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Air pollution trends measured from Terra: CO and AOD over industrial, fire-prone, and background regions Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-26 Rebecca R. Buchholz; Helen M. Worden; Mijeong Park; Gene Francis; Merritt N. Deeter; David P. Edwards; Louisa K. Emmons; Benjamin Gaubert; John Gille; Sara Martínez-Alonso; Wenfu Tang; Rajesh Kumar; James R. Drummond; Cathy Clerbaux; Maya George; Pierre-François Coheur; Daniel Hurtmans; Kevin W. Bowman; Susan S. Kulawik
Following past studies to quantify decadal trends in global carbon monoxide (CO) using satellite observations, we update estimates and find a CO trend in column amounts of about −0.50 % per year between 2002 to 2018, which is a deceleration compared to analyses performed on shorter records that found −1 % per year. Aerosols are co-emitted with CO from both fires and anthropogenic sources but with a
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Assessment of near-shore currents from CryoSat-2 satellite in the Gulf of Cádiz using HF radar-derived current observations Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-25 R. Mulero-Martínez; J. Gómez-Enri; R. Mañanes; M. Bruno
This study evaluated the possibility of studying mesoscale surface circulation in coastal areas, as is the Gulf of Cádiz, Spain, using high-resolution altimetry data (20-Hz of posting rate) along with the use of wind and bottom friction ageostrophic corrections. Absolute cross-track surface zonal current velocities, derived from filtered along-track CryoSat-2 SIRAL-SARM Absolute Dynamic Topography
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Accurate and fast simulation of remote sensing images at top of atmosphere with DART-Lux Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-25 Yingjie Wang; Jean-Philippe Gastellu-Etchegorry
DART model is one of the most comprehensive and accurate radiative transfer (RT) models to simulate remotely sensed signals in the Earth-atmosphere system. Its standard RT modelling mode, called DART-FT, relies on the discrete ordinates method. Its recently developed Monte Carlo mode using an unbiased bidirectional path tracing method, called DART-Lux, increases hundredfold DART efficiency to simulate
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Change detection using deep learning approach with object-based image analysis Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-23 Tao Liu; Lexie Yang; Dalton Lunga
In their applications, both deep learning techniques and object-based image analysis (OBIA) have shown better performance separately than conventional methods on change detection tasks. However, efforts to investigate the effect of combining these two techniques for advancing change detection techniques are unexplored in current literature. This study proposes a novel change detection method implementing
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Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization-based approach Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-23 Ting Yun; Kang Jiang; Guangchao Li; Markus P. Eichhorn; Jiangchuan Fan; Fangzhou Liu; Bangqian Chen; Feng An; Lin Cao
Accurate segmentation of individual tree crowns (ITCs) from airborne light detection and ranging (LiDAR) data remains a challenge for forest inventories. Although many ITC segmentation methods have been developed to derive tree crown information from airborne LiDAR data, these algorithms contain uncertainty in processing false treetops because of foliage clumps and lateral branches, overlapping canopies
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Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-21 Zifeng Wang; Junguo Liu; Jinbao Li; Ying Meng; Yadu Pokhrel; Hongsheng Zhang
Extraction of drainage networks is an important element of river flow routing in hydrology and large-scale estimates of river behaviors in Earth sciences. Emerging studies with a focus on greenhouse gases reveal that small rivers can contribute to more than half of the global carbon emissions from inland waters (including lakes and wetlands). However, large-scale extraction of drainage networks is
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Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-22 Ahmed Samir Abowarda; Liangliang Bai; Caijin Zhang; Di Long; Xueying Li; Qi Huang; Zhangli Sun
Soil moisture has a considerable impact on the hydrological cycle, runoff generation, drought development, and water resources management. Soil moisture products provided by passive microwave remote sensing possess coarse spatial resolutions ranging from 25 to 50 km, unable to reflect large spatial heterogeneity in soil moisture caused by complex interactions among meteorological forcing, land cover
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Evaluating the temporal accuracy of grassland to cropland change detection using multitemporal image analysis Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-21 Jacob Mardian; Aaron Berg; Bahram Daneshfar
