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Chlorophyll-a concentrations in 82 large alpine lakes on the Tibetan Plateau during 2003–2017: temporal–spatial variations and influencing factors Int. J. Digit. Earth (IF 3.097) Pub Date : 2021-01-13 Xuehui Pi; Lian Feng; Weifeng Li; Junguo Liu; Xingxing Kuang; Kun Shi; Wei Qi; Deliang Chen; Jing Tang
ABSTRACT As essential parts of the unique ecosystem of Tibetan Plateau (TP), the sizes and associated physical properties of alpine lakes have long been investigated. However, little is known about one of the most critical biogeochemical properties, i.e. the Chlorophyll-a (Chl-a) concentrations. Here, for the first time, we presented a comprehensive investigation of the temporal–spatial variations
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Governance interactions of spatial data infrastructures: an agent-based modelling approach Int. J. Digit. Earth (IF 3.097) Pub Date : 2021-01-11 Jaap-Willem Sjoukema; Jalal Samia; Arnold K. Bregt; Joep Crompvoets
ABSTRACT In order to facilitate and coordinate spatial data sharing and exchange, many organisations have developed spatial data infrastructures (SDIs). SDI governance plays a pivotal role in the development and evolution of an SDI, but as SDIs are complex adaptive systems, governing is a challenge. This research therefore proposes a complexity perspective to SDI governance by exploring the use of
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The geometry of mesoscale eddies in the South China Sea: characteristics and implications Int. J. Digit. Earth (IF 3.097) Pub Date : 2021-01-04 Guiyan Han; Fenglin Tian; Chunyong Ma; Ge Chen
ABSTRACT The symmetrical circular shape of mesoscale eddies has been widely used in their scientific researches. Recently, an elliptical average eddy shape has been confirmed for eddies in the global ocean using multi-satellite altimeter data. As a regional extension of a previous study on the geometry of global eddies, a mean eddy shape in the South China Sea (SCS) has been derived by averaging a
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Integrated monitoring of lakes’ turbidity in Wuhan, China during the COVID-19 epidemic using multi-sensor satellite observations Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-31 Xianghan Sun; Jianqiang Liu; Jianru Wang; Liqiao Tian; Qu Zhou; Jian Li
ABSTRACT During the COVID-19 epidemic in Wuhan, China, a series of measures were implemented by the government to prevent the spread of disease, including the lockdown policy and construction of emergency hospitals. To estimate the impact of these measures on aquatic environments, turbidity of lakes in Wuhan was dynamically monitored by integrating multi-sensor satellite observations. Calibrated against
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Supporting integrative maritime spatial planning by operationalising SEANERGY – a tool to study cross-sectoral synergies and conflicts Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-30 Ida Maria Bonnevie; Henning Sten Hansen; Lise Schrøder
ABSTRACT With growing pressures on marine ecosystems and on marine space, an increasingly needed strategy to optimise the use of marine space is to co-locate synergic marine human uses in close spatial–temporal proximity while separating conflicting marine human uses. The ArcMap toolbox SEANERGY is a new, cross-sectoral spatial decision support tool (DST) that enables maritime spatial planners to consider
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Investigate the relationships between the Aral Sea shrinkage and the expansion of cropland and reservoir in its drainage basins between 2000 and 2020 Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-29 Qiang Li; Xin Li; Youhua Ran; Min Feng; Yanyun Nian; Meibao Tan; Xi Chen
ABSTRACT The Aral Sea crisis is considered one of the most severe ecological tragedies from the 1960s in Central Asia. The reasons for this crisis, especially in the twenty-first century, are still scientific disputes. This study investigated the relationship between land cover change in the Aral Sea related basins and the Aral Sea crisis from 2000 to 2020 by employing the GlobeLand30 dataset with
