-HI regression model to better understand the dynamic patterns of chlorophyll-a concentration in coastal waters.

    更新日期:2018-07-15
  • What is the Range of Soil Water Density? Critical reviews with a unified model
    Rev. Geophys. (IF 13.529) Pub Date : 2018-07-14
    Chao Zhang; Ning Lu

    The soil water density is defined as the ratio of soil water mass to soil water volume. It is a cornerstone in defining thermodynamic states of either saturated or unsaturated soils for quantifying water storage and movement in the subsurface, and for mechanical stability of landscape. So far, it has been widely treated as identical to the free water density, i.e., a constant of 0.997 g/cm3, but can be remarkably different from this value as it is subject to a wide range of variation in energy levels. Some experimental and theoretical evidence indicates that it can be as high as 1.680 g/cm3 and as low as 0.752 g/cm3. However, to date, there is no unanimous agreement upon a reliable experimental method to measure the soil water density or a unified theory to explain why and how the soil water density can deviate remarkably from the free water density. Consequently, the understanding of the soil water density is controversial and elusive, or some theories are contradictory to each other. In this review, the authors will: (1) conduct critical reviews on the experimental and theoretical methodologies to identify their limitations, flaws, and uncertainties, (2) synthesize some recent findings on intermolecular forces, interfacial interactions, and soil‐water retention mechanisms to clarify molecular‐scale physicochemical mechanisms governing the soil water density, and (3) propose a unified model to quantify soil water density variation. It is found that capillarity associated with surface tension tends to generate tensile stress in soil water and thereby decreases the soil water density, whereas adsorption stemmed from cation hydration, surface hydration, and interlamellar cation hydration tends to produce compressive stress thus increases the soil water density. Furthermore, the abnormally high water density greater than 1.15 g/cm3 is a result of cation and surface hydration that involves significant water structure change around exchangeable cations and mineral surface hydroxyls. The unified soil water density model, explicitly quantifying adsorptive and capillary water, could potentially reconcile the unresolved controversies. The critical reviews and the unified model also would allow us to further confine the upper and lower bounds of the soil water density. The upper bound is theoretically inferred to be around 1.872 g/cm3, whereas the lower bound is around 0.995 g/cm3; both are higher than that reported in the literature. With the unified model and measured soil water retention curves, it is demonstrated quantitatively that the soil water density significantly impacts the magnitude of various fundamental soil properties such as matric potential, specific surface area, and volumetric water content. The abnormally high soil water density has significant implications to the conventional concepts of matric potential and pore water pressure in soils and other earthen porous materials.

    更新日期:2018-07-15
  • A flexible and efficient radiation scheme for the ECMWF model
    J. Adv. Model. Earth Syst. (IF 3.97) Pub Date : 2018-07-13
    Robin J. Hogan; Alessio Bozzo

    This paper describes a new radiation scheme ‘ecRad’ for use both in the model of the European Centre for Medium‐Range Weather Forecasts (ECMWF), and offline for non‐commercial research. Its modular structure allows the spectral resolution, the description of cloud and aerosol optical properties, and the solver, to be changed independently. The available solvers include the Monte Carlo Independent Column Approximation (McICA), ‘Tripleclouds’ and the Speedy Algorithm for Radiative Transfer through Cloud Sides (SPARTACUS), the latter which makes ECMWF the first global model capable of representing the 3D radiative effects of clouds. The new implementation of the operational McICA solver produces less noise in atmospheric heating rates, and is 41% faster, which can yield indirect forecast skill improvements via calling the radiation scheme more frequently. We demonstrate how longwave scattering may be implemented for clouds but not aerosols, which is only 4% more computationally costly overall than neglecting longwave scattering and yields further modest forecast improvements. It is also shown how a sequence of radiation changes in the last few years has led to a substantial reduction in stratospheric temperature biases.

    更新日期:2018-07-14
  • Interplay between inherited rift faults and strike-slip structures: Insights from analogue models and field data from Iceland
    Glob. Planet. Change (IF 3.982) Pub Date : 2018-04-01
    F.L. Bonali, A. Tibaldi, F. Pasquaré Mariotto, E. Russo

    Although structural inheritance is a fundamental factor in the tectonic evolution of the crust, few studies have been aimed at understanding in detail the interaction between pre-existing normal faults in a rift zone and successive dominant strike-slip (transtensional) movements. Firstly, we present the complex pattern of faults and tension fractures of the western, pre-Holocene part of the N-S Theistareykir Fissure Swarm (ThFS - Northern Iceland Rift), crossed by the NW-SE striking, right-lateral, Husavik-Flatey Fault (HFF), and we integrate previous observations with new field data that reveal Holocene motions along the N-S faults near the HFF. Secondly, we propose a set of analogue experiments that reproduce the N-S rifting followed by superimposed transtensional faulting along the HFF. In a first set of experiments, we tested the effect of an initial extension at the shallow crustal level by forming a rift zone. During this rifting phase, we modelled the presence of a sub-orthogonal discontinuity that represents the structural inheritance of the HFF (that is older than the ThFS), but without any imposed “regional” transtensional movement along it. After that, we superimposed a dominant right-lateral movement along the HFF on the modelled rift faults in order to assess the effect of the inheritance of the rift plus the HFF. Our results show that during rifting, a series of elongated and depressed areas develop along the initial HFF discontinuity (that is locally reactivated by the rift opening), in agreement with field data. During the second experimental set of exclusively shear deformation along the HFF, the models show the development of Riedel shears at the HFF, contemporaneous to the local reactivation of normal faults and tension fractures in the previous rift zone. This reactivation occurs by block rotation, incremental dip-slip motions on pre-existing fault scarps, widening of tension fractures and development of new structures. We conclude that transversal basins can develop from the early stages of rift development, and that the structures of a pre-existing rift may reactivate under a local stress state induced by incremental transtensional motions.

    更新日期:2018-07-14
  • Two plutonic complexes of the Sanandaj-Sirjan magmatic-metamorphic belt record Jurassic to Early Cretaceous subduction of an old Neotethys beneath the Iran microplate
    Gondwana Res. (IF 5.657) Pub Date : 2018-04-18
    T.N. Yang, J.L. Chen, M.J. Liang, D. Xin, M. Aghazadeh, Z.Q. Hou, H.R. Zhang

    The Neotethyan tectonics of the Zagros orogenic belt, SW Iran remains still hotly debated in comparing with its western counterparts. One major issue concerns the timing and nature of the Sanandaj-Sirjan magmatic-metamorphic belt (SSMB), which is made predominantly of metamorphic rocks and Jurassic to Early Cretaceous large plutonic complexes. The Alvand and Qory are two largest plutonic complexes locating in north-central and southern segments, respectively, of the SSMB. Careful LA-ICP-MS U/Pb analyses of the magmatic zircons from the Alvand plutonic complex reveal a smooth spectra, along which the concordant age increase gradually from 120 to 190 Ma; while that of Qory is step-like consisting of two stages, a Jurassic and a late Early Cretaceous ones, respectively. New geochemical data, combined with zircon Lu/Hf results suggest that (1) the Alvand granitoids mostly resulted from a long-lived, successive injection of juvenile-crust-sourced magma batches without obvious fractionation crystallization (FC); but (2) the two stages granitoids of the Qory complex both generated by FC of juvenile-crust-sourced magmas; and (3) the gabbros of the Alvand complex are geochemically of E-MORB-affinity while those of the Qory complex are typical continental arc mafic rocks. Previously published petrological and 40Ar/39Ar data have identified a broken, Jurassic to Early Cretaceous high-pressure metamorphic belt to the southwest of the SSMB, which likely represents the closed, southeastern equivalent of the northern Neotethyan Ocean, north of the Taurides-Anatolia-Armenia block. Thus, the SSMB in Iran, the Kapan belt in Caucasus, and the Serbo-Macedonian belt in northern Turkey form a huge Jurassic to Early Cretaceous continental margin arc system recording northeastwards subduction of the older Northern Neotethyan Ocean beneath Eurasia. The Albian-Cenomanian ophiolites such as Koy, Kermanshah, and Neyriz in Iran represent the eastern counterpart of the younger Southern Neotethyan Ocean, south of the Taurides-Anatolia-Armenia block. During the subduction of the Old Neotethys, an intraplate transform fault likely opened and generated a slab-window beneath the Alvand region, which provided a constant energy source to steadily heat the low crust. This model satisfactorily interprets the unusual geochronological framework and geochemistry of the Alvand complex.

    更新日期:2018-07-14
  • Geochemistry, zircon U-Pb and Hf isotope for granitoids, NW Sanandaj-Sirjan zone, Iran: Implications for Mesozoic-Cenozoic episodic magmatism during Neo-Tethyan lithospheric subduction
    Gondwana Res. (IF 5.657) Pub Date : 2018-04-23
    Zhiyong Zhang, Wenjiao Xiao, Weiqiang Ji, Mahmoud Reza Majidifard, Mahnaz Rezaeian, Morteza Talebian, Dunfeng Xiang, Ling Chen, Bo Wan, Songjian Ao, Rasoul Esmaeili

    The Sanandaj-Sirjan zone (SSZ) of Iran comprises sedimentary and metamorphic basement rocks, which are generally regarded as having been derived from the southern active margin of the Eurasian plate. Within the SSZ, a number of Mesozoic to Cenozoic granitoid intrusions of various size, elongated in a NW-SE direction are exposed. With the benefit of precise age dating, geochemical and isotopic data over the past decade, the magmatic history of these intrusions has become clearer. This study presents further geochronological and geochemical data for previously dated and undated granitoids together with considerable zircon Lu-Hf isotopic data, which were limited in the past. Combined with previous work, these new data, including the finding of ca. 170 Ma adakite, lead to improved constraints on the Meso-Cenozoic tectonic evolution of Neo-Tethyan lithospheric subduction. The dominant early-middle Jurassic magmatism is proposed to have occurred with a major contribution of crustal components during the initiation of Neo-Tethyan subduction. Subsequent, late Jurassic magmatism suggests the involvement of lower crust partial melting in an extensional tectonic setting. Cretaceous magmatism almost ceased after formation of a flat slab, caused by a trench retreat rate exceeding that of slab roll-back. Late Paleocene-Eocene magma sources in the SSZ are dominated by mantle-derived input through an asthenospheric window with subordinate crustal contamination during the subduction of the Neo-Tethyan ridge-spreading center. This interpretation differs from Paleocene-Eocene magmatic flare-up proposed for the northern Iranian interior, which may have been driven by an episode of slab retreat or slab roll-back following Cretaceous flat slab subduction.

    更新日期:2018-07-14
  • China paleogeography: Current status and future challenges
    Earth Sci. Rev. (IF 7.491) Pub Date : 2018-04-12
    Mingcai Hou, Anqing Chen, James G. Ogg, Gabriele M. Ogg, Keke Huang, Fengcun Xing, Hongde Chen, Zhenkui Jin, Yiqun Liu, Zhiqiang Shi, Herong Zheng, Zongquan Hu, Hu Huang, Xinchun Liu

    Paleogeographic maps, especially when overlain on reconstructions of ancient plate positions, represent the culmination of geoscience field mapping, basin drilling, geophysical research and methods of interpretation and correlation. During the past century, Chinese geoscientists have progressively compiled and revised many depositional facies maps from the scale of individual basins to nationwide syntheses for different slices of geologic time. However, the most recent comprehensive national compilation spanning the entire Phanerozoic was in 1985, and the most recent national compilation that spans only the Paleozoic was in 2010 (Zheng, Hu, et al., 2010; which is partly reproduced in the Supplementary materials). A major challenge is to place these facies maps of the numerous individual blocks into the larger contexts of moving plates and of their relationships to adjoining regions, especially for the diverse opinions on pre-Triassic plate tectonic models of Southeast Asia. There are many challenges in compiling the paleogeography of China in the context of Southeast Asia, especially prior to the Permian. A multi-institutional coordinated paleogeography program with user-friendly shared databases and visualization outputs from the basin- to inter-national scale is a major goal in China and Southeast Asia stratigraphy and geophysical research.