Grasslands are valuable carbon sinks in the effort to mitigate climate change. However, they are not well protected and are consequently being replaced by agricultural systems worldwide. Current monitoring efforts using remote sensing and ground-based methods are insufficient, and accordingly the mapping of grassland to cropland conversions must be improved to better document these changes in the Canadian
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River body extraction from sentinel-2A/B MSI images based on an adaptive multi-scale region growth method Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-21 Song Jin; Yongxue Liu; Sergio Fagherazzi; Huan Mi; Gang Qiao; Wenxuan Xu; Chao Sun; Yongchao Liu; Bingxue Zhao; Cédric G. Fichot
River networks are important water carriers that provide a multitude of ecosystem services, including freshwater for agriculture, drinking water for cities, and recreational activities. Accurate mapping of river networks from remote-sensing images is important for the study of these systems. Unfortunately, the delineation of river networks is challenging due to the meandering nature of river channels
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Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrieval in heterogeneous ecological systems after fire Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-22 José Manuel Fernández-Guisuraga; Jochem Verrelst; Leonor Calvo; Susana Suárez-Seoane
In forest landscapes affected by fire, the estimation of fractional vegetation cover (FVC) from remote sensing data using radiative transfer models (RTMs) enables to evaluate the ecological impact of such disturbance across plant communities at different spatio-temporal scales. Even though, when landscapes are highly heterogeneous, the fine-scale ground spatial variation might not be properly captured
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Multi-angular reflectance spectra of small single trees Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-21 Petri R. Forsström; Aarne Hovi; Giulia Ghielmetti; Michael E. Schaepman; Miina Rautiainen
Understanding the reflectance anisotropy of forests and the underlying scattering mechanisms is needed to improve the accuracy of retrievals of fundamental forest characteristics from optical remote sensing data. In this paper, we developed a laboratory measurement set-up for a large goniometer (LAGOS) and measured multi-angular spectra (350–2500 nm) of 18 small trees, composed of three common European
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Forest fire fuel through the lens of remote sensing: Review of approaches, challenges and future directions in the remote sensing of biotic determinants of fire behaviour Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-21 Matthew G. Gale; Geoffrey J. Cary; Albert I.J.M. Van Dijk; Marta Yebra
Forested environments are subject to large and high intensity unplanned fire events, owing to, among other factors, the high quantity and complex structure of fuel in these environments. Compiling accurate and spatially comprehensive fuel information is necessary to inform various aspects of land management in forested environments. Remote sensing may offer distinct advantages for this in comparison
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Quality-control tests for OC4, OC5 and NIR-red satellite chlorophyll-a algorithms applied to coastal waters Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-22 H. Lavigne; D. Van der Zande; K. Ruddick; J.F. Cardoso Dos Santos; F. Gohin; V. Brotas; S. Kratzer
Reliable satellite estimates of chlorophyll-a concentration (Chl-a) are needed in coastal waters for applications such as eutrophication monitoring. However, because of the optical complexity of coastal waters, retrieving accurate Chl-a is still challenging. Many algorithms exist and give quite different performance for different optical conditions but there is no clear definition of the limits of
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Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS) Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-20 Langning Huo; Henrik Jan Persson; Eva Lindberg
The European spruce bark beetle (Ips typographus [L.]) is one of the most damaging pest insects of European spruce forests. A crucial measure in pest control is the removal of infested trees before the beetles leave the bark, which generally happens before the end of June. However, stressed tree crowns do not show any significant color changes in the visible spectrum at this early-stage of infestation
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Hyperspectral imagery to monitor crop nutrient status within and across growing seasons Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-20 Nanfeng Liu; Philip A. Townsend; Mack R. Naber; Paul C. Bethke; William B. Hills; Yi Wang
Imaging spectroscopy provides the opportunity to monitor nutrient status of vegetation. In crops, prior studies have generally been limited in scope, either to a small wavelength range (e.g., 400–1300 nm), a small number of crop cultivars, a single growth stage or single growing season. Methods that are not time- or site-specific are needed to use imaging spectroscopy for routine monitoring of crop
