Quantitative Estimation of Soil Erosion Using Open-Access Earth Observation Data Sets and Erosion Potential Model

2019 ◽  
Vol 4 (4) ◽  
pp. 187-200 ◽  
Author(s):  
Edon Maliqi ◽  
Sudhir Kumar Singh
Keyword(s):  
Open Access ◽  
Soil Erosion ◽  
Potential Model ◽  
Quantitative Estimation ◽  
Earth Observation ◽  
Data Sets ◽  
Observation Data ◽  
Earth Observation Data

scholarly journals Evaluation of the Potential of Convolutional Neural Networks and Random Forests for Multi-Class Segmentation of Sentinel-2 Imagery

2019 ◽  
Vol 11 (8) ◽  
pp. 907 ◽  
Author(s):  
Vasileios Syrris ◽  
Paul Hasenohr ◽  
Blagoj Delipetrev ◽  
Alexander Kotsev ◽  
Pieter Kempeneers ◽  
...  
Keyword(s):  
Random Forests ◽  
Computational Models ◽  
Earth Observation ◽  
Data Sets ◽  
Observation Data ◽  
Computational Aspects ◽  
Learning Set ◽  
Earth Observation Data ◽  
Class Segmentation ◽  
Sentinel 2

Motivated by the increasing availability of open and free Earth observation data through the Copernicus Sentinel missions, this study investigates the capacity of advanced computational models to automatically generate thematic layers, which in turn contribute to and facilitate the creation of land cover products. In concrete terms, we assess the practical and computational aspects of multi-class Sentinel-2 image segmentation based on a convolutional neural network and random forest approaches. The annotated learning set derives from data that is made available as result of the implementation of European Union’s INSPIRE Directive. Since this network of data sets remains incomplete in regard to some geographic areas, another objective of this work was to provide consistent and reproducible ways for machine-driven mapping of these gaps and a potential update of the existing ones. Finally, the performance analysis identifies the most important hyper-parameters, and provides hints on the models’ deployment and their transferability.

Modelling of land use land cover change using earth observation data-sets of Tons River Basin, Madhya Pradesh, India

2017 ◽  
Vol 33 (11) ◽  
pp. 1202-1222 ◽  
Author(s):  
Sudhir Kumar Singh ◽  
Prosper Basommi Laari ◽  
Sk. Mustak ◽  
Prashant K. Srivastava ◽  
Szilárd Szabó
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
River Basin ◽  
Earth Observation ◽  
Data Sets ◽  
Observation Data ◽  
Land Use Land Cover ◽  
Earth Observation Data ◽  
Tons River Basin

Prediction of soil erosion risk using earth observation data under recent emission scenarios of CMIP6

2021 ◽  
pp. 1-24
Author(s):  
Nirmal Kumar ◽  
Sudhir Kumar Singh ◽  
Amit Kumar Dubey ◽  
Ram L. Ray ◽  
Sk. Mustak ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Earth Observation ◽  
Observation Data ◽  
Emission Scenarios ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Earth Observation Data

scholarly journals Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets

2016 ◽  
pp. 1-15 ◽  
Author(s):  
Sudhir Kumar Singh ◽  
Prashant K. Srivastava ◽  
Szilárd Szabó ◽  
George P. Petropoulos ◽  
Manika Gupta ◽  
...  
Keyword(s):  
Land Cover ◽  
Earth Observation ◽  
Data Sets ◽  
Observation Data ◽  
Spatial Metrics ◽  
Land Cover Dynamics ◽  
Earth Observation Data
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