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Validation of Landsat land surface temperature product in the conterminous United States using in situ measurements from SURFRAD, ARM, and NDBC sites Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-28 Si-Bo Duan; Zhao-Liang Li; Wei Zhao; Penghai Wu; Cheng Huang; Xiao-Jing Han; Maofang Gao; Pei Leng; Guofei Shang
ABSTRACT Since 1982, Landsat series of satellite sensors continuously acquired thermal infrared images of the Earth’s land surface. In this study, Landsat 5, 7, and 8 land surface temperature (LST) products in the conterminous United States from 2009 to 2019 were validated using in situ measurements collected at 6 SURFRAD (Surface Radiation Budget Network) sites, 6 ARM (Atmospheric Radiation Measurement)
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Antarctic-wide annual ice flow maps from Landsat 8 imagery between 2013 and 2019 Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-28 Qiang Shen; Hansheng Wang; C. K. Shum; Liming Jiang; Houtse Hsu; Fan Gao; Yingli Zhao
ABSTRACT Ice velocity constitutes a key parameter for quantifying ice-sheet discharge rates and is thus crucial for improving the coupled models of the Antarctic ice sheet towards accurately predict its contribution to future global sea-level rise. However, in Antarctica, high-resolution and continuous ice velocity estimates remain elusive, which is key to unravel Antarctica’s present-day ice mass
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Dense 3D surface reconstruction of large-scale streetscape from vehicle-borne imagery and LiDAR Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-17 Xiaohu Lin; Bisheng Yang; Fuhong Wang; Jianping Li; Xiqi Wang
ABSTRACT Accurate and efficient three-dimensional (3D) streetscape reconstruction is the fundamental ability for an exploration vehicle to navigate safely and perform high-level tasks. Recently, remarkable progress has been made in streetscape reconstruction with visual images and light detection and ranging (LiDAR), but they have difficulties either in scaling and reconstructing large-scale outdoors
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Ensemble machine learning models based on Reduced Error Pruning Tree for prediction of rainfall-induced landslides Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-15 Binh Thai Pham; Abolfazl Jaafari; Trung Nguyen-Thoi; Tran Van Phong; Huu Duy Nguyen; Neelima Satyam; Md Masroor; Sufia Rehman; Haroon Sajjad; Mehebub Sahana; Hiep Van Le; Indra Prakash
ABSTRACT In this paper, we developed highly accurate ensemble machine learning models integrating Reduced Error Pruning Tree (REPT) as a base classifier with the Bagging (B), Decorate (D), and Random Subspace (RSS) ensemble learning techniques for spatial prediction of rainfall-induced landslides in the Uttarkashi district, located in the Himalayan range, India. To do so, a total of 103 historical
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Sea ice conditions and navigability through the Northeast Passage in the past 40 years based on remote-sensing data Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-14 Miao Yu; Peng Lu; Zhiyuan Li; Zhijun Li; Qingkai Wang; Xiaowei Cao; Xiaodong Chen
ABSTRACT Sea ice conditions and navigability along four typical routes of the Northeast Passage (NEP) are analysed using remote-sensing data from 1979 to 2019. The influence of air temperature (T air) and surface wind on the sea ice concentration (SIC) and the navigability of routes is determined. It is found that the annually averaged SICs of the different routes have decreased over the past 41 years
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List of reviewers for International Journal of Digital Earth Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-12-04
(2020). List of reviewers for International Journal of Digital Earth. International Journal of Digital Earth: Vol. 13, No. 12, pp. (i)-(ii).