    更新日期:2018-07-14
  • Current Systems in the Earth's Magnetosphere
    Rev. Geophys. (IF 13.529) Pub Date : 2018-03-08
    N. Yu. Ganushkina; M. W. Liemohn; S. Dubyagin

    The basic structure and dynamics of the primary electric current systems in the Earth's magnetosphere are presented and discussed. In geophysics, the word current is used to describe the flow of mass from one location to another, and its analog of electric current is a flow of charge from one place to another. An electric current is associated with a magnetic field, and they combine with the Earth's internally generated dipolar magnetic field to form the topology of the magnetosphere. The concept of an electric current is reviewed and compared with other approaches to investigate the physics of the magnetosphere. The implications of understanding magnetospheric current systems are discussed, including paths forward for new investigations with the robust set of observations being produced by the numerous scientific and commercial satellites orbiting Earth.

    更新日期:2018-07-14
  • The Global Food‐Energy‐Water Nexus
    Rev. Geophys. (IF 13.529) Pub Date : 2018-04-20
    Paolo D'Odorico; Kyle Frankel Davis; Lorenzo Rosa; Joel A. Carr; Davide Chiarelli; Jampel Dell'Angelo; Jessica Gephart; Graham K. MacDonald; David A. Seekell; Samir Suweis; Maria Cristina Rulli

    Water availability is a major factor constraining humanity's ability to meet the future food and energy needs of a growing and increasingly affluent human population. Water plays an important role in the production of energy, including renewable energy sources and the extraction of unconventional fossil fuels that are expected to become important players in future energy security. The emergent competition for water between the food and energy systems is increasingly recognized in the concept of the “food‐energy‐water nexus.” The nexus between food and water is made even more complex by the globalization of agriculture and rapid growth in food trade, which results in a massive virtual transfer of water among regions and plays an important role in the food and water security of some regions. This review explores multiple components of the food‐energy‐water nexus and highlights possible approaches that could be used to meet food and energy security with the limited renewable water resources of the planet. Despite clear tensions inherent in meeting the growing and changing demand for food and energy in the 21st century, the inherent linkages among food, water, and energy systems can offer an opportunity for synergistic strategies aimed at resilient food, water, and energy security, such as the circular economy.

    更新日期:2018-07-14
  • Computational Evidence for the Enzymatic Transformation of 2-hydroxypropylphosphonate to Methylphosphonate
    ACS Earth Space Chem. Pub Date : 2018-07-12
    Yanwei Li, Xiaodan Wang, Ruiming Zhang, Junjie Wang, Zhongyue Yang, Likai Du, Xiaowen Tang, Qingzhu Zhang, Wenxing Wang

    Understanding the origins of the greenhouse gas methane in the ocean is of great environmental importance, especially for global climate change and the flow of carbon within the earth surface system. A mutant (E176H) of 2-hydroxyethylphosphonate dioxygenase (HEPD) has been reported to catalyze the transformation of 2-hydroxypropylphosphonate (2-HEP) to methylphosphonate (MPn), a compound that can be easily transformed to methane by C–P lyase in marine microbe. Here, HEPD E176H-catalyzed transformation of 2-HEP to MPn was investigated at the molecular level by using QM/MM method. The results evidenced the feasibility of the transformation of 2-HEP to MPn and highlighted that the transformation contains five elementary steps: H-abstraction, O-O bond cleavage, H-transfer, C-C bond cleavage, and MPn formation. H-abstraction was found to be the rate-determining step with an energy barrier of 17.8 kcal/mol, which is in reasonable accordance with the experimentally determined rate constant (0.38 s-1, correspond to 18.0 kcal/mol). Three intersystem crossing events were involved in H-abstraction, H-transfer, and MPn formation steps. Residue electrostatic analysis on the rate determining step suggests that proper mutation of Tyr174 may improve the enzymatic efficiency.

    更新日期:2018-07-14
  • Effects of Phosphonate Structures on Brine−Biotite Interactions under Subsurface Relevant Conditions
    ACS Earth Space Chem. Pub Date : 2018-07-12
    Lijie Zhang, Doyoon Kim, Young-Shin Jun

    Phosphonates have been widely used as scale inhibitors in energy-related subsurface operations, where their performance is greatly affected by interactions with rocks and minerals. However, information about commonly used phosphonate scale inhibitor–shale interactions is limited. In this study, using Fe-bearing mica (biotite) as a model phyllosilicate mineral, the effects of three common phosphonates, namely IDMP (iminodi(methylene)phosphonate), NTMP (nitrilotris(methylene)phosphonate), and DTPMP (diethylenetriaminepenta(methylene)phosphonate), were studied at 95 °C and 102 atm of CO2. During the experiments (0−70 h), IDMP remained stable, while NTMP and DTPMP were degraded and released phosphate, formate, and new phosphonates with smaller molecular weights. Due to the differences in chelating capability, IDMP, with the fewest phosphonate functional groups, promoted biotite dissolution mainly through surface complexation, and DTPMP, with the most functional groups, promoted biotite dissolution mainly through aqueous complexation. Furthermore, the presence of phosphonates enhanced secondary precipitation of P, Fe, and Al-bearing minerals, and their phosphonate structures affected the morphologies, phases, and distributions of secondary precipitates. As a result of phosphonate−biotite interactions (mainly due to surface adsorption), the biotite surfaces became much more hydrophilic. This study provides new insight into structure-dependent phosphonate−mineral interactions, and the results have important implications for the safety and efficiency of energy-related subsurface operations.

    更新日期:2018-07-14
  • The Tuareg shield terranes revisited and extended towards the northern Gondwana margin: Magnetic and gravimetric constraints
    Earth Sci. Rev. (IF 7.491) Pub Date : 2018-07-10
    Sonia Brahimi, Jean-Paul Liégeois, Jean-François Ghienne, Marc Munschy, Amar Bourmatte

    The Trans-Saharan Belt is one of the most important orogenic systems constitutive of the Pan-African cycle, which, at the end of the Neoproterozoic, led to the formation of the Gondwana Supercontinent. It is marked by the opening and closing of oceanic domains, collision of continental blocks and the deformation of thick synorogenic sedimentary basins. It extends from north to south over a distance of 3000 km in Africa, including the Nigerian Shield and the Tuareg Shield as well as their counterparts beneath the Phanerozoic oil-rich North- and South-Saharan sedimentary basins. In this study, we take advantage of potential field methods (magnetism and gravity) to analyze the crustal-scale structures of the Tuareg Shield terranes and to track these Pan-African structures below the sedimentary basins, offering a new, >1000 km extent. The map interpretations are based on the classical potential field transforms and two-dimensional forward modeling. We have identified geophysical units and first-order bounding lineaments essentially defined owing to magnetic and gravimetric anomaly signatures. In particular, we are able to highlight curved terminations, which in the Trans-Saharan context have been still poorly documented. We provide for the first time a rheological map showing a categorization of contrasted basement units from the south of the Tuareg Shield up to the Atlas Belt. These units highlight the contrasted rheological behavior of the Tuareg tectonostratigraphic terranes during (i) the northerly Pan-African tectonic escape characteristic of the Trans-Saharan Belt and (ii) the North Sahara basin development, especially during intraplate reworking tied to the Variscan event. The discovery of a relatively rigid E-W oriented unit to the south of the Atlas system, and on which the escaping Pan-African terranes were blocked, offers a new perspective on the structural framework of the north-Gondwana margin. It will help to understand how occurred the rendezvous of the N-S oriented Pan-African terranes and the E-W oriented Cadomian peri-Gondwanan terranes.

    更新日期:2018-07-12
  • Multiple negative carbon-isotope excursions during the Carnian Pluvial Episode (Late Triassic)
    Earth Sci. Rev. (IF 7.491) Pub Date : 2018-07-12
    Jacopo Dal Corso, Piero Gianolla, Manuel Rigo, Marco Franceschi, Guido Roghi, Paolo Mietto, Stefano Manfrin, Béla Raucsik, Tamás Budai, Hugh C. Jenkyns, Claire E. Reymond, Marcello Caggiati, Giovanni Gattolin, Anna Breda, Agostino Merico, Nereo Preto

    The Carnian Pluvial Episode was a phase of global climatic change and biotic turnover that occurred during the early Late Triassic. In marine sedimentary basins, the arrival of huge amounts of siliciclastic sediments, the establishment of anoxic conditions, and a sudden change of the carbonate factory on platforms marked the Carnian Pluvial Episode. The sedimentary changes are closely associated with abrupt biological turnover among marine and terrestrial groups as, for example, an extinction among ammonoids and conodonts in the ocean, and a turnover of the vertebrate fauna and the flora on land. Multiple negative carbon-isotope excursions were recorded during the Carnian Pluvial Episode in both organic matter and marine carbonates suggesting repeated injection of 13C-depleted CO2 into the ocean–atmosphere system, but their temporal and causal links with the sedimentological and palaeontological changes are poorly understood. We here review the existing carbon-isotope records and present new data on the carbon-isotope composition of organic carbon in selected sections of the western Tethys realm that record the entire Carnian Pluvial Episode. New ammonoid, conodont and sporomorph biostratigraphic data were collected and coupled to an extensive review of the existing biostratigraphy to constrain the age of the sampled sections. The results provide biostratigraphically constrained composite organic carbon-isotope curves for the Carnian. This sheds light on the temporal and causal links between the main carbon-isotope perturbations, and the distinct environmental and biotic changes that mark the Carnian Pluvial Episode. The carbon-isotope records suggest that a series of carbon-cycle perturbations, possibly recording multiple phases of volcanic activity during the emplacement of the Wrangellia Large Igneous Province, disrupted Carnian environments and ecosystems repeatedly over a remarkably long time interval of about 1 million years.

    更新日期:2018-07-12
  • The 2016 Mw 6.7 Aketao earthquake in Muji range, northern Pamir: Rupture on a strike-slip fault constrained by Sentinel-1 radar interferometry and GPS
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-15
    Ping He, Kaihua Ding, Caijun Xu

    On 25 November 2016, the Aketao, Xinjiang earthquake occurred on the Muji fault, which is located at the northernmost end of the right-lateral Karakorum Fault (KF). This event provides a rare chance to gain insights into how the stress accumulates in Pamir margin as the Indian plate collides with the Eurasian plate. Space geodetic measurements including InSAR and GPS were used to obtain coseismic surface displacements associated with this earthquake. Based on a finite fault model, the coseismic slip distribution inverted by the combined datasets indicates that the 2016 Aketao event is caused by a primary shallow strike-slip with minor normal-slip at a steep-dipping angle. To explore the real structure of Muji fault, listric fault model inferred by relocated aftershocks as well as the planar fault model, were used in our slip distribution inversion. The results suggest that the optimal fault model should be a highly-dipping planar fault with two separated asperities. The large slip zone is beneath the surface near the epicenter with a maximum slip of 1.1 m, while the small one in the east breaks the surface, in a good agreement with the field seismic geological survey. The total geodetic moment is 1.35 × 1019N∙m, equivalent to Mw 6.7. The nearly pure dextral strike-slip Aketao earthquake, and the recent 2015 Mw 7.2 sinistral strike-slip Tajikstan earthquake in this region, to some extent, manifest the extension motion is dominated in northern Pamir Plateau, in response to the northward convergence between Indian and Eurasian collision.