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Assessment of approaches for monitoring forest structure dynamics using bi-temporal digital aerial photogrammetry point clouds Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-20 Xiaoyao Fu; Zhengnan Zhang; Lin Cao; Nicholas C. Coops; Tristan R.H. Goodbody; Hao Liu; Xin Shen; Xiangqian Wu
Assessing changes in forest structure over time is crucial for monitoring forest resources, supporting sustainable forest management practices, and providing key insights into changes in the terrestrial carbon cycle. Recent research interest and rapid growth of unmanned aerial vehicle (UAV)-based digital aerial photogrammetry (DAP) technology principally due to its low cost and timeliness, is providing
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A D-vine copula quantile regression approach for soil moisture retrieval from dual polarimetric SAR Sentinel-1 over vegetated terrains Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-18 Hoang Hai Nguyen; Seongkeun Cho; Jaehwan Jeong; Minha Choi
Soil moisture retrieval from Synthetic Aperture Radar (SAR) over vegetated terrains requires an isolation of soil and canopy signals from observed backscatter (σ°). This study develops a probabilistic soil moisture retrieval method from dual polarimetric C-band SAR Sentinel-1 (S-1) with uncertainty quantification at distinct vegetation covers (VCs). Both σVV° and σVH° were used to represent ground
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Estimating three-dimensional coseismic deformations with the SM-VCE method based on heterogeneous SAR observations: Selection of homogeneous points and analysis of observation combinations Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-18 Jun Hu; Jihong Liu; Zhiwei Li; Jianjun Zhu; Lixin Wu; Qian Sun; Wenqing Wu
The previously proposed Strain Model and Variance Component Estimation (SM-VCE) method estimates three-dimensional (3-D) deformations based on heterogeneous synthetic aperture radar (SAR) observations from three or more distinct observing geometries. This method establishes an observation function by exploiting the spatial correlation of adjacent point deformations based on a geo-kinematic model (i
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Using SMAP Level-4 soil moisture to constrain MOD16 evapotranspiration over the contiguous USA Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-17 Colin Brust; John S. Kimball; Marco P. Maneta; Kelsey Jencso; Mingzhu He; Rolf H. Reichle
Evapotranspiration (ET) is a key hydrologic variable linking the Earth's water, carbon and energy cycles. At large spatial scales, remote sensing-based (RS) models are often used to quantify ET. Despite the large number of RS ET models available, few include soil moisture as a key environmental input, which can degrade model accuracy and utility. Here, we use model assimilation enhanced soil moisture
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Rapid, robust, and automated mapping of tidal flats in China using time series Sentinel-2 images and Google Earth Engine Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-16 Mingming Jia; Zongming Wang; Dehua Mao; Chunying Ren; Chao Wang; Yeqiao Wang
Tidal flats are threatened by tidal reclamation and climatic changes around the world. Particular challenges exist in China where tidal flats are changing rapidly along with accelerated economic development in coastal regions. The unique and important ecosystem functions and services that tidal flats provide in coastal regions warrant the necessary of mapping such a particular land cover type in high
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Regional winter wheat yield estimation based on the WOFOST model and a novel VW-4DEnSRF assimilation algorithm Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-16 Shangrong Wu; Peng Yang; Jianqiang Ren; Zhongxin Chen; He Li
To further improve the accuracy of regional crop yield estimation based on data assimilation, a novel EnSRF assimilation algorithm based on a variable time window and four-dimensional extension (VW-4DEnSRF) was proposed. In this research, taking Hengshui City of Hebei Province as the study area and winter wheat as the research crop, based on the WOFOST crop model and the proposed VW-4DEnSRF algorithm
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Terrestrial laser scanning intensity captures diurnal variation in leaf water potential Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-14 S. Junttila; T. Hölttä; E. Puttonen; M. Katoh; M. Vastaranta; H. Kaartinen; M. Holopainen; H. Hyyppä
During the past decades, extreme events have become more prevalent and last longer, and as a result drought-induced plant mortality has increased globally. Timely information on plant water dynamics is essential for understanding and anticipating drought-induced plant mortality. Leaf water potential (ΨL), which is usually measured destructively, is the most common metric that has been used for decades