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Normalization of VIIRS DNB images for improved estimation of socioeconomic indicators Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-11-28 Duc Chuc Man; Hirakawa Tsubasa; Hiromichi Fukui
ABSTRACT Monthly Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) composite data are widely used in research, such as estimations of socioeconomic parameters. However, some surface conditions affect the VIIRS DNB radiance, which may create some estimation bias in certain regions. In this paper, we propose a novel normalization algorithm for VIIRS DNB monthly composite data. The
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Versioned geoscientific workflow for the collaborative geo-simulation of human-nature interactions – a case study of global change and human activities Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-11-26 Yuting Chen; Hui Lin; Ling Xiao; Qi Jing; Lan You; Yulin Ding; Mingyuan Hu; Adam Thomas Devlin
ABSTRACT obal change refers to changes in the relationship between humans and nature. It is desirable to actively integrate human social activities into the unified framework of global change so that their mutual relations and functional mechanisms can be understood. This complicated issue necessitates an appropriate method allowing domain experts to collaboratively contribute their knowledge to geoscientific
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A data fusion-based framework to integrate multi-source VGI in an authoritative land use database Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-11-05 Lanfa Liu; Ana-Maria Olteanu-Raimond; Laurence Jolivet; Arnaud-le Bris; Linda See
ABSTRACT Updating an authoritative Land Use and Land Cover (LULC) database requires many resources. Volunteered geographic information (VGI) involves citizens in the collection of data about their spatial environment. There is a growing interest in using existing VGI to update authoritative databases. This paper presents a framework aimed at integrating multi-source VGI based on a data fusion technique
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Improvement of microwave emissivity parameterization of frozen Arctic soils using roughness measurements derived from photogrammetry Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-10-26 J. Meloche; A. Royer; A. Langlois; N. Rutter; V. Sasseville
ABSTRACT Soil emissivity of Arctic regions is a key parameter for assessing surface properties from microwave brightness temperature (Tb) measurements. Particularly in winter, frozen soil permittivity and roughness are two poorly characterized unknowns that must be considered. Here, we show that after removing snow, the 3D soil roughness can be accurately inferred from in-situ photogrammetry using
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Monitoring travel patterns in German city regions with the help of mobile phone network data Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-10-22 Stefan Fina; Jigeeshu Joshi; Dirk Wittowsky
ABSTRACT This paper discusses the possibility to use mobile phone network data to monitor spatial policies in land use and transport planning. Monitoring requires robust time series and reproducible concepts linking spatial policies to monitoring outcomes, a requirement differing from current literature where mobile phone data analysis is exemplified in selected areas with privileged data access. Concepts
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Incorporating DeepLabv3+ and object-based image analysis for semantic segmentation of very high resolution remote sensing images Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-10-09 Shouji Du; Shihong Du; Bo Liu; Xiuyuan Zhang
ABSTRACT Semantic segmentation of remote sensing images is an important but unsolved problem in the remote sensing society. Advanced image semantic segmentation models, such as DeepLabv3+, have achieved astonishing performance for semantically labeling very high resolution (VHR) remote sensing images. However, it is difficult for these models to capture the precise outlines of ground objects and explore
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ClimateCharts.net – an interactive climate analysis web platform Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-10-07 Laura Zepner; Pierre Karrasch; Felix Wiemann; Lars Bernard
ABSTRACT This article describes the conception and implementation of a web platform which uses special charts and maps for climate monitoring and analysis. At first it gives an overview of related web applications and their advantages and limitations. This is followed by a basic introduction of current technologies and methods for working with climate data, geospatial web services and visualization
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Taking the pulse of COVID-19: a spatiotemporal perspective Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-25 Chaowei Yang; Dexuan Sha; Qian Liu; Yun Li; Hai Lan; Weihe Wendy Guan; Tao Hu; Zhenlong Li; Zhiran Zhang; John Hoot Thompson; Zifu Wang; David Wong; Shiyang Ruan; Manzhu Yu; Douglas Richardson; Luyao Zhang; Ruizhi Hou; You Zhou; Cheng Zhong; Yifei Tian; Fayez Beaini; Kyla Carte; Colin Flynn; Wei Liu; Dieter Pfoser; Shuming Bao; Mei Li; Haoyuan Zhang; Chunbo Liu; Jie Jiang; Shihong Du; Liang Zhao; Mingyue
ABSTRACT The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, Brazil, Russia, and the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., India, Russia, and Brazil. In response