    更新日期:2018-07-12
  • A modified model for estimating tree height from PolInSAR with compensation for temporal decorrelation
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-11
    Nafiseh Ghasemi, Valentyn Tolpekin, Alfred Stein

    The RMoG (Random-Motion-over-Ground) model is commonly used to obtain tree height values from PolInSAR images. The RMoG model borrows its structure function from conventional RVoG (Random-Volume-over-Ground) model which is limited for modelling structural variety in canopy layer. This paper extends the RMoG model to improve tree height estimation accuracy by using a Fourier-Legendre polynomial as the structure function. The new model is denoted by the RMoGL model. The proposed modification makes height estimation less prone to errors by enabling more flexibility in representing the vertical structure of the vegetation layer. We applied the RMoGL model on airborne P- and L-band PolInSAR images from the Remingstorp test site in southern Sweden. We compared it with the RMoG and the conventional RVoG models using Lidar height map and field data for validation. For P-band, the relative error was equal to 37.5% for the RVoG model, to 23.7% for the RMoG model, and to 18.5% for the RMoGL model. For L-band it was equal to 30.54% for the RVoG model, to 20.02% for the RMoG model, and to 21.63% for the RMoGL. We concluded that the RMoGL model estimates tree height more accurately in P-band, while in L-band the RMoG model was equally good. The RMoGL model is of a great value for future SAR sensors that are more focused than before on tree height and biomass estimation.

    更新日期:2018-07-12
  • Utilizing satellite radar remote sensing for burn severity estimation
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-07
    Priscilla Addison, Thomas Oommen

    The increasing knowledge in the capabilities of satellite imagery to hazard applications is especially useful in emergency situations where timing and ability to cover large areas are of the essence. For optical imagery, cloud coverage can corrupt an image rendering it unusable for intended emergency analyses. This study proposes the use of Synthetic Aperture Radar (SAR) imagery for burn severity analysis for western United States sites, as an alternative to its optical based counterpart, differenced normalized burn ratio (dNBR). Unlike optical sensors, the radar sensor is an active sensor that is able to penetrate clouds and smoke, an attribute that is crucial in emergency situations where immediate burn severity data are needed to assess the vulnerability of fire affected areas to post-fire hazards. Using C5 decision tree algorithm we developed a SAR-based metric that attempts to classify burn severities of fire affected locations in the western USA. We then compared the performance of this developed metric to that obtained by the existing dNBR metric, to determine if there is any merit to its adoption as an alternative for the western USA landscape. The results showed the SAR approach to produce higher validation metrics in comparison to the dNBR. It had an overall accuracy and kappa of 60% and 0.35, respectively, in comparison to the 35% and 0.1 of the dNBR approach. This shows an improved ability to quickly obtain burn severity data and make better informed decisions in emergency situations.

    更新日期:2018-07-12
  • Synergy of sampling techniques and ensemble classifiers for classification of urban environments using full-waveform LiDAR data
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-06
    Mohsen Azadbakht, Clive S. Fraser, Kourosh Khoshelham

    Fine scale land cover classification of urban environments is important for a variety of applications. LiDAR data has been increasingly used, separately or in conjunction with other remote sensing data, for providing land cover classification due to its high geometric accuracy as well as its additional radiometric information. An important issue in the classification of remote sensing data is the inevitable imbalance of training samples, which usually results in poor classification performance in classes with few samples (minority classes). In this paper, a synergy of sampling techniques in data mining with ensemble classifiers is proposed to address the data imbalance problem in the training datasets. Several sampling strategies, including under-sampling the majority classes, synthetic over-sampling the minority classes, hybrid-sampling, and under-sampling aggregation are examined. The results from two different datasets show superior performance of ensemble classifiers when integrated with sampling techniques. In particular, under-sampling aggregation and hybrid sampling coupled with random forests resulted in 16.7% and 5.5% improvements in the G-mean measure in two experimental datasets examined.

    更新日期:2018-07-12
  • Exploring the Potential of Sentinels-1 & 2 of the Copernicus Mission in Support of Rapid and Cost-effective Wildfire Assessment
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-06
    Daniel Colson, George P. Petropoulos, Konstantinos P. Ferentinos

    The present study explores the use of the recently launched Sentinel-1 and -2 data of the Copernicus mission in wildfire mapping with a particular focus on retrieving information on burnt area, burn severity as well as in quantifying soil erosion changes. As study area, the Sierra del Gata wildfire occurred in Spain during the summer of 2015 was selected. First, diverse image processing algorithms for burnt area extraction from Sentinel-2 data were evaluated. In the next step, burn severity maps were derived from Sentinel-2 data alone, and the synergy between Sentinel-2 & Sentinel-1 for this purpose was evaluated. Finally, the impact of the wildfire to soil erodibility estimates derived from the Revised Universal Soil Loss Equation (RUSLE) model implemented to the acquired Sentinel images was explored. In overall, the Support Vector Machines (SVMs) classifier obtained the most accurate burned area mapping, with a derived accuracy of 99.38%. An object-based SVMs classification using as input both optical and radar data was the most effective approach of delineating burn severity, achieving an overall accuracy of 92.97%. Soil erosion mapping predictions allowed quantifying the impact of wildfire to soil erosion at the studied site, suggesting the method could be potentially of a wider use. Our results contribute to the understanding of wildland fire dynamics in the context of the Mediterranean ecosystem, demonstrating the usefulness of Sentinels and of their derived products in wildfire mapping and assessment.

    更新日期:2018-07-12
  • LiDAR patch metrics for object-based clustering of forest types in a tropical rainforest
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-02
    Cici Alexander, Amanda H. Korstjens, Graham Usher, Matthew G. Nowak, Gabriella Fredriksson, Ross A. Hill

    Tropical rainforests support a large proportion of the Earth’s plant and animal species within a restricted global distribution, and play an important role in regulating the Earth’s climate. However, the existing knowledge of forest types or habitats is relatively poor and there are large uncertainties in the quantification of carbon stock in these forests. Airborne Laser Scanning, using LiDAR, has advantages over other remote sensing techniques for describing the three-dimensional structure of forests. With respect to the habitat requirements of different species, forest structure can be defined by canopy height, canopy cover and vertical arrangement of biomass. In this study, forest patches were identified based on classification and hierarchical merging of a LiDAR-derived Canopy Height Model in a tropical rainforest in Sumatra, Indonesia. Attributes of the identified patches were used as inputs for k-medoids clustering. The clusters were then analysed by comparing them with identified forest types in the field. There was a significant association between the clusters and the forest types identified in the field, to which arang forests and mixed agro-forests contributed the most. The topographic attributes of the clusters were analysed to determine whether the structural classes, and potentially forest types, were related to topography. The tallest clusters occurred at significantly higher elevations (>850 m) and steeper slopes (>26°) than the other clusters. These are likely to be remnants of undisturbed primary forests and are important for conservation and habitat studies and for carbon stock estimation. This study showed that LiDAR data can be used to map tropical forest types based on structure, but that structural similarities between patches of different floristic composition or human use histories can limit habitat separability as determined in the field.

    更新日期:2018-07-12
  • Building a spatiotemporal index for Earth Observation Big Data
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-02
    Jizhe Xia, Chaowei Yang, Qingquan Li

    With the rapid advancement of Earth Observation systems, Earth Observation data has been collected and accumulated at an unprecedented fast rate. Earth Observation Big Data emerged with new opportunities for human to better understand the Earth systems, but also pose a tremendous challenge for efficiently transforming Big Data into Earth Observation Big Value. Targeting on this challenge, a well-organized data index is a key to enhance the “Data-Value” transformation by accelerating the access to data. Although various data indexing approaches have been proposed with different optimization objectives, literature shows that there are still apparent limitations for Earth Observation data indexing. This paper aims to build a spatiotemporal indexing for Earth Observation Big Data. Specifically, a) to support various Earth Observation Data Infrastructures, we adopt an indexing framework to efficiently retrieve data with various textual, spatial and temporal requirements; b) a distributed indexing structure is designed to improve the index scalability; c) data access pattern is integrated to the indexing algorithm for both spatial and workload balancing. The results show that our indexing approach outperforms traditional indexing approaches and accelerates the access to Earth Observation data. We envision that data indexing will become a key technology that drives fundamental Earth Observation advancements in the Big Data era.

    更新日期:2018-07-12
  • Landsat time series analysis for temperate forest cover change detection in the Sierra Madre Occidental, Durango, Mexico
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-02
    Alís Novo-Fernández, Shannon Franks, Christian Wehenkel, Pablito M. López-Serrano, Matthieu Molinier, Carlos A. López-Sánchez

    The Sierra Madre Occidental (SMO) is the longest continuous mountain complex in Mexico and is characterised by high species diversity and a high proportion of endemism. The rate of deforestation is high in Mexico, as in other megadiverse countries, and protection of the country’s biodiversity is a top priority. Quantification of changes in vegetation cover is essential for this purpose. Temporal information is required to enable classification of vegetation cover and change processes. In this study, the disturbances that occurred in the temperate forest of the SMO in the State of Durango (Mexico) during the period 1986–2012 were quantified using Landsat Time Series Stacks (LTSS) and the Vegetation Change Tracker (VCT) algorithm. The results obtained confirmed that land cover changes were detected with high overall accuracy (97.6%). In order to analyze the forest losses corresponding to the only official data available in Mexico, we retrieved land use and vegetation mapping (USV) data from the Mexican National Institute of Statistics and Geography (INEGI). The aridity index was established and fragmentation analysis was carried out in the study area, showing that forest pests and forest fires were the principal disturbance events in the SMO of Durango, and that the climate greatly influenced the occurrence of disturbances. The LTSS-VCT analysis revealed that for the period 1986–2012, about 34% of the temperate forest cover in the SMO in Durango was lost due to different types of disturbance, representing an annual rate of loss of forest cover of 1.3% and affecting 32,840 ha of land per year. The trend analysis of USV data showed very similar changes to those indicated by the LTSS-VCT analysis in terms of loss of temperate forest. However, differences were observed in regards to the absolute values of forest cover and vegetation loss, with analysis of the USV data indicating forest losses of 28% due to disturbances and an annual disturbance rate of 1%, affecting 49,940 ha of land per year. The LTSS-VCT approach proved efficient for mapping data on forest disturbance acquired by a medium spatial resolution (Landsat) sensor in the SMO in the State of Durango, providing satisfactory results and at low cost.