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A machine learning approach to estimating the error in satellite sea surface temperature retrievals Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-13 Chirag Kumar; Guillermo Podestá; Katherine Kilpatrick; Peter Minnett
Global, repeated, and accurate measurements of Sea Surface Temperature (SST) are critical for weather and climate projections. While thermometers on buoys measure SST relatively accurately, only sensors aboard satellites give global and repeated SST measurements necessary for many applications, including climate modeling. For satellite-based thermal infrared sensors, an atmospheric correction converts
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SPLITSnow: A spectral light transport model for snow Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-12 Petri M. Varsa; Gladimir V.G. Baranoski; Bradley W. Kimmel
Snow is a fundamental component of the climate system. It is also an important part of the planet's hydrological cycle. Accordingly, the investigation of its light scattering properties is essential for remote sensing applications employed in the estimation of changes in the current amount of snowpack. These wide-scale environmental changes are key indicators of future climate events affecting global
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Characterization of ice shelf fracture features using ICESat-2 – A case study over the Amery Ice Shelf Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-12 Shujie Wang; Patrick Alexander; Qiusheng Wu; Marco Tedesco; Song Shu
Fractures are important structural features that affect the stress condition and stability of ice shelves. Previous studies have mainly focused on the measurement of fractures in the horizontal dimension. However, the vertical morphology of fractures could also be potentially important in determining their evolution and role in ice shelf stability. In this regard, the dense and high-resolution surface
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Evaluation and blending of ATMS and AMSR2 snow water equivalent retrievals over the conterminous United States Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-05 Yanjun Gan; Yu Zhang; Cezar Kongoli; Christopher Grassotti; Yuqiong Liu; Yong-Keun Lee; Dong-Jun Seo
This study first compares two different passive microwave snow water equivalent (SWE) retrievals, namely the retrieval from the Suomi National Polar-orbiting Partnership (S-NPP) Advanced Technology Microwave Sounder (ATMS) and that from the Global Change Observation Mission – Water (GCOM-W1) Advanced Microwave Scanning Radiometer 2 (AMSR2); it further creates an optimal blending mechanism that merges
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Sentinel-1 based soil freeze/thaw estimation in boreal forest environments Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-05 Juval Cohen; Kimmo Rautiainen; Juha Lemmetyinen; Tuomo Smolander; Juho Vehviläinen; Jouni Pulliainen
A method for the retrieval of soil freeze/thaw (F/T) state in the boreal forest region using SAR is presented in this paper. The method utilizes Sentinel-1 data and is thus suitable for continuous near real-time monitoring. The main challenge with the C-band VV-polarization signal is the sensitivity to vegetation and especially to forest canopies. A relatively simple zeroth-order model is used for
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Landsat-based detection of mast events in white spruce (Picea glauca) forests Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-05 Matthew Garcia; Benjamin Zuckerberg; Jalene M. LaMontagne; Philip A. Townsend
Mast seeding in conifers is characterized by the spatially synchronous and temporally variable production of seed cone crops. Large mast seeding events (known as “mast years”) can be a visually stunning and ecologically important phenomenon, supporting trophic interactions and survival of seed predators as well as forest regeneration. Documenting patterns in mast seeding is generally labor-intensive
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Archetypal temporal dynamics of arid and semi-arid rangelands Remote Sens. Environ. (IF 9.085) Pub Date : 2021-01-03 O. Bruzzone; M.H. Easdale
The way in which temporal dynamics structure ecological systems under the influence of a changing environment has long interested ecologists. Tackling the hierarchical structure of complex temporal patterns is a necessary step towards a more complete description of the fundamental nature of temporal dynamics in ecosystems. In pursuance of this task, remote sensing data provide valuable information
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Evolution of the representation of global vegetation by vegetation continuous fields Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-31 Charlene DiMiceli; John Townshend; Mark Carroll; Robert Sohlberg