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Research agenda for the Russian Far East and utilization of multi-platform comprehensive environmental observations Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-09-29 Tuukka Petäjä; Kirill S. Ganzei; Hanna K. Lappalainen; Ksenia Tabakova; Risto Makkonen; Jouni Räisänen; Sergey Chalov; Markku Kulmala; Sergej Zilitinkevich; Petr Ya Baklanov; Renat B. Shakirov; Natalia V. Mishina; Evgeny G. Egidarev; Igor I. Kondrat’ev
ABSTRACT The Russian Far East is a region between China and the Russian Arctic with a diverse climatological, geophysical, oceanic, and economical characteristic. The southern region is located in the Far East monsoon sector, while the northern parts are affected by the Arctic Ocean and cold air masses penetrating far to the south. Growing economic activities and traffic connected to the China Belt
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Interactive data styling and multifocal visualization for a multigrid web-based Digital Earth Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-09-27 M. J. Sherlock; M. Hasan; F. F. Samavati
ABSTRACT Globe-based Digital Earth (DE) is a promising system that uses 3D models of the Earth for integration, organization, processing, and visualization of vast multiscale geospatial datasets. The growing size and scale of geospatial datasets present significant obstacles to interactive viewing and meaningful visualizations of these DE systems. To address these challenges, we present a novel web-based
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Assessing remotely sensed and reanalysis products in characterizing surface soil moisture in the Mongolian Plateau Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-09-21 Min Luo; Chula Sa; Fanhao Meng; Yongchao Duan; Tie Liu; Yuhai Bao
Soil moisture (SM) plays a crucial role in the dynamics of coupled atmosphere, water, energy, and carbon cycles. In this study, the spatiotemporal distribution and variations of SM in the Mongolian Plateau were investigated for the period of 1982–2018 based on four gridded SM datasets. Taking the observed SM from 33 monitoring stations as a reference, the reliability of these four gridded products
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Building health monitoring in the old town of Madrid: applicability of SAR Imagery to the monitoring of underground works through classification indexes Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-09-08 Adrian Jesus Garcia; Beatriz González-Rodrigo; Sara Martinez; Ruben Martinez; Miguel Marchamalo
The old city centers of many major cities represent a great challenge from a constructive point of view since the foundations of the buildings consist of an aggregation of previous constructions. This endorses thorough monitoring activities during any underground construction. The capabilities of the persistent scatterer interferometry (PSI) can be exploited to cope with these monitoring needs. However
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Improved modeling and analysis of the patch size–frequency distribution of forest disturbances in China based on a Landsat forest cover change product Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-09-03 Dan-Xia Song; Chengquan Huang; Tao He; Joseph O. Sexton; Ainong Li; Sike Li; Hao Wu; John R. Townshend
Forest disturbances have been altering the ecological properties of ecosystems; meanwhile, disturbance events of varying sizes create different structures and functions for a forest landscape. Therefore, size and frequency are important attributes of disturbances, and their relationship should be studied. We present a hierarchical method through the modeling of the overall trend of the size–frequency
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Impact of spatiotemporal land-use and land-cover changes on surface urban heat islands in a semiarid region using Landsat data Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-09-02 Ehsan Kamali Maskooni; Hossein Hashemi; Ronny Berndtsson; Peyman Daneshkar Arasteh; Mohammad Kazemi
Many factors are involved in urban heat island development, such as lack of green spaces, improper choice of building materials, densification, and other human activities. The aim of this research was to quantify the effects of land-use/land-cover (LU/LC) changes on urban land surface temperature (LST) during a 25-year period (1993–2018) for the semiarid Shiraz City in southern Iran using Landsat data
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Separating the impacts of climate variability, land-use change and large reservoir operations on streamflow in the Yangtze River basin, China, using a hydrological modeling approach Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-30 Ning Nie; Wanchang Zhang; Min Liu; Hao Chen; Dengzhong Zhao
Separating the individual effects of climate variability and human activities on streamflow is more important than just knowing their combined effects. In this paper, using a scenario-based hydrological simulation approach, the streamflow changes caused by climate variability and two different types of human activities (i.e. land-use change and large reservoirs operations) as well as the contribution
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Distinguishing different subclasses of water bodies for long-term and large-scale statistics of lakes: a case study of the Yangtze River basin from 2008 to 2018 Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-24 Jin Luo; Zeqiang Chen; Nengcheng Chen