    更新日期:2018-07-12
  • Using FloodRisk GIS freeware for uncertainty analysis of direct economic flood damages in Italy
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-30
    R. Albano, A. Sole, J. Adamowski, A. Perrone, A. Inam

    The considerable increase in flood damages in Europe in recent decades has shifted attention from flood protection to flood risk management. Assessments of expected damage provide critical information for flood risk management efforts. The evaluation of potential damages under different flood scenarios through quantification of their ability to provide relative short-, medium- and long-term risk reduction, supports decision-makers in discriminating among several alternative mitigation actions. End-users should be aware of, and knowledgeable about, the limitations and uncertainties of such analyses, as well-informed decisions regarding efficient and sustainable flood risk management will become increasingly relevant under future climate and socio-economic changes. In this context, a method was developed to identify and quantify the role of the input parameters in the uncertainty of the potential flood economic damage assessment in urban areas with low sloping/flat terrain and complex topography using a GIS-based, free and open-source software called Floodrisk. Sets of plausible input parameters for the model’s two flood loss modelling subroutines (hydraulic modelling and damage estimation) were dynamically combined to quantify the contribution of their inner parameters to the total damage assessment uncertainty. To estimate the contributions of each input to overall model uncertainty, the combination of input parameters that minimized the error in the spatial distribution assessment of the extensive damages affecting (downtown) Albenga (Italy), enumerated after the historical Centa River flood of November 5, 1994, was taken as a reference. In this specific case, a high epistemic uncertainty for the damage estimation module was noted for the specific type and form of the damage functions used. In the absence of region-specific depth-damage functions, the vulnerability curves were adapted from a range of geographic and socio-economic studies. Given the strong dependence of model uncertainty and sensitivity to local characteristics, the epistemic uncertainty associated with the risk estimate was reduced by introducing additional information into the risk analysis. Implementing newly developed site-specific curves and a more detailed classification of the construction typology of the buildings at risk, led to a substantial decrease in modelling uncertainty, along with a decrease in the sensitivity of the flood loss estimation to the uncertainty in the depth-damage function input parameter. These findings indicated the need to produce and openly disseminate data in order to develop micro-scale risk analysis through site-specific vulnerability curves. Moreover, this study highlighted the urgent need for research on the development and implementation of methods and models for the assimilation of uncertainties in decision-making processes.

    更新日期:2018-07-12
  • Tree species classification using plant functional traits from LiDAR and hyperspectral data
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-30
    Yifang Shi, Andrew K. Skidmore, Tiejun Wang, Stefanie Holzwarth, Uta Heiden, Nicole Pinnel, Xi Zhu, Marco Heurich

    Plant functional traits have been extensively used to describe, rank and discriminate species according to their variability between species in classical plant taxonomy. However, the utility of plant functional traits for tree species classification from remote sensing data in natural forests has not been clearly established. In this study, we integrated three selected plant functional traits (i.e. equivalent water thickness (Cw), leaf mass per area (Cm) and leaf chlorophyll (Cab)) retrieved from hyperspectral data with hyperspectral derived spectral features and airborne LiDAR derived metrics for mapping five tree species in a natural forest in Germany. Our results showed that when plant functional traits were combined with spectral features and LiDAR metrics, an overall accuracy of 83.7% was obtained, which was statistically significantly higher than using LiDAR (65.1%) or hyperspectral (69.3%) data alone. The results of our study demonstrate that plant functional traits retrieved from hyperspectral data using radiative transfer models can be used in conjunction with hyperspectral features and LiDAR metrics to further improve individual tree species classification in a mixed temperate forest.

    更新日期:2018-07-12
  • Desertification trends in the Northeast of Brazil over the period 2000–2016
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-30
    Javier Tomasella, Rita M. Silva Pinto Vieira, Alexandre A. Barbosa, Daniel A. Rodriguez, Marcos de Oliveira Santana, Marcelo F. Sestini

    Information about changes in land use and land cover is useful to address issues related to drylands management, as well as to support decision-making related to the sustainable use of soils. Since drylands are frequently affected by accelerated soil erosion, land degradation and desertification associated with vegetation cover losses, constant monitoring of land use and land cover changes are required. However, land use and land cover maps are often not available, making it difficult to monitor degradation. Therefore, in this work, we developed an efficient mapping method to monitor bare soil areas, which are indicative of land degradation in the case of the Northeast of Brazil, using Normalized Difference Vegetation Index images. The proposed methodology was field calibrated and applied to the region using 17-year (2000–2016) NDVI maps, with a spatial resolution of 250 m. Based on bare soil mapping, we estimated the degree of degradation using an index calculated from the persistence and frequency of bare soil during the study period. The results indicated that the degraded areas increased in the period of the study, mainly in areas of pasture and Caatinga. This expansion has been accelerated due to the severe drought that affected the region since 2011.

    更新日期:2018-07-12
  • Reflectance reference target at Järvselja, Estonia for the calibration of optical remote sensing sensors and lessons learned
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-29
    Andres Kuusk, Joel Kuusk, Mait Lang, Jouni Peltoniemi, Maria Gritsevich, Jan Pisek

    A calibration target for the support of airborne and satellite measurements was built at the Järvselja site for ecological and remote sensing studies located in southeastern Estonia. The calibration target is a 10 × 10 m concrete panel which is protected by a removable roof. Optical properties of the panel are carefully studied in order to serve as a reference in spectroscopic remote sensing measurements. In this study we report the spectral distribution of reflectance in the wavelength range of 350–2500 nm, the angular distribution of directional reflectance and the linear polarization of the reflected radiation. The reflectance spectrum of the panel is smooth in the visible and NIR wavelengths but with steep decrease at wavelengths less than 400 nm. Variations of reflectance over the panel surface are less than 1%. The radiation is partly polarized in forward scattering direction. No temporal changes of optical properties have been observed. The calibration target improves the metrological quality of airborne spectral measurements at the Järvselja test site and neighboring areas. It can also be used for ground truth to aid the validation of adjacency correction algorithms for data from high spatial resolution satellite images, as well as a reference for the registration of airborne and satellite images. It can also serve as an elevation reference for both lidar and radar altimeter measurements.

    更新日期:2018-07-12
  • Use of MSI/Sentinel-2 and airborne LiDAR data for mapping vegetation and studying the relationships with soil attributes in the Brazilian semi-arid region
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-28
    Hilton Luís Ferraz da Silveira, Lênio Soares Galvão, Ieda Del’Arco Sanches, Iedo Bezerra de Sá, Tatiana Ayako Taura

    The Caatinga is an important ecosystem in the semi-arid region of northeast Brazil and a natural laboratory for the study of plant adaptation to seasonal water stress or prolonged droughts. The soil water availability for plants depends on plant root depth and soil properties. Here, we combined for the first time the remote sensing classification of Caatinga physiognomies with soil information derived from geostatistical analysis to relate vegetation distribution with physico-chemical attributes of soils. We evaluated the potential of multi-temporal data acquired by the MultiSpectral Instrument (MSI)/Sentinel-2 for Random Forest (RF) classification of seven physiognomies. In addition, we analyzed the contribution of airborne LiDAR metrics to improve classification accuracy compared to six vegetation indices (VIs) and 10 reflectance bands from the MSI instrument. Using a detailed soil survey, the spatial distribution of the vegetation physiognomies mapped by RF was associated with the variability of 20 physico-chemical attributes of 75 soil profiles submitted to principal components analysis (PCA) and ordinary kriging. The results showed gains in overall classification accuracy with use of the multi-temporal data over the mono-temporal observations. Gains in classification of arboreous Caatinga were also observed after the insertion of LiDAR metrics in the analysis, especially the percentage of vegetation cover with height greater than 5 m, the terrain elevation and the standard deviation of vegetation height. Overall, the most important metrics for classification were the VIs, especially the Enhanced Vegetation Index (EVI), Normalized Difference Infrared Index (NDII-1), Optimized Soil-Adjusted Vegetation Index (OSAVI) and the Normalized Difference Vegetation Index (NDVI). The most important MSI/Sentinel-2 bands were positioned in the red-edge spectral interval. From PCA, soil attributes responsible for most of the data variance were related to soil fertility, soil depth and rock fragments in the surface horizon. The amounts of gravels and pebbles were factors of physiognomic variability with shrub and sub-shrub Caatinga occurring preferentially over shallow and stony soils. By contrast, arboreous Caatinga occurred over soils with total profile depth greater than 1 m. Finally, areas of sub-shrub Caatinga had greater values of cation exchange capacity (CEC) and water retention at field capacity than areas of arboreous Caatinga. The differences were statistically significant at 95% confidence level, as indicated by Mann-Whitney U tests.

    更新日期:2018-07-12
  • Effects of pre-processing methods on Landsat OLI-8 land cover classification using OBIA and random forests classifier
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-26
    Darius Phiri, Justin Morgenroth, Cong Xu, Txomin Hermosilla

    The application of Landsat satellite imagery in land cover classification is affected by atmospheric and topographic errors, which have led to the development of different correction methods. In this study, moderate resolution atmospheric transmission (MODTRAN) and dark object subtraction (DOS) atmospheric corrections, and cosine topographic correction were evaluated individually and combined in a heterogeneous landscape in Zambia. These pre-processing methods were tested using a combination of object-based image analysis (OBIA) and Random Forests (RF) non-parametric classifier (hereafter referred to as OBIA-RF). This assessment aimed at understanding the combined effects of different pre-processing methods and the OBIA-RF classification method on the accuracy of Landsat operational land (OLI-8) imagery with different spatial resolutions. Here, we used pansharpened and standard Landsat OLI-8 images with 15 and 30 m spatial resolutions, respectively. The results showed that non pre-processed images reached a classification accuracy of 68% for pansharpened and 66% for standard Landsat OLI-8. Classification accuracy improved to 93% (pansharpened) and 86% (standard) when combined MODTRAN and cosine topographic correction pre-processing were applied. The results highlight the importance of pansharpening, as well as atmospheric and topographic corrections for Landsat OLI-8 imagery, when used as input in OBIA classification with the RF classifier.

    更新日期:2018-07-12
  • 更新日期:2018-07-12
  • Using object-based image analysis to conduct high- resolution conifer extraction at regional spatial scales
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-21
    K. Benjamin Gustafson, Peter S. Coates, Cali L. Roth, Michael P. Chenaille, Mark A. Ricca, Erika Sanchez-Chopitea, Michael L. Casazza

    Distributional expansion and infill of pinyon (Pinus monophylla) and juniper (Juniperus osteosperma, J. occidentalis) trees (hereinafter, "pinyon-juniper") into sagebrush ecosystems alters the ecological function and economic viability of these ecosystems and represents a major contemporary challenge facing land and wildlife managers. Therefore, accurate and high-resolution maps of pinyon-juniper distribution and abundance across broad geographic extents would facilitate science that quantifies ecological effects of pinyon-juniper expansion and help guide land management decisions that better target areas for pinyon-juniper treatment projects. We mapped conifers at a high (1- m2; i.e., 1 × 1-m) resolution across the majority of Nevada and northeastern California. We used digital orthophoto quad tiles from National Agriculture Imagery Program (USDA, 2013) to classify conifers using automated feature extraction (AFE) with the program Feature Analyst™ (Overwatch, 2013). Overall accuracy was >86% across all mapped areas for ground referencing methods. We provide five sets of full-extent maps for land managers: (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1-m2 resolution; (3) a 900-m2 resolution raster representing percentages of conifer canopy cover within each cell; (4) 1-m2 resolution canopy cover classification rasters derived from a 50-m radius moving window analysis; and (5) an example map derived from our canopy cover product that prioritizes pinyon-juniper treatment by significance to sage-grouse habitat improvement. Importantly, the canopy cover maps were developed to allow user-specified flexibility based on their own objectives (i.e., develop phases of expansion). These products improve upon or complement existing conifer maps for the Western United States and will help facilitate habitat management and sagebrush ecosystem restoration through an accurate understanding of conifer distribution and abundance at multiple spatial scales.