Two decades of global annual fractional vegetation cover products have been derived using daily surface reflectance and land surface temperature data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA's Terra satellite. These MODIS Vegetation Continuous Fields (VCF) products are unique and a distinct advance over discrete (ordinal) land cover characterizations. VCF
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Satellite InSAR survey of structurally-controlled land subsidence due to groundwater exploitation in the Aguascalientes Valley, Mexico Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-31 Francesca Cigna; Deodato Tapete
To address increasing water demands in expanding cities, many aquifers in Mexico are overexploited and deplete. The resulting land subsidence often combines with ground faulting/fracturing and damage to infrastructure. This study provides the longest Synthetic Aperture Radar (SAR) survey ever undertaken for the Aguascalientes Valley, aimed to constrain its structurally-controlled subsidence process
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Integration of electron flow partitioning improves estimation of photosynthetic rate under various environmental conditions based on chlorophyll fluorescence Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-30 Mitsutoshi Kitao; Yukio Yasuda; Eiji Kodani; Hisanori Harayama; Yoshio Awaya; Masabumi Komatsu; Kenichi Yazaki; Hiroyuki Tobita; Evgenios Agathokleous
Electron transport rate (ETR), estimated from chlorophyll fluorescence, is a widely-used indicator of photosynthetic activity. However, net photosynthetic CO2 assimilation rate (A) does not linearly correlate with ETR when the fraction of electron partitioning into photosynthesis and photorespiration changes under fluctuating environmental conditions (CO2, light, temperature and soil moisture). Here
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Challenges in the atmospheric characterization for the retrieval of spectrally resolved fluorescence and PRI region dynamics from space Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-26 Neus Sabater; Pekka Kolmonen; Shari Van Wittenberghe; Antti Arola; José Moreno
In the coming years, Earth Observation missions like the FLuorescence EXplorer (FLEX) will acquire the radiance signal from the visible to the near-infrared at a very high spectral resolution, enabling exciting prospects for new insights in satellite-based photosynthetic studies. In this context, the process of de-coupling atmospheric and vegetation-related spectral signatures will become essential
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Impact of channel selection on SST retrievals from passive microwave observations Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-25 Pia Nielsen-Englyst; Jacob L. Høyer; Emy Alerskans; Leif Toudal Pedersen; Craig Donlon
Two retrieval algorithms developed as a part of the European Space Agency Climate Change Initiative (ESA-CCI) project are used to assess the effects of withholding observations from selected frequency channels on the retrieved subskin Sea Surface Temperature (SST) from AQUA's Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) and to evaluate a Copernicus Imaging Microwave Radiometer
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Using satellite remote sensing to improve the prediction of scallop condition in their natural environment: Case study for Georges Bank, Canada Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-25 Xiaohan Liu; Emmanuel Devred; Catherine L. Johnson; Dave Keith; Jessica A. Sameoto
The continuous, synoptical and high spatio-temporal resolution of thermal and visible satellite observations constitute an asset when characterizing and monitoring biogeochemical cycles in the oceans. In particular, they provide a unique insight into the hydrodynamics of the surface ocean and phytoplankton phenology. This information can be combined with in-situ observations of higher trophic levels
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An automated, generalized, deep-learning-based method for delineating the calving fronts of Greenland glaciers from multi-sensor remote sensing imagery Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-24 Enze Zhang; Lin Liu; Lingcao Huang; Ka Shing Ng
In the past two decades, the data volume of remote sensing imagery in the polar regions has increased dramatically. The calving fronts of many Greenland glaciers have been undergoing substantial variations, and a comprehensive front dataset is necessary for better understanding such frontal dynamics. Therefore, there is a need for an automated approach to identifying glaciological features such as
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Practical approaches for normalizing directional solar-induced fluorescence to a standard viewing geometry Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-24 Dalei Hao; Yelu Zeng; Han Qiu; Khelvi Biriukova; Marco Celesti; Mirco Migliavacca; Micol Rossini; Ghassem R. Asrar; Min Chen