Long-term and large-scale lake statistics are meaningful for the study of environment change, but many of the existing methods are labour-intensive and time-consuming. To overcome this problem, a novel method for long-term and large-scale lake extraction by shape-factors- and machine-learning-based water body classification is proposed. An experiment was conducted to extract the lakes in the Yangtze
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Gap analysis in decision support systems for real-estate in the era of the digital earth Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-20 Hamidreza Rabiei-Dastjerdi; Gavin McArdle; Stephen A. Matthews; Peter Keenan
Searching for a property is inherently a multicriteria spatial decision. The decision is primarily based on three high-level criteria composed of household needs, building facilities, and location characteristics. Location choice is driven by diverse characteristics; including but not limited to environmental factors, access, services, and the socioeconomic status of a neighbourhood. This article aims
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Forecasting NDVI in multiple complex areas using neural network techniques combined feature engineering Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-20 Changlu Cui; Wen Zhang; ZhiMing Hong; LingKui Meng
ABSTRACT NDVI (Normalized difference vegetation index) is a critical variable for monitoring climate change, studying ecological balance, and exploring the pattern of regional phenology. Traditional neural network models only consider image features in time series prediction, while historical data and its changes play an important role in time series forecasting. For this study, we proposed convolutional
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Lessons from a Marine Spatial Planning data management process for Ireland Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-19 Sarah Flynn; Will Meaney; Adam M. Leadbetter; Jeffrey P. Fisher; Caitriona Nic Aonghusa
ABSTRACT This paper presents a framework containing ten components to deliver a data management process for the storage and management of data used for Marine Spatial Planning (MSP) in Ireland. The work includes a data process flow and a recommended solution architecture. The architecture includes a central data catalogue and a spatial storage system. The components of the process are presented to
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Volunteered remote sensing data generation with air passengers as sensors Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-19 Chisheng Wang; Yongquan Wang; Leyang Wang; Zhongwen Hu; Shaobiao Zhang; Shuanglong Wang; Wenqun Xiu; Hongxing Cui; Dan Wang; Qingquan Li
Remote sensing satellites are playing very important roles in diverse earth observation fields. However, long revisit period, high cost and dense cloud cover have been the main limitations of satellite remote sensing for a long time. This paper introduces the novel volunteered passenger aircraft remote sensing (VPARS) concept, which can partly overcome these problems. By obtaining aerial imaging data
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The role of machine intelligence in photogrammetric 3D modeling – an overview and perspectives Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-10 Rongjun Qin; Armin Gruen
The process of modern photogrammetry converts images and/or LiDAR data into usable 2D/3D/4D products. The photogrammetric industry offers engineering-grade hardware and software components for various applications. While some components of the data processing pipeline work already automatically, there is still substantial manual involvement required in order to obtain reliable and high-quality results
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Analysis of geo-spatiotemporal data using machine learning algorithms and reliability enhancement for urbanization decision support Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-08-10 Kwame O. Hackman; Xuecao Li; Daniel Asenso-Gyambibi; Emmanuella A. Asamoah; Isaac. D. Nelson
ABSTRACT We present systematic analyses of the temporal dynamics of the growth of Kumasi, the fastest growing city in Ghana using 20-year Landsat time-series data from 2000 to 2020 (with 1986 Landsat image as a baseline). Two classification algorithms – random forest (RF) and support vector machines (SVM) – were used to produce binary (built-up / non-built up) maps for all years within the temporal
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Analyzing Antarctic ice sheet snowmelt with dynamic Big Earth Data Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-07-30 Dong Liang; Huadong Guo; Lu Zhang; Mingwei Wang; Lizhe Wang; Lei Liang; Zeeshan Shirazi
ABSTRACT Big Earth Data—big data associated with Earth sciences—can potentially revolutionize research on climate change, sustainable development, and other issues of global concern. For example, analyzing massive amounts of satellite imagery of polar environments, which are sensitive to the effects of climate change, provides insights into global climate trends. This study proposes a method to use
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Machine learning methods’ performance in radiative transfer model inversion to retrieve plant traits from Sentinel-2 data of a mixed mountain forest Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-07-15 Abebe Mohammed Ali; Roshanak Darvishzadeh; Andrew Skidmore; Tawanda W. Gara; Marco Heurich