    更新日期:2018-07-12
  • Downscaling of surface air temperature over the Tibetan Plateau based on DEM
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-20
    Lirong Ding, Ji Zhou, Xiaodong Zhang, Shaomin Liu, Ruyin Cao

    Surface air temperature (Ta) is critical to the studies of radiation balance, energy budget, and water cycle. It is a necessary input for associated models. Most of the current Ta datasets of reanalysis products have limitations at local scales due to their coarse spatial resolutions. For better modeling the radiation balance, energy budget, and water cycle over the Tibetan Plateau, this study proposes a practical method for Ta downscaling based on the digital elevation model. This method is applied to downscale Ta of the China regional surface meteorological feature dataset (CRSMFD) at 0.1° and the ERA-interim (ERAI) product at 0.125° to 0.01°. The daily mean Ta and the 3-hourly instantaneous Ta with a 0.01° are obtained. The downscaled Ta are evaluated from the perspectives of accuracy and image quality. Results show that the daily mean Ta downscaled from the CRSMFD product has a RMSE of 1.13 ± 1.0 K at 105 meteorological stations and RMSEs of 0.96 K to 2.34 K at three experimental stations; the instantaneous Ta downscaled from CRSMFD has RMSEs of 1.02 K to 4.0 K at the three experimental stations. Ta after downscaling has better agreement with the ground measured Ta than before downscaling, especially in mountain areas. By contrast, Ta downscaled from the ERAI product has unacceptable accuracy due to the great uncertainty of the ERAI Ta over the Tibetan Plateau. With the proposed method, a 0.01° Ta dataset from 2000 to 2015 over the Tibetan Plateau was generated to satisfy related studies and applications.

    更新日期:2018-07-12
  • An automatic change detection approach for rapid flood mapping in Sentinel-1 SAR data
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-18
    Yu Li, Sandro Martinis, Simon Plank, Ralf Ludwig

    In this paper, a two-step automatic change detection chain for rapid flood mapping based on Sentinel-1 Synthetic Aperture Radar (SAR) data is presented. First, a reference image is selected from a set of potential image candidates via a Jensen-Shannon (JS) divergence-based index. Second, saliency detection is applied on log-ratio data to derive the prior probabilities of changed and unchanged classes for initializing the following expectation-maximization (EM) based generalized Gaussian mixture model (GGMM). The saliency-guided GGMM is capable of capturing the primary pixel-based change information and handling highly imbalanced datasets. A fully-connected conditional random field (FCRF) model, which takes long-range pairwise potential connections into account, is integrated to remove the ambiguities of the saliency-guided GGMM and to achieve the final change map. The whole process chain is automatic with an efficient computation. The proposed approach was validated on flood events at the Evros River, Greece and the Wharfe River and Ouse River in York, United Kingdom. Kappa coefficients (k) of 0.9238 and 0.8682 were obtained respectively. The sensitivity analysis underlines the robustness of the proposed approach for rapid flood mapping.

    更新日期:2018-07-12
  • Acceleration and fragmentation of CORINE land cover changes in the United Kingdom from 2006–2012 detected by Copernicus IMAGE2012 satellite data
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-17
    B. Cole, G. Smith, H. Balzter

    The CORINE land cover maps present the longest series of land cover maps with a consistent class labelling system and date back to 1985. This paper presents the results of the CORINE land cover mapping of the United Kingdom for 2012 and the corresponding land cover change map from 2006 to 2012. It compares the rates of change with those of the preceding land cover change map 2000–2006 and finds that land cover change has become smaller in scale, more diverse in types of change and affects more land cover polygons than in the past reporting period. Land cover change from 2006 to 2012 affected almost 60% more land cover polygons than from 2000 to 2006. A greater variety of 165 types of land cover change was detected from 2006 to 2012 than the 67 types of change from 2000 to 2006. The total land cover change area increased by over 21,000 ha or 11% but remained at around 1% of the total land area of the UK. Rotation forestry mostly of conifer forests was a dominant type of land cover change in both periods (53% of overall change from 2000 to 2006 and 54% from 2006 to 2012), followed by growth and replanting of conifer forest. From 2006 to 2012 the replanting rate decreased by almost 15,000 ha compared to 2000–2006 and a smaller decrease in planting of broadleaf and mixed forests was also observed. Urban land take continued from 2006 to 2012 in the UK, with over 16,000 ha of increase in artificial surfaces. The rate of change from other land cover types to artificial surfaces accelerated from 2006 to 2012. However, we urge caution when interpreting the rate of land take, as it includes wind farms in forested areas which leave the forest largely intact apart from an access road and the wind turbine sites. We also found that the inference from the land cover change matrices is dependent on the level of class aggregation (level 1, 2 or 3).

    更新日期:2018-07-12
  • A robust object-based woody cover extraction technique for monitoring mine site revegetation at scale in the monsoonal tropics using multispectral RPAS imagery from different sensors
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-07-10
    Timothy G. Whiteside, Renée E. Bartolo

    Revegetation success is a key element of mine site rehabilitation. A number of criteria related to mine site close-out are associated with revegetation. The monitoring of mine site revegetation efforts have traditionally been undertaken using field-based plot or transect methods. Often the sampling design for this monitoring is limited due to resource constraints, therefore reducing the statistical power of the data and missing information over most of the mine site. The recent advances in Remotely Piloted Aircraft Systems (RPAS) technology for remote sensing enables the collection of appropriate scale data over entire mine sites reducing the need for sampling and eliminating potential bias. This paper describes an object-based technique for extracting woody cover and estimating proportional woody cover from RPAS imagery over the rehabilitated Jabiluka mine site located in the tropical north of Australia. The technique was tested on three data sets that covered three different dates, two different sensors, and two different processing methods. Overall woody cover detection accuracies from each data set were over 95%. Proportional woody cover derived from the technique showed strong linear relationships with manually estimated cover (r2 > 0.88). This study shows that the technique is robust and works with a range of RPAS data sets and enables at scale analysis of woody cover change between dates. The technique will be an important component of ongoing monitoring of mine site revegetation in the region.

    更新日期:2018-07-12
  • Monitoring mangrove forest change in China from 1990 to 2015 using Landsat-derived spectral-temporal variability metrics
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-15
    Luojia Hu, Wenyu Li, Bing Xu

    Reliable information of national-level mangrove forest change in China is urgently needed for Chinese government to make appropriate policies of mangrove forest conservation. Yet, employing traditional methods (all based on single-date remotely sensed imagery) to accurately map mangrove forest in China is relatively difficult, given the influence of tide variability on the spectrum of a large proportion of mangrove forest and the spectral similarity between mangrove forest, cropland, and natural terrestrial vegetation. However, the temporal profile of spectrum for mangrove forest is likely to be distinctive, due to the influence of tide variability on mangrove forest spectrum. Therefore, in this study, we investigated the potential of using some robust spectral-temporal variability metrics (quantiles), capturing characteristics of temporal profiles for different land cover types, to reliably separate mangrove forest. We also mapped mangrove forest in China for 6 periods (1986–1992, 1993–1997, 1998–2002, 2003–2007, 2008–2012, and 2013–2017) and analyzed mangrove forest change over past decades using all available Landsat imagery. Producer’s and user’s accuracies of the land cover type “mangrove forest” for all periods are high (>90%), indicating the effectiveness of our method. We found that mangrove forest in China has significantly increased, from 10774 ha in the period 1986–1992 to 19220 ha in the period 2013–2017. There is also a potential for employing our method to map global mangrove forest around 2015.

    更新日期:2018-07-12
  • Agro-meteorological risks to maize production in Tanzania: Sensitivity of an adapted Water Requirements Satisfaction Index (WRSI) model to rainfall
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-14
    Elena Tarnavsky, Erik Chavez, Hendrik Boogaard

    The Water Requirements Satisfaction Index (WRSI) – a simplified crop water stress model – is widely used in drought and famine early warning systems, as well as in agro-meteorological risk management instruments such as crop insurance. We developed an adapted WRSI model, as introduced here, to characterise the impact of using different rainfall input datasets, ARC2, CHIRPS, and TAMSAT, on key WRSI model parameters and outputs. Results from our analyses indicate that CHIRPS best captures seasonal rainfall characteristics such as season onset and duration, which are critical for the WRSI model. Additionally, we consider planting scenarios for short-, medium-, and long-growing cycle maize and compare simulated WRSI and model outputs against reported yield at the national level for maize-growing areas in Tanzania. We find that over half of the variability in yield is explained by water stress when the CHIRPS dataset is used in the WRSI model (R2 = 0.52–0.61 for maize varieties of 120–160 days growing length). Overall, CHIRPS and TAMSAT show highest skill (R2 = 0.46–0.55 and 0.44–0.58, respectively) in capturing country-level crop yield losses related to seasonal soil moisture deficit, which is critical for drought early warning and agro-meteorological risk applications.

    更新日期:2018-07-12
  • Assessment of atmospheric correction methods for Sentinel-2 images in Mediterranean landscapes
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-13
    Ion Sola, Alberto García-Martín, Leire Sandonís-Pozo, Jesús Álvarez-Mozos, Fernando Pérez-Cabello, María González-Audícana, Raquel Montorio Llovería

    Atmospheric correction of optical satellite imagery is an essential pre-processing for modelling biophysical variables, multi-temporal analysis, and digital classification processes. Sentinel-2 products available for users are distributed by the European Space Agency (ESA) as Top Of Atmosphere reflectance values in cartographic geometry (Level-1C product). In order to obtain Bottom Of Atmosphere reflectance images (Level-2A product) derived from this Level-1C products, ESA provides the SEN2COR module, which is implemented in the Sentinel Application Platform. Alternatively, ESA recently distributes Level-2A products processed by SEN2COR with a default configuration. On the other hand, the conversion from Level-1C to Level-2A product can be generated using alternative atmospheric correction methods, such as MAJA, 6S, or iCOR. In this context, this paper aims to evaluate the quality of Level-2A products obtained through different methods in Mediterranean shrub and grasslands by comparing data obtained from Sentinel-2 imagery with field spectrometry data. For that purpose, six plots with different land covers (asphalt, grass, shrub, pasture, and bare soil) were analyzed, by using synchronous imagery to fieldwork (from July to September 2016). The results suggest the suitability of the applied atmospheric corrections, with coefficients of determination higher than 0.90 and root mean square error lower than 0.04 achieving a relative error in bottom of atmosphere reflectance of only 2–3%. Nevertheless, minor differences were observed between the four tested methods, with slightly varying results depending on the spectral band and land cover.

    更新日期:2018-07-12
  • Long-term hazard analysis of destructive storm surges using the ADCIRC- SWAN model: A case study of Bohai Sea, China
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-15
    Yanping Wang, Xinyan Mao, Wensheng Jiang

    Destructive storm surges bring large waves and unusually high surges of water to coastal areas, resulting in many human casualties and significant economic loss. In this study, an unstructured grid wave-current coupled model was developed for the Bohai Sea, China, using the ADCIRC (ADvanced CIRCulation) and SWAN (Simulating WAves Nearshore) models to simulate 32 disastrous storm surge events from 1985 to 2014. The return storm surge elevation in the Bohai Sea using the Gumbel method is obtained and compared with previous results. It is found that extratropical cyclones and cold air play important roles in storm surges in the Laizhou Bay and have more influence than tropical cyclones. Moreover, the joint probabilities of surge and wave are obtained by using the Gumbel logistical model. The results show that the effect of waves in surge-wave joint probabilities on the central basin of the Bohai Sea is more significant than that on the Bohai Sea coast. By establishing a system to assess the relative risks of storm surges in the Bohai Sea, it is found that Laizhou Bay is in the greatest danger.