Recent advances in remote sensing of solar-induced chlorophyll fluorescence (SIF) have improved the capabilities of monitoring large-scale Gross Primary Productivity (GPP). However, SIF observations are subject to directional effects which can lead to considerable uncertainties in various applications. Practical approaches for normalizing directional SIF observations to nadir viewing, to minimize the
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Active learning regularization increases clear sky retrieval rates for vegetation biophysical variables using Sentinel-2 data Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-22 Najib Djamai; Richard Fernandes
For typical cloud conditions, a clear sky retrieval rate (CSRR) >67% is required to meet the Global Climate Observing System temporal interval requirement of 10 days when mapping canopy biophysical variables (‘variables’). Physically based algorithms suitable for global mapping of variables using multispectral satellite imagery, e.g. the Simplified Level 2 Prototype Processor (SL2P), typically have
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Spatiotemporal estimation of satellite-borne and ground-level NO2 using full residual deep networks Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-22 Lianfa Li; Jiajie Wu
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A new land surface temperature fusion strategy based on cumulative distribution function matching and multiresolution Kalman filtering Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-22 Shuo Xu; Jie Cheng
Fusing high-level passive microwave (PMW) LST and thermal infrared (TIR) LST products is a promising means of generating high-quality, all-weather land surface temperature (LST) data. In this paper, we propose a new fusion strategy for generating high-quality, all-weather LST data based on cumulative distribution function (CDF) matching and multiresolution Kalman filtering (MKF). CDF matching was employed
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Global chlorophyll distribution induced by mesoscale eddies Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-21 Dandan Zhao; Yongsheng Xu; Xiangguang Zhang; Chao Huang
While mesoscale eddies can trap and transport chlorophyll (CHL) within the water columns, satellite measurements can only observe CHL at the sea surface. Here, we estimate the eddy-induced CHL distribution based on satellite observations, Argo float measurements, and global empirical models. The combination of satellite altimeter data and Argo measurements is used to detect eddy boundaries by tracking
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SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-19 Jean-Pierre Wigneron; Xiaojun Li; Frédéric Frappart; Lei Fan; Amen Al-Yaari; Gabrielle De Lannoy; Xiangzhuo Liu; Mengjia Wang; Erwan Le Masson; Christophe Moisy
Passive microwave remote sensing observations at L-band provide key and global information on surface soil moisture and vegetation water content, which are related to the Earth water and carbon cycles. Only two space-borne L-band sensors are currently operating: SMOS, launched end of 2009 and thus providing now a 10-year global data set and SMAP, launched beginning of 2015. This study provides a state-of-the-art
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Spatio-temporal Cokriging method for assimilating and downscaling multi-scale remote sensing data Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-18 Bo Yang; Hongxing Liu; Emily L. Kang; Song Shu; Min Xu; Bin Wu; Richard A. Beck; Kenneth M. Hinkel; Bailang Yu
No single satellite remote sensing system is able to provide the observations on the Earth's surface at both high spatial and high temporal resolution due to the general trade-off between orbit revisit frequency and satellite sensor's spatial resolution. This paper presents a spatio-temporal Cokriging (ST-Cokriging) method for assimilating remote sensing data sets acquired by multiple remote sensing
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Mapping bull kelp canopy in northern California using Landsat to enable long-term monitoring Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-17 Dennis J.I. Finger; Meredith L. McPherson; Henry F. Houskeeper; Raphael M. Kudela
Extending from central California to Alaska, bull kelp (Nereocystis luetkeana) forms seasonal kelp forests that are iconic coastal ecosystems in much of the eastern Pacific. Historical and ongoing field surveys and aerial imagery are used to provide biological data on kelp canopy cover and health, but satellite remote sensing provides the opportunity to generate consistent, long-term datasets over
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An assessment of emission characteristics of Northern Hemisphere cities using spaceborne observations of CO2, CO, and NO2 Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-17 Hayoung Park; Sujong Jeong; Hoonyoung Park; Lev D. Labzovskii; Kevin W. Bowman