ABSTRACT Assessment of vegetation biochemical and biophysical variables is useful when developing indicators for biodiversity monitoring and climate change studies. Here, we compared a radiative transfer model (RTM) inversion by merit function and five machine learning algorithms trained on an RTM simulated dataset predicting the three plant traits leaf chlorophyll content (LCC), canopy chlorophyll
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Assessment of VIIRS 375 m active fire using tropical peatland combustion algorithm applied to Landsat-8 over Indonesia’s peatlands Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-07-09 Parwati Sofan; David Bruce; Wilfrid Schroeder; Eriita Jones; Jackie Marsden
ABSTRACT VIIRS 375 m active fire data (VNP14IMG), the highest spatial resolution available cost-free fire product, were assessed for representing fire in typical degraded tropical peatlands in Indonesia. The results of applying the Tropical Peatland Combustion Algorithm to Landsat-8 (ToPeCAl-L8) daytime imagery were utilised as the fire references. To permit the comparison of non-simultaneous VNP14IMG
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Sensitivity analysis of parameters and contrasting performance of ground filtering algorithms with UAV photogrammetry-based and LiDAR point clouds Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-07-09 Petr Klápště; Michal Fogl; Vojtěch Barták; Kateřina Gdulová; Rudolf Urban; Vítězslav Moudrý
ABSTRACT Most ground filtering algorithms are primarily designed for airborne LiDAR point cloud processing and their successful use in identifying ground points from photogrammetric point clouds remains questionable. We compared six ground filtering algorithms implemented in Metashape, ArcGIS, CloudCompare, LAStools, and PDAL. We used UAV photogrammetry-based (acquired under leaf-off conditions) and
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DAPR-tree: a distributed spatial data indexing scheme with data access patterns to support Digital Earth initiatives Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-06-12 Jizhe Xia; Sicheng Huang; Shaobiao Zhang; Xiaoming Li; Jianrong Lyu; Wenqun Xiu; Wei Tu
ABSTRACT This paper proposes a novel data indexing scheme, the distributed access pattern R-tree (DAPR-tree), for spatial data retrieval in a distributed computing environment. As compared to traditional distributed indexing schemes, the DAPR-tree introduces the data access patterns during the indexing utilization stage so that a more balanced indexing structure can be provided for spatial applications
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Mapping summer soybean and corn with remote sensing on Google Earth Engine cloud computing in Parana state – Brazil Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-06-05 Alex Paludo; Willyan Ronaldo Becker; Jonathan Richetti; Laíza Cavalcante De Albuquerque Silva; Jerry Adriani Johann
ABSTRACT Brazilian farming influences directly the worldwide economy. Thus, fast and reliable information on areas sown with the main crops is essential for planning logistics and public or private commodity market policies. Recent farming practices have embraced remote sensing to provide fast and reliable information on commodity dynamics. Medium-to-low resolution free orbital images, such as those
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The construction of personalized virtual landslide disaster environments based on knowledge graphs and deep neural networks Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-06-04 Yunhao Zhang; Jun Zhu; Qing Zhu; Yakun Xie; Weilian Li; Lin Fu; Junxiao Zhang; Jianmei Tan
ABSTRACT Virtual Landslide Disaster environments are important for multilevel simulation, analysis and decision-making about Landslide Disasters. However, in the existing related studies, complex disaster scene objects and relationships are not deeply analyzed, and the scene contents are fixed, which is not conducive to meeting multilevel visualization task requirements for diverse users. To resolve
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Book review for ‘Manual of Digital Earth’ Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-05-29 Luis M. Vilches-Blázquez
(2020). Book review for ‘Manual of Digital Earth’. International Journal of Digital Earth: Vol. 13, No. 7, pp. 851-853.
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Change detection, risk assessment and mass balance of mobile dune fields near Dunhuang Oasis with optical imagery and global terrain datasets Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-05-18 Chao Ding; Guangcai Feng; Mingsheng Liao; Lu Zhang
ABSTRACT Quantifying the kinematic evolution patterns of dune migration plays a major role in resisting the sand-dust disasters and evaluating the desertification process. With the increment of optical observations, measuring the dune migration with dense spatial and temporal density has become possible. In this study, with the open-accessible Landsat-8 (L8)/Sentinel-2 (S2) imagery and global terrain
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Fast registration of forest terrestrial laser scans using key points detected from crowns and stems Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-05-13 Wenxia Dai; Bisheng Yang; Xinlian Liang; Zhen Dong; Ronggang Huang; Yunsheng Wang; Jiri Pyörälä; Antero Kukko
ABSTRACT Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. Most existing registration methods rely on stems to determine the transformation parameters. However, the complexity of the registration problem increases dramatically as the number of stems grows. It is tricky to reduce the stems and determine the valid ones that can provide reliable registration