    更新日期:2018-07-12
  • A data mining approach for global burned area mapping
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-15
    Rubén Ramo, Mariano García, Daniel Rodríguez, Emilio Chuvieco

    Global burned are algorithms provide valuable information for climate modellers since fire disturbance is responsible of a significant part of the emissions and their related impact on humans. The aim of this work is to explore how four different classification algorithms, widely used in remote sensing, such as Random Forest (RF), Support Vector Machine (SVM), Neural Networks (NN) and a well-known decision tree algorithm (C5.0), for classifying burned areas at global scale through a data mining methodology using 2008 MODIS data. A training database consisting of burned and unburned pixels was created from 130 Landsat scenes. The resulting database was highly unbalanced with the burned class representing less than one percent of the total. Therefore, the ability of the algorithms to cope with this problem was evaluated. Attribute selection was performed using three filters to remove potential noise and to reduce the dimensionality of the data: Random Forest, entropy-based filter, and logistic regression. Eight out of fifty-two attributes were selected, most of them related to the temporal difference of the reflectance of the bands. Models were trained using an 80% of the database following a ten-fold approach to reduce possible overfitting and to select the optimum parameters. Finally, the performance of the algorithms was evaluated over six different regions using official statistics where they were available and benchmark burned area products, namely MCD45 (V5.1) and MCD64 (V6). Compared to official statistics, the best agreement was obtained by MCD64 (OE = 0.15, CE = 0.29) followed by RF (OE = 0.27, CE = 0.21). For the remaining three areas (Angola, Sudan and South Africa), RF (OE = 0.47, CE = 0.45) yielded the best results when compared to the reference data. NN and SVM showed the worst performance with omission and commission error reaching 0.81 and 0.17 respectively. SVM and NN showed higher sensitivity to unbalanced datasets, as in the case of burned area, with a clear bias towards the majority class. On the other hand, tree based algorithms are more robust to this issue given their own mechanisms to deal with big and unbalanced databases.

    更新日期:2018-07-12
  • Urban tree health assessment using airborne hyperspectral and LiDAR imagery
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-15
    J. Degerickx, D.A. Roberts, J.P. McFadden, M. Hermy, B. Somers

    Urban trees provide valuable ecosystem services but are at the same time under continuous pressure due to unfavorable site conditions. In order to better protect and manage our natural capital, urban green managers require frequent and detailed information on tree health at the city wide scale. In this paper we developed a workflow to monitor tree defoliation and discoloration of broadleaved trees in Brussels, Belgium, through the combined use of airborne hyperspectral and LiDAR data. Individual trees were delineated using an object-based tree detection and segmentation algorithm primarily based on LiDAR data with an average accuracy of 91%. We constructed Partial Least Squares Regression (PLSR) models to derive tree chlorophyll content (RMSE = 2.8 μg/cm²; R² = 0.77) and Leaf Area Index (LAI; RMSE = 0.5; R² = 0.66) from the average canopy spectrum. Existing spectral indices were found to perform significantly worse (RMSE > 7 μg/cm² and >1.5 respectively), mainly due to contamination of tree spectra by neighboring background materials. In the absence of local calibration data, the applicability of PLSR to other areas, sensors and tree species might be limited. Therefore, we identified the best performing/least sensitive spectral indices and proposed a simple pixel selection procedure to reduce disturbing background effects. For LAI, laser penetration metrics derived from LiDAR data attained comparable accuracies as PLSR and were suggested instead. Detection of healthy and unhealthy trees based on remotely sensed tree properties matched reasonably well with a more traditional visual tree assessment (93% and 71% respectively). If combined with early tree stress detection methods, the proposed methodology would constitute a solid basis for future urban tree health monitoring programs.

    更新日期:2018-07-12
  • Possibility of optimized indices for the assessment of heavy metal contents in soil around an open pit coal mine area
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-15
    Rukeya Sawut, Nijat Kasim, Abdugheni Abliz, Li Hu, Ahunaji Yalkun, Balati Maihemuti, Shi Qingdong

    Spectroscopy is regarded as a quick and nondestructive method to classify and quantitatively analyze many elements of the soil. Visible and Near-infrared reflectance spectroscopy offers a conductive tool for investigating soil heavy metal pollution. The main goal of this work is to obtain spectral optimized indices (RSI, NPDI and NDSI) related to soil heavy metal Arsenic (As), to estimate the As contents in soil based on geographically weighted regression model (GWR), and to investigate the plausibility of using these spectral optimized indices to map the distribution of heavy metal Arsenic in the soil of coal mining areas. The spectral optimized indices (RSI, NPDI and NDSI) derived from the original and transformed reflectance (the reciprocal (1/R), logarithm (lgR), logarithm-reciprocal (1/lgR) and root mean square method ( R ) were used to construct the GWR models. Then, the variables (RSIs, NPDIs and NDIs) were applied in estimating the Arsenic (As) concentration and in the mapping of the As distribution in this study region. The NPDIs calculated by the original and transformed reflectance (R, 1/R, lgR, 1/lgR, and R ) indicated higher correlation coefficient values than NDSI and RSI. The highest correlation coefficient and lowest p-values (r≥0.73 and p=0.001) were found in thenear-infrared (NIR, 780–1100 nm) and shortwave infrared (SWIR, 1100–1935 nm). From the 4 prediction models (GWR) performances, it can be seen that Model-a (R) showed superior performance to the other three models (Model-b (1/R), Model-c ( R ) and Model-d (lgR)), and it has the highest validation coefficients (R2 = 0.831, RMSE =4.912 μg/g, RPD=2.321) and lowest AIC (Akaike Information Criterion) value (AIC=179.96). NPDI1417 nm, 1246 nm is more sensitive and potential hyperspectral index for As in the study area. Thus, the two band optimized index (NPDI1417 nm, 1246 nm) might be recommended as an indicator for estimating soil As content. The hyperspectral optimized indices may help to quickly and accurately evaluate Arsenic contents in soil, and furthermore, the results provide theoretical and data support to access the distribution of heavy metal pollution in surface soil, promoting fast and efficient investigation of mining environment pollution and sustainable development of ecology.

    更新日期:2018-07-12
  • On the estimation of tree mortality and liana infestation using a deep self-encoding network
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-15
    Wei Li, Carlos Campos-Vargas, Philip Marzahn, Arturo Sanchez-Azofeifa

    Global environmental change leads to the variation in the relative coverage of dead trees, liana-infested and non-liana-infested trees in many tropical forests. Increase in the coverage of lianas had adverse effects on forested ecosystems such as decreasing tree growth rates and increasing tree mortality. This paper proposes a classification framework that integrates unmanned aerial vehicle systems (UAVs)-derived multi-spectral images and a Deep self-encoding network (DSEN) with the goal of monitoring and quantifying the relative coverage of dead trees, liana-infested, and non-liana-infested trees at high spatial scales. Today's UAVs-derived multi-spectral images provide the much necessary high resolution/quality data to monitor ecosystem-level processes at low cost and on demand. On the other hand, DSEN, a state-of-the-art classification approach that uses multiple layers to exploit abstract, invariant features from input data, has been proved to have the ability to acquire excellent results. This new classification framework, implemented at a tropical Dry Forest site in Costa Rica, provided accurate estimations of the relative coverage of dead trees, liana-infested trees, non-liana-infested trees, and non-forests. The approach opens the door to start exploring linkages between a booming UAVS industry and machine learning/Deep learning classifiers.

    更新日期:2018-07-12
  • Histogram-based spatio-temporal feature classification of vegetation indices time-series for crop mapping
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-05
    Saeid Niazmardi, Saeid Homayouni, Abdolreza Safari, Heather McNairn, Jiali Shang, Keith Beckett

    Classification of time-series of vegetation indices (VIs) can be a reliable strategy for identifying and monitoring different crop types. Recently, with the advent of new sensors, the time-series data with high spatial and temporal resolutions have become widely available and used for constructing various VIs time-series. These high-resolution time-series, in addition to temporal information about the crops’ phenology, contain valuable information about the spatial patterns of croplands. This information can be used to increase the performance of crop classification. In order to properly extract both spatial and temporal information from the time-series of VIs, we proposed the concept of histogram-based spatio-temporal (HST) features. These features represent each pixel in a time-series by the histogram of its spatio-temporal neighborhood. The HST features, like any other histogram-based features, are characterized by high dimensionality and sparseness. Consequently, the common classification algorithms cannot be employed for their classification. To address this issue, we presented Support Vector Machines (SVM) using an intersection kernel, which is specifically proposed for classification of histogram-based features. Time-series of three different vegetation indices, namely, Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Red Edge Normalized Difference Vegetation Index (NDVIRE) were considered to evaluate the performance of the HST features. The results of experimental tests showed that the HST features by yielding the overall accuracy of 88.31%, 87.27% and 84.36% for NDVIRE, NDVI, and SAVI respectively are much more informative than other textural features used for comparison. Moreover, we provided a detailed analysis of the performance of the HST features concerning the size of the spatio-temporal neighborhood and the number of histogram’s bins.

    更新日期:2018-07-12
  • Locating emergent trees in a tropical rainforest using data from an Unmanned Aerial Vehicle (UAV)
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-06
    Cici Alexander, Amanda H. Korstjens, Emma Hankinson, Graham Usher, Nathan Harrison, Matthew G. Nowak, Abdullah Abdullah, Serge A. Wich, Ross A. Hill

    Emergent trees, which are taller than surrounding trees with exposed crowns, provide crucial services to several rainforest species especially to endangered primates such as gibbons and siamangs (Hylobatidae). Hylobatids show a preference for emergent trees as sleeping sites and for vocal displays, however, they are under threat from both habitat modifications and the impacts of climate change. Traditional plot-based ground surveys have limitations in detecting and mapping emergent trees across a landscape, especially in dense tropical forests. In this study, a method is developed to detect emergent trees in a tropical rainforest in Sumatra, Indonesia, using a photogrammetric point cloud derived from RGB images collected using an Unmanned Aerial Vehicle (UAV). If a treetop, identified as a local maximum in a Digital Surface Model generated from the point cloud, was higher than the surrounding treetops (Trees_EM), and its crown was exposed above its neighbours (Trees_SL; assessed using slope and circularity measures), it was identified as an emergent tree, which might therefore be selected preferentially as a sleeping tree by hylobatids. A total of 54 out of 63 trees were classified as emergent by the developed algorithm and in the field. The algorithm is based on relative height rather than canopy height (due to a lack of terrain data in photogrammetric point clouds in a rainforest environment), which makes it equally applicable to photogrammetric and airborne laser scanning point cloud data.