Intensified anthropogenic activities and high levels of energy consumption in cities have led to an increase in emissions of CO2 and air pollutants, impacting air quality and calling for better measures to monitor and reduce emissions. This study assesses the emission characteristics of cities in the Northern Hemisphere during two winter seasons from December 2018 to March 2020 using a combination
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Monitoring time-varying terrestrial water storage changes using daily GNSS measurements in Yunnan, southwest China Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-17 Zhongshan Jiang; Ya-Ju Hsu; Linguo Yuan; Dingfa Huang
Global Navigation Satellite System (GNSS) instruments provide a powerful tool to investigate spatiotemporal variations in regional-scale terrestrial water storage based on the solid Earth's elastic response to hydrologic loading signals. Here, we implemented an independent component analysis-based inversion method to investigate water storage changes and hydrometeorological extremes (e.g., heavy precipitation
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Displacement history and potential triggering factors of Baige landslides, China revealed by optical imagery time series Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-17 Chao Ding; Guangcai Feng; Mingsheng Liao; Pengjie Tao; Lu Zhang; Qiang Xu
In this study, on the basis of the image correlation technique and the time-series images of Landsat-8 (L8), Sentinel-2 (S2), and GaoFen-2 (GF2), a systematic technical process is designed to investigate the precursory displacement evolution of two successive slope failures occurred in Baige Village, China on Oct. 11, 2018 and Nov. 3, 2018. An innovative fusion strategy is proposed to investigate the
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Estimating the overstory and understory vertical extents and their leaf area index in intensively managed loblolly pine (Pinus taeda L.) plantations using airborne laser scanning Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-17 Matthew J. Sumnall; Andrew Trlica; David R. Carter; Rachel L. Cook; Morgan L. Schulte; Otávio C. Campoe; Rafael A. Rubilar; Randolph H. Wynne; Valerie A. Thomas
Data from four discrete-return airborne laser scanning (ALS) acquisitions and three different sensor types across seven experimentally varied loblolly pine (Pinus taeda L.) plantations were used to test published and novel methodologies in quantifying forest structural attributes within stands, including height to live crown (HTLC; i.e. the lowest vertical canopy extent) of the canopy and the contributions
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Disturbance detection in landsat time series is influenced by tree mortality agent and severity, not by prior disturbance Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-16 Kyle C. Rodman; Robert A. Andrus; Thomas T. Veblen; Sarah J. Hart
Landsat time series (LTS) and associated change detection algorithms are useful for monitoring the effects of global change on Earth's ecosystems. Because LTS algorithms can be easily applied across broad areas, they are commonly used to map changes in forest structure due to wildfire, insect attack, and other important drivers of tree mortality. But factors such as initial forest density, tree mortality
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In-situ and triple-collocation based evaluations of eight global root zone soil moisture products Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-15 Lei Xu; Nengcheng Chen; Xiang Zhang; Hamid Moradkhani; Chong Zhang; Chuli Hu
Root zone soil moisture (RZSM) is a vital variable for vegetation growth, drought monitoring and agricultural water management. Satellite remote sensing measures soil moisture at the surface layer, while RZSM is derived usually by model-based simulations. Here, we provide the first comprehensive evaluation of eight RZSM products at a global scale, including GLDAS NOAH, ERA-5, MERRA-2, NCEP R1, NCEP
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Ice water content assessment in the single-, dual-, and triple-frequency radar scenarios Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-16 Eugenio Gorgucci; Luca Baldini; Elisa Adirosi; Mario Montopoli
With the advent of the Global Precipitation Measurement (GPM) mission and the associated Ground Validation campaigns, there has been a strong development of studies related to dual-frequency and more recently to triple-frequency radar. In this context, one requirement is that at least one of the radar frequencies operates in the Rayleigh regime while the others have to ensure a measurable difference
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Evolution of NDVI secular trends and responses to climate change: A perspective from nonlinearity and nonstationarity characteristics Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-16 Liqin Yang; Qingyu Guan; Jinkuo Lin; Jing Tian; Zhe Tan; Huichun Li
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Spectral range within global aCDOM(440) algorithms for oceanic, coastal, and inland waters with application to airborne measurements Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-16 Henry F. Houskeeper; Stanford B. Hooker; Raphael M. Kudela