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Automated location correction and spot height generation for named summits in the coterminous United States Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-04-30 Samantha T. Arundel; Gaurav Sinha
ABSTRACT Spot elevations published on historical U.S. Geological Survey topographic maps were established as needed to enhance information imparted by the quadrangle’s contours. In addition to other features, labels were routinely placed on mountain summits. While some elevations were established through field survey triangulation, many were computed during photogrammetric stereo-compilation. Today
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Automated location correction and spot height generation for named summits in the coterminous United States Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-04-30 Samantha T. Arundel; Gaurav Sinha
ABSTRACT Spot elevations published on historical U.S. Geological Survey topographic maps were established as needed to enhance information imparted by the quadrangle’s contours. In addition to other features, labels were routinely placed on mountain summits. While some elevations were established through field survey triangulation, many were computed during photogrammetric stereo-compilation. Today
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Automated location correction and spot height generation for named summits in the coterminous United States Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-04-30 Samantha T. Arundel; Gaurav Sinha
Spot elevations published on historical U.S. Geological Survey topographic maps were established as needed to enhance information imparted by the quadrangle’s contours. In addition to other features, labels were routinely placed on mountain summits. While some elevations were established through field survey triangulation, many were computed during photogrammetric stereo-compilation. Today, Global
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A novel method of determining the optimal polyhedral orientation for discrete global grid systems applicable to regional-scale areas of interest Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-04-14 Jianbin Zhou; Jin Ben; Rui Wang; Mingyang Zheng; Xiaochuang Yao; Lingyu Du
ABSTRACT The polyhedral discrete global grid system (DGGS) is a multi-resolution discrete earth reference model supporting the fusion and processing of multi-source geospatial information. The orientation of the polyhedron relative to the earth is one of its key design choices, used when constructing the grid system, as the efficiency of indexing will decrease if local areas of interest extend over
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Assessing 40 years of spatial dynamics and patterns in megacities along the Belt and Road region using satellite imagery Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-04-01 Zhongchang Sun; Sisi Yu; Huadong Guo; Cuizhen Wang; ZengXiang Zhang; Ru Xu
ABSTRACT The Belt and Road (B&R) region, a vital area with historical, economic, cultural and political significance, has undergone rapid urbanization in the past several decades, especially in the form of urban expansion. In this study, 20 megacities in the B&R region were selected to explore different spatiotemporal patterns of urban expansion. Object-oriented support vector machines (SVM), annual
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Big Earth Data science: an information framework for a sustainable planet Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-03-23 Huadong Guo; Stefano Nativi; Dong Liang; Max Craglia; Lizhe Wang; Sven Schade; Christina Corban; Guojin He; Martino Pesaresi; Jianhui Li; Zeeshan Shirazi; Jie Liu; Alessandro Annoni
ABSTRACT The digital transformation of our society coupled with the increasing exploitation of natural resources makes sustainability challenges more complex and dynamic than ever before. These changes will unlikely stop or even decelerate in the near future. There is an urgent need for a new scientific approach and an advanced form of evidence-based decision-making towards the benefit of society,
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Geo-analytical question-answering with GIS Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-03-12 Simon Scheider; Enkhbold Nyamsuren; Han Kruiger; Haiqi Xu
ABSTRACT Question Answering (QA), the process of computing valid answers to questions formulated in natural language, has recently gained attention in both industry and academia. Translating this idea to the realm of geographic information systems (GIS) may open new opportunities for data scientists. In theory, analysts may simply ask spatial questions to exploit diverse geographic information resources
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Crustal evolution events in the Chinese continent: evidence from a zircon U-Pb database Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-03-11 Yujing Wu; Xianjun Fang; Sisi Liao; Lizhi Xue; Zhe Chen; Jiangnan Yang; Yamin Lu; Kun Ling; Shengyi Hu; Shuyuan Kong; Yiwei Xiong; Huacheng Li; Xiuqi Shang; Rui Ji; Xueyun Lu; Biao Song; Lei Zhang; Jianqing Ji
ABSTRACT The zircon U-Pb chronology database provides a good opportunity to obtain important zircon growth peak periods in the Earth's history so as to study the origin and evolution of the crust. It should be noted that research preference affects the objectivity of zircon sampling, leading to hot data in the database and age statistics. To evaluate the influence of hot data on statistical results