    更新日期:2018-07-12
  • Combined use of agro-climatic and very high-resolution remote sensing information for crop monitoring
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-06
    R. Ballesteros, J.F. Ortega, D. Hernandez, A. del Campo, M.A. Moreno

    Accurate and real-time yield forecasting is one of the main pillars for decision making in farming and thus for farmers’ profitability. Biomass has been traditionally predicted by multi- and hyperspectral vegetation indices from low- and medium-resolution platforms. This research work aimed to assess the accuracy of the combined use of agro-climatic information and very high-resolution products obtained with RGB cameras mounted on unmanned aerial vehicles (UAVs) for biomass predictions in maize (Zea mays L.). Two agro-climatic predictors, reference evapotranspiration (ETo) and growing degree days (GDDs), and twelve vegetation indices (VIs) derived from RGB bands were calculated for the entire growing cycle. The root mean squared error (RMSE) of the model that considers only GDD to estimate total dry biomass (TDB) was 692.7 g m−2, which was reduced to 509.3 g m−2 when introducing as predictor variables the VARI and GLI vegetation indices. Difficulties in the radiometric calibration of consumer grade RGB cameras together with sources of error such as the bidirectional reflectance distribution function and the blending algorithms in the photogrammetry processing could decrease the applicability of the obtained relationship and should be further evaluated. This study illustrated the advantage of the combined use of agro-climatic predictors (GDD) and green-based VIs derived from RGB consumer grade cameras for biomass predictions.

    更新日期:2018-07-12
  • Identification and classification of mineralogical associations by VNIR-SWIR spectroscopy in the Tajo basin (Spain)
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-06
    Javier García-Rivas, Mercedes Suárez, Emilia García-Romero, Eduardo García-Meléndez

    41 soil samples were collected at the Tajo Basin (Spain), in an area where Mg-rich clays are benefitted, whit the aim of studying their spectral response in the Visible, Near Infrared (VNIR) – Short Wave Infrared (SWIR) range (350–2500 nm) in terms of mineralogical composition and exploring the possibility of using these data as the basis of a geological mapping through hyperspectral imaging in this wavenumber interval in future research. The samples, belonging to nine different stratigraphic units, were characterized by X-Ray diffraction and VNIR – SWIR laboratory reflectance spectroscopy. The mineralogical associations are formed by complex mixtures of carbonates, gypsum, quartz, feldspars, illite, and smectites in variable proportions depending on the stratigraphic unit. The samples were classified into different groups and subgroups according to their spectral response. The resulting groups allow to extrapolate certain type-spectra to different mineralogical associations corresponding to the stratigraphic units sampled within the area of study. This work is of upmost importance for future works through remote-sensing techniques using VNIR – SWIR imaging of the area. The classification of the samples in different groups, according to their spectral response, and their attribution to the different stratigraphic units sampled, according to their mineralogical content, could help improve the geological mapping of the area of study as well as detecting deposits of Mg-rich clays of economic interest.

    更新日期:2018-07-12
  • Updating authoritative spatial data from timely sources: A multiple representation approach
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-05
    Xiang Zhang, Weijun Yin, Min Yang, Tinghua Ai, Jantien Stoter

    Integrating updates from timely sources such as volunteered geographic information (VGI) into the spatial data maintained at official agencies is becoming a more demanding requirement but presents many challenges. This paper proposes an approach to addressing the technical challenge of propagating updates from timely sources (e.g. OpenStreetMap) to spatial data maintained at separate map scales. The main idea is to establish a multiple representation database (MRDB) for datasets at different scales and time to facilitate incremental update, where linkages between corresponding objects at different datasets are made explicit. First, two ways in which the timely sources can be integrated into official data for incremental update are discussed. To derive the linkages between different datasets, a data matching procedure based on computer vision is presented and fine-tuned to match data in different scale ranges. Furthermore, the generalization history used to produce smaller scale data from the larger ones in official data is inferred based on the linkages, and is then used to guide the update propagation. Finally, a framework for incremental generalization in MRDBs is proposed, where crucial issues like strategies for update propagation, cartographic generalization, and the so-called ‘chain reaction’ are addressed. The framework is implemented as a fully automated process where operators like simplification, enlargement, compression, displacement and typification are incorporated into the incremental update process. By testing the framework against real world data sets (i.e. OpenStreetMap and official data at 1:10k, 1:50k and 1:100k), we show that the updates are integrated consistently into existing data in terms of spatial relations and cartographic quality. Our work suggests that making use of timely sources by official mapping agencies and companies in a continuous or event-driven data update is technically feasible, with further improvement and extensions discussed.

    更新日期:2018-07-12
  • Surface soil moisture retrievals over partially vegetated areas from the synergy of Sentinel-1 and Landsat 8 data using a modified water-cloud model
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-06
    Yansong Bao, Libin Lin, Shanyu Wu, Khidir Abdalla Kwal Deng, George P. Petropoulos

    In this study, is presented a new methodology for retrieving surface soil moisture (SSM) under conditions of partial vegetation cover based on the synergy between Sentinel-1 Synthetic Aperture Radar (SAR) and Landsat Operational Land Image (OLI) data. To remove the effect of vegetation on SSM retrieval, the Landsat OLI spectral index is applied to build a model for the vegetation water content estimation. The model is substituted into the original water-cloud model, and thus a modified water-cloud model with a spectral index is built. Additionally, an SSM estimation model is developed based on the modified water-cloud model. The technique was tested at two experimental sites in the UK and Spain on which reference data of SSM are acquired operationally by ground observational networks. In overall, the key findings of our study were: (1) For a vegetation-covered surface, the normalized difference water index (NDWI) obtained from the 1.57–1.65 μm band reflectance data was the most suitable for removing the effects of vegetation cover on soil water content estimation; (2) Compared to the Sentinel-1 VH polarization, the backscattering coefficient at VV polarization was more suitable for soil moisture retrieval and obtained a higher accuracy; (3) The developed model could be used to retrieve SSM under vegetation cover with a high accuracy that indicates the correlation coefficient (R) between the estimated and measured soil moisture was 0.911 and that the root mean square error (RMSE) was 0.053 cm3/cm3; (4) The model can be used to retrieve regional SSM with a high spatial and temporal resolution. Our methodology for deriving SSM offers a number of advantages for many practical applications and research alike and its use by the wider community remains to be seen.

    更新日期:2018-07-12
  • Designing a field sampling plan for landscape-pest ecological studies using VHR optical imagery
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-05
    V. Soti, C. Lelong, F-R. Goebel, T. Brévault

    The objective of this study was to develop an easily replicable sampling methodology using very high spatial resolution (VHSR) optical imagery to study the effect of landscape composition on crop pest incidence and biological control. The methodology was developed for the millet head miner (MHM), Heliocheilus albipunctella (de Joannis) (Lepidoptera: Noctuidae), a key pest of millet in Senegal (West Africa). The sampling plan was developed according to two main hypotheses: (i) pest incidence increases with millet abundance in the landscape, and (ii) biological control increases with the abundance of semi-natural habitats in the landscape. VHSR satellite imagery (<1 m) provided from a Pléiades sensor was used to map and to quantify the landscape elements. Covering a square region of 20 × 20 km, a hierarchical, broad-scale land cover map focusing on crop (millet and peanut crops) and tree (tree vegetation) categories was produced and validated with ground truth data. Then, the landscape variables (tree density index and millet crop density index) were calculated based on a regular grid of 100 ha for each cell size covering the study area; the variables were then split into three density classes (low-medium-high) representative of the full landscape heterogeneity and combined into nine landscape patterns. Finally, according to sampling capacity, track accessibility, and statistical constraints, 45 field sites, including five replicates for each landscape pattern, were validated and selected for pest monitoring.

    更新日期:2018-07-12
  • Assimilating multi-source remotely sensed data into a light use efficiency model for net primary productivity estimation
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-05
    Yuchao Yan, Xiaoping Liu, Jinpei Ou, Xia Li, Youyue Wen

    High spatiotemporal resolution satellite data are necessary for the retrieval of vegetation indexes, such as Normalized Difference Vegetation Index (NDVI), to be assimilated into the Carnegie-Ames-Stanford Approach (CASA) model for net primary productivity (NPP) estimation, especially in the growing season. However, current remotely sensed data cannot accurately monitor vegetation changes at high spatiotemporal resolution. To consider both temporal and spatial information, spatiotemporal fusion models have been developed to obtain the temporal information from high temporal resolution data (e.g., MODIS) together with the spatial information from high spatial resolution data (e.g., Landsat). In this paper, synthetic NDVI images with the spatial resolution of Landsat data and the temporal resolution of MODIS data were first produced using spatiotemporal fusion models. Next, phenological features were extracted from synthetic NDVI time series data to improve land cover classification accuracy. Finally, we evaluated the approach of assimilating the synthetic NDVI and land cover classification map into the CASA model for synthetic NPP estimation. The results revealed that the accuracy of the synthetic NPP was better than NPP estimation from non-fusion NDVI data, and improving the land cover classification accuracy could improve the accuracy of the synthetic NPP estimation. Furthermore, the monthly synthetic NPP showed a significant exponential relationship with the temperature, rainfall, and solar radiation of the current and previous month.

    更新日期:2018-07-12
  • Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-02
    Patricio Martínez-Carricondo, Francisco Agüera-Vega, Fernando Carvajal-Ramírez, Francisco-Javier Mesas-Carrascosa, Alfonso García-Ferrer, Fernando-Juan Pérez-Porras

    Civil engineering uses digital elevation models (DEMs) and orthophotos as basic material to be able to design and execute any project. UAV photogrammetry has made it possible to obtain this type of information in an economic and practical way. However, it is necessary to know the accuracy of the data and that it is within the admissible limits. There are many factors that affect the accuracy of products resulting from UAV photogrammetry. Of all of these, the effect of the number of ground control points (GCPs) and their distribution in the study area are especially significant. Different distributions of GCPs have been studied to try to optimize the products obtained by UAV photogrammetry. Of all the distributions tested, the best results were obtained with edge distribution and stratified distribution. Therefore, it is necessary to place GCPs around the edge of the study area to minimize planimetry errors. In addition, it is advisable to create a stratified distribution inside the study area with a density of around 0.5–1 GCP × ha−1 to minimize altimetry errors. The combination of these two distributions minimizes the total error obtained.

    更新日期:2018-07-12
  • Mapping threats to agriculture in East Africa: Performance of MODIS derived LST for frost identification in Kenya’s tea plantations
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-06-19
    Susan M. Kotikot, Africa Flores, Robert E. Griffin, Absae Sedah, James Nyaga, Robinson Mugo, Ashutosh Limaye, Daniel E. Irwin

    Frost is a major threat to crop productivity in the Kenyan highlands. With agriculture being central to the Kenyan economy, every effort needs to be taken to alleviate losses especially on high value crops like tea, the leading foreign exchange earner. Current frost mapping efforts by SERVIR, a joint initiative between National Aeronautics and Space Administration (NASA) and the U.S. Agency for International Development (USAID), and its hub institution in Eastern and Southern Africa, the Regional Center for Mapping of Resources for Development (RCMRD), utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) derived Land Surface Temperature (LST) to probabilistically map areas that have been affected by frost. In this paper, we assessed the accuracy of these frost maps by testing the performance of MYD11A1 MODIS product in indicating areas affected by frost. MODIS derived LST values corresponding to frost and no frost observation locations and dates were reclassified according to 6 predetermined categories representing frost severity levels. The overall accuracy of each threshold category as LST cutoff separating frost and no frost affected areas was determined. An overall performance measure was then estimated using a Receiver Operating Characteristics curve (ROC). Overall accuracies of 67.3%–71.9% among the thresholds were obtained. An area under the ROC curve of 0.69 was obtained, indicating a poor performance of MODIS LST to distinguish frost from no frost areas. This shows that although MODIS derived LST can be used to identify frost-affected areas, it is not on its own sufficient in discriminating these areas with high levels of accuracy. Revision of temperature thresholds is recommended, in addition to improved characterization of frost occurrence in the region to include other factors that may be affecting frost occurrence. These results stand to better prepare the agricultural sector for damaging weather-related events.