The optically active component of dissolved organic material in aquatic ecosystems, or colored dissolved organic matter (CDOM), is represented by the coefficient of absorption due to the dissolved aquatic constituents at 440 nm, aCDOM(440). Remote sensing of aCDOM(440) enables characterization of ecosystem processes and aids in retrieval of chlorophyll a, a proxy for phytoplankton biomass. Spectrally
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OC-SMART: A machine learning based data analysis platform for satellite ocean color sensors Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-15 Yongzhen Fan; Wei Li; Nan Chen; Jae-Hyun Ahn; Young-Je Park; Susanne Kratzer; Thomas Schroeder; Joji Ishizaka; Ryan Chang; Knut Stamnes
We introduce a new platform, Ocean Color - Simultaneous Marine and Aerosol Retrieval Tool (OC-SMART), for analysis of data obtained by satellite ocean color sensors. OC-SMART is a multi-sensor data analysis platform which supports heritage, current, and possible future multi-spectral and hyper-spectral sensors from US, EU, Korea, Japan, and China, including SeaWiFS, Aqua/MODIS, SNPP/VIIRS, ISS/HICO
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Detection of shadows in high spatial resolution ocean satellite data using DINEOF Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-14 Aida Alvera-Azcárate; Dimitry Van der Zande; Alexander Barth; João Felipe Cardoso dos Santos; Charles Troupin; Jean-Marie Beckers
Cloud shadows present in high spatial resolution remote sensing datasets can affect the quality of the data if they are not properly detected and removed. When working with ocean data, cloud shadows are often difficult to differentiate from non-shadow values, since they show similar spectral characteristics than water pixels. A methodology to detect cloud shadows over the ocean is proposed. The present
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Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-10 Carlos Alberto Silva; Laura Duncanson; Steven Hancock; Amy Neuenschwander; Nathan Thomas; Michelle Hofton; Lola Fatoyinbo; Marc Simard; Charles Z. Marshak; John Armston; Scott Lutchke; Ralph Dubayah
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A multi-angular invariant spectral index for the estimation of leaf water content across a wide range of plant species in different growth stages Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-10 Xiao Li; Zhongqiu Sun; Shan Lu; Kenji Omasa
Plant leaf water content plays a key role in several biogeochemical processes, such as photosynthesis, evapotranspiration, and net primary production. Yet, the accurate estimation of leaf water content using multi-angular reflectance measurements across different plant species is still challenging. This study aims to propose a generic spectral index for accurately estimating equivalent water thickness
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Extending satellite ocean color remote sensing to the near-blue ultraviolet bands Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-10 Yongchao Wang; Zhongping Lee; Jianwei Wei; Shaoling Shang; Menghua Wang; Wendian Lai
Ultraviolet (UV) radiation has a profound impact on marine life, but historically and even currently, most ocean color satellites cannot provide radiance measurements in the UV, and thus UV penetration, in the global ocean. We develop a system (termed as UVISRdl) in this study, based on deep learning, to estimate remote sensing reflectance (Rrs) at 360, 380, and 400 nm (collectively termed as near-blue
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Assimilation of SMAP and ASCAT soil moisture retrievals into the JULES land surface model using the Local Ensemble Transform Kalman Filter Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-09 Eunkyo Seo; Myong-In Lee; Rolf H. Reichle
A land data assimilation system is developed to merge satellite soil moisture retrievals into the Joint U.K. Land Environment Simulator (JULES) land surface model (LSM) using the Local Ensemble Transform Kalman Filter (LETKF). The system assimilates microwave soil moisture retrievals from the Soil Moisture Active Passive (SMAP) radiometer and the Advanced Scatterometer (ASCAT) after bias correction
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Integration of allometric equations in the water cloud model towards an improved retrieval of forest stem volume with L-band SAR data in Sweden Remote Sens. Environ. (IF 9.085) Pub Date : 2020-12-08 Maurizio Santoro; Oliver Cartus; Johan E.S. Fransson
Much attention is paid to the estimation of forest biomass-related variables (stem volume and above-ground biomass) with synthetic aperture radar (SAR) backscatter images because of the increasing number of sensors in space providing global and repeated coverage and the sensitivity of the backscattered intensity to forest properties. One of the most popular models used to estimate a biomass-related
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