Spatial prediction of soil erosion risk by remote sensing, GIS and RUSLE approach: a case study of Siruvani river watershed in Attapady valley, Kerala, India

2011 ◽  
Vol 64 (4) ◽  
pp. 965-972 ◽  
Author(s):  
V. Prasannakumar ◽  
R. Shiny ◽  
N. Geetha ◽  
H. Vijith
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Spatial Prediction ◽  
River Watershed ◽  
Erosion Risk ◽  
Soil Erosion Risk

scholarly journals Soil Erosion Estimation Using Remote Sensing Techniques in Wadi Yalamlam Basin, Saudi Arabia

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Jarbou A. Bahrawi ◽  
Mohamed Elhag ◽  
Amal Y. Aldhebiani ◽  
Hanaa K. Galal ◽  
Ahmad K. Hegazy ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Saudi Arabia ◽  
Soil Erosion ◽  
Decision Support Tool ◽  
Data Availability ◽  
Productive Capacity ◽  
Support Tool ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Key Aspects

Soil erosion is one of the major environmental problems in terms of soil degradation in Saudi Arabia. Soil erosion leads to significant on- and off-site impacts such as significant decrease in the productive capacity of the land and sedimentation. The key aspects influencing the quantity of soil erosion mainly rely on the vegetation cover, topography, soil type, and climate. This research studies the quantification of soil erosion under different levels of data availability in Wadi Yalamlam. Remote Sensing (RS) and Geographic Information Systems (GIS) techniques have been implemented for the assessment of the data, applying the Revised Universal Soil Loss Equation (RUSLE) for the calculation of the risk of erosion. Thirty-four soil samples were randomly selected for the calculation of