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Spatiotemporal event detection: a review Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-03-09 Manzhu Yu; Myra Bambacus; Guido Cervone; Keith Clarke; Daniel Duffy; Qunying Huang; Jing Li; Wenwen Li; Zhenlong Li; Qian Liu; Bernd Resch; Jingchao Yang; Chaowei Yang
ABSTRACT The advancements of sensing technologies, including remote sensing, in situ sensing, social sensing, and health sensing, have tremendously improved our capability to observe and record natural and social phenomena, such as natural disasters, presidential elections, and infectious diseases. The observations have provided an unprecedented opportunity to better understand and respond to the spatiotemporal
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Three-dimensional CityGML building models in mobile augmented reality: a smartphone-based pose tracking system Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-03-02 Christoph Blut; Jörg Blankenbach
ABSTRACT Many augmented reality (AR) systems are developed for entertainment, but AR and particularly mobile AR potentially have more application possibilities in other fields. For example, in civil engineering or city planning, AR could be used in combination with CityGML building models to enhance some typical workflows in planning, execution and operation processes. A concrete example is the geo-referenced
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How does map use differ in virtual reality and desktop-based environments? Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-02-26 Weihua Dong; Tianyu Yang; Hua Liao; Liqiu Meng
ABSTRACT Maps based on virtual reality (VR) are evolving and are being increasingly used in the field of geography. However, the advantages of VR based on the map use processes of users over desktop-based environments (DEs) are not fully understood. In this study, an experiment was conducted in which 120 participants performed map use tasks using maps and globes in VR and DE. The participants’ eye
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New hybrid algorithm for land surface temperature retrieval from multiple-band thermal infrared image without atmospheric and emissivity data inputs Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-02-23 Huazhong Ren; Jiaji Dong; Rongyuan Liu; Yitong Zheng; Jinxin Guo; Shanshan Chen; Jing Nie; Yan Zhao
ABSTRACT Land surface temperature (LST) retrieval from thermal infrared (TIR) remote sensing image requires atmospheric and land surface emissivity (LSE) data that are sometimes unattainable. To overcome this problem, a hybrid algorithm is developed to retrieve LST without atmospheric correction and LSE data input, by combining the split-window (SW) and temperature–emissivity separation (TES) algorithms
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Detecting visually salient scene areas and deriving their relative spatial relations from continuous street-view panoramas Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-02-23 Fangli Guan; Zhixiang Fang; Tao Yu; Mingxiang Feng; Fan Yang
ABSTRACT A salient scene is an area within an image that contains visual elements that stand out from surrounding areas. They are important for distinguishing landmarks in first-person-view (FPV) applications and determining spatial relations in images. The relative spatial relation between salient scenes acts as a visual guide that is easily accepted and understood by users in FPV applications. However
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Identifying marsh dieback events from Landsat image series (1998–2018) with an Autoencoder in the NIWB estuary, South Carolina Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-02-20 Huixuan Li; Cuizhen Wang; Jean T. Ellis; Yuxin Cui; Gwen Miller; James T. Morris
ABSTRACT This study reports an inventory of marsh dieback events from spatial and temporal perspectives in the North Inlet-Winyah Bay (NIWB) estuary, South Carolina (SC). Past studies in the Gulf/Atlantic coast states have reported acute marsh dieback events in which marsh rapidly browned and thinned, leaving stubble of dead stems or mudflat with damaged ecosystem services. Reported marsh dieback in
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Use of Twitter in disaster rescue: lessons learned from Hurricane Harvey Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-02-19 Volodymyr V. Mihunov; Nina S. N. Lam; Lei Zou; Zheye Wang; Kejin Wang
ABSTRACT Despite the increasingly prominent role of social media in disaster events, studies analyzing its use in rescue operations remain scanty. Hurricane Harvey hit Texas with unprecedented rainfall and flooding in 2017 and was marked by widespread use of social media for rescue requests. We conducted a survey of 195 Twitter users in Houston and surrounding communities who had requested for rescue
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Producing consistent visually interpreted land cover reference data: learning from feedback Int. J. Digit. Earth (IF 3.097) Pub Date : 2020-02-18 Agnieszka Tarko; Nandin-Erdene Tsendbazar; Sytze de Bruin; Arnold K. Bregt
ABSTRACT Reference data for large-scale land cover map are commonly acquired by visual interpretation of remotely sensed data. To assure consistency, multiple images are used, interpreters are trained, sites are interpreted by several individuals, or the procedure includes a review. But little is known about important factors influencing the quality of visually interpreted data. We assessed the effect
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