    更新日期:2018-07-12
  • Urban landscape extraction and analysis in the mega-city of China’s coastal regions using high-resolution satellite imagery: A case of Shanghai, China
    Int. J. Appl. Earth Obs. Geoinf. (IF 4.003) Pub Date : 2018-04-12
    Zhi Li, Chenghu Zhou, Xiaomei Yang, Xi Chen, Fan Meng, Chen Lu, Tao Pan, Wenjuan Qi

    The analysis of urban land-cover classes and their spatial patterns are important problems in urban ecology, especially in ecologically fragile coastal areas. It is of great significance to those who optimize urban functional zones and are involved in urban planning management and sustainable development. High-resolution imagery has become an instrumental data source for detailed urban spatial pattern analysis, due to the complex structure of urban land covers made it difficult to achieve accurate and detailed information for urban landscape using medium or low-resolution images. In this study, based on China’s GaoFen-1 (GF-1) high spatial resolution remote sensing images and a reference dataset, an information extraction technology based on a combination of pixel-, object-, and knowledge- based methods is developed to classify the land covers in urban built-up areas (BUAs) of Shanghai, China. The mapping and landscape pattern analysis of urban BUAs in Shanghai has been completed based on the results of land cover classification. The experimental results show that the overall accuracy and Kappa coefficients of the land-cover classification in Shanghai urban BUAs are 83.7% and 0.71, respectively, which provide effective and reliable data for spatial mapping and landscape pattern analysis. Through the landscape analysis of the classification results of land cover in Shanghai, the results demonstrated that not only is there a high degree of exploitation and utilization of land resources in Shanghai but also that the spatial distribution pattern of land cover types is reasonable, which indicates that its development is sustainable.

    更新日期:2018-07-12
  • Sensitivity of Radiative‐Convection Equilibrium to Divergence Damping in GFDL‐FV3‐Based Cloud‐Resolving Model Simulations
    J. Adv. Model. Earth Syst. (IF 3.97) Pub Date : 2018-05-05
    Usama M. Anber; Nadir Jeevanjee; Lucas M. Harris; Isaac M. Held

    Using a nonhydrostatic model based on a version of Geophysical Fluid Dynamics Laboratory's FV3 dynamical core at a cloud‐resolving resolution in radiative‐convective equilibrium (RCE) configuration, the sensitivity of the mean RCE climate to the magnitude and scale‐selectivity of the divergence damping is explored. Divergence damping is used to reduce small‐scale noise in more realistic configurations of this model. This sensitivity is tied to the strength (and width) of the convective updrafts, which decreases (increases) with increased damping and acts to organize the convection, dramatically drying out the troposphere and increasing the outgoing longwave radiation. Increased damping also results in a much‐broadened precipitation probability distribution and larger extreme values, as well as reduction in cloud fraction, which correspondingly decreases the magnitude of shortwave and longwave cloud radiative effects. Solutions exhibit a monotonic dependence on the strength of the damping and asymptotically converge to the inviscid limit. While the potential dependence of RCE simulations on resolution and microphysical assumptions are generally appreciated, these results highlight the potential significance of the choice of subgrid numerical diffusion in the dynamical core.

    更新日期:2018-07-12
  • Matrix‐based sensitivity assessment of soil organic carbon storage: A case study from the ORCHIDEE‐MICT model
    J. Adv. Model. Earth Syst. (IF 3.97) Pub Date : 2018-07-10
    Yuanyuan Huang; Dan Zhu; Philippe Ciais; Bertrand Guenet; Ye Huang; Daniel S. Goll; Matthieu Guimberteau; Albert Jornet‐Puig; Xingjie Lu; Yiqi Luo

    Modeling of global soil organic carbon (SOC) is accompanied by large uncertainties. The heavy computational requirement limits our flexibility in disentangling uncertainty sources especially in high latitudes. We build a structured sensitivity analyzing framework through reorganizing the ORCHIDEE‐MICT model with vertically discretized SOC into one matrix equation, which brings flexibility in comprehensive sensitivity assessment. Through Sobol's method enabled by the matrix, we systematically rank 34 relevant parameters according to variance explained by each parameter and find a strong control of carbon input and turnover time on long‐term SOC storages. From further analyses for each soil layer and regional assessment, we find that the active layer depth plays a critical role in the vertical distribution of SOC and SOC equilibrium stocks in northern high latitudes (>50°N). However, the impact of active layer depth on SOC is highly interactive and nonlinear, varying across soil layers and grid cells. The stronger impact of active layer depth on SOC comes from regions with shallow active layer depth (e.g., the northernmost part of America, Asia and some Greenland regions). The model is sensitive to the parameter that controls vertical mixing (cryoturbation rate) but only when the vertical carbon input from vegetation is limited since the effect of vertical mixing is relatively small. And the current model structure may still lack mechanisms that effectively bury non‐recalcitrant SOC. We envision a future with more comprehensive model inter‐comparisons and assessments with an ensemble of land carbon models adopting the matrix‐based sensitivity framework.

    更新日期:2018-07-12
  • Description and Evaluation of the MIT Earth System Model (MESM)
    J. Adv. Model. Earth Syst. (IF 3.97) Pub Date : 2018-07-10
    Andrei Sokolov; David Kicklighter; Adam Schlosser; Chien Wang; Erwan Monier; Benjamin Brown‐Steiner; Ron Prinn; Chris Forest; Xiang Gao; Alex Libardoni; Sebastian Eastham

    The MIT Integrated Global System Model (IGSM) is designed for analyzing the global environmental changes that may result from anthropogenic causes, quantifying the uncertainties associated with the projected changes, and assessing the costs and environmental effectiveness of proposed policies to mitigate climate risk. The IGSM consists of the MIT Earth System Model of intermediate complexity (MESM) and the Economic Projections and Policy Analysis (EPPA) model. This paper documents the current version of the MESM, which includes a 2‐dimensional (zonally averaged) atmospheric model with interactive chemistry coupled to the zonally averaged version of Global Land System model and an anomaly‐diffusing ocean model.

    更新日期:2018-07-12
  • Development and evaluation of an explicit treatment of aerosol processes at cloud scale within a multi‐scale modeling framework (MMF)
    J. Adv. Model. Earth Syst. (IF 3.97) Pub Date : 2018-07-10
    Guangxing Lin; Steven J. Ghan; Minghuai Wang; Po‐Lun Ma; Richard C. Easter; Mikhail Ovchinnikov; Jiwen Fan; Kai Zhang; Hailong Wang; Duli Chand; Yun Qian

    Modeling the aerosol lifecycle in traditional global climate models (GCM) is challenging for a variety of reasons, not the least of which is the coarse grid. The multi‐scale modeling framework (MMF), in which a cloud resolving model replaces conventional parameterizations of cloud processes within each GCM grid column, provides a promising framework to address this challenge. Here, we develop a new version of MMF that for the first time treats aerosol processes at cloud scale to improve the aerosol‐cloud interaction representation in the model. We demonstrate that the model with the explicit aerosol treatments shows significant improvements of many aspects of the simulated aerosols compared to the previous version of MMF with aerosols parameterized at the GCM grid scale. The explicit aerosol treatments produce a significant increase of the column burdens of black carbon (BC), primary organic aerosol (POA), and sulfate by up to 40% in many remote regions, a decrease of the sea‐salt aerosol burdens by 40% in remote regions. These differences are caused by the differences in aerosol convective transport and wet removal between these two models. The new model also shows reduced bias of BC surface concentration in North America and BC vertical profiles in the high‐latitudes. However, the biased‐high BC concentrations in the upper troposphere over the remote Pacific regions remain, requiring further improvements on other process representations (for example, secondary activation neglected in the model).

    更新日期:2018-07-12
  • Roles of cloud microphysics on cloud responses to sea surface temperatures in radiative–convective equilibrium experiments using a high‐resolution global nonhydrostatic model
    J. Adv. Model. Earth Syst. (IF 3.97) Pub Date : 2018-07-10
    Tomoki Ohno; Masaki Satoh

    The high‐cloud amount responses to sea surface temperature (SST) changes were investigated based on simulations with radiative–convective equilibrium (RCE) configuration using a high‐resolution nonhydrostatic global circulation model (NICAM). The RCE was calculated using a non‐rotating sphere with Earth‐radius and a 14‐km horizontal mesh with uniform SSTs of 300 and 304 K. Two types of cloud microphysics schemes (single‐ and double‐moment bulk schemes) and two types of vertical layer configurations (38 and 78 layers) were tested. The radiatively‐driven circulation weakens with increasing SST in all simulation pairs due to the increase in the static stability, as suggested in previous studies. In contrast, the high‐cloud amount increases in three simulation pairs and decreases in one pair. These indicate that the weakening of radiatively‐driven circulation with increasing SST does not always accompany the high‐cloud amount decrease. We determined that the tropopause layer was wet (dry) in simulations that showed positive (negative) high‐cloud cover responses. The radiatively‐driven upward moisture transport just below the wet tropopause layer increases with increasing SST in the simulation pairs with positive high‐cloud amount responses, and this causes the supply of ice condensate to the lower layer through the sedimentation process, while this feedback was not observed in the simulation pair with the negative response. These indicate that the high‐cloud cover response depends on the occurrence of the feedback and there is a feedback threshold among the variety of simulations. This speculates whether the feedback mechanism is effective has the large impact on high‐cloud responses in the real atmosphere.

    更新日期:2018-07-12
  • Understanding global model systematic shortwave radiation errors in subtropical marine boundary layer cloud regimes
    J. Adv. Model. Earth Syst. (IF 3.97) Pub Date : 2018-07-10
    Maike Ahlgrimm; Richard M. Forbes; Robin J. Hogan; Irina Sandu

    Global numerical weather prediction and climate models are subject to long‐standing systematic shortwave radiation errors due to deficiencies in the representation of boundary layer clouds over the ocean. In the subtropics, clouds are typically too reflective in the cumulus regime and not reflective enough in the stratocumulus regime. Potential sources of error include cloud cover, liquid water path, effective radius and subgrid heterogeneity, but diagnosing the absolute contributions of each to the radiation bias is hampered by uncertainties and sometimes contradictory information from different observational products. This paper draws on a set of ship‐based observations of boundary layer clouds obtained during the ARM MAGIC campaign along a north‐east Pacific Ocean transect, crossing both stratocumulus and shallow cumulus cloud regimes. The surface‐based observations of cloud properties are compared with various satellite products, taking account of the diurnal cycle, to provide an improved quantitative assessment of the deficiencies in the ECMWF global numerical weather prediction model. A series of offline radiation calculations are then performed to assess the impact on the shortwave radiation bias of “correcting” each of the model's deficiencies in cloud characteristics along the transect. A reduction in the bias is achieved by improving the agreement between modelled and observed in‐cloud LWP frequency distributions. In the cumulus regime, this is accomplished primarily by reducing the all‐sky water path, while for the stratocumulus regime, an underestimate of cloud cover and liquid water and an overestimate in effective radius and subgrid heterogeneity all contribute to a lack of reflected shortwave radiation.

    更新日期:2018-07-12
Some contents have been Reproduced with permission of the American Chemical Society.
Some contents have been Reproduced by permission of The Royal Society of Chemistry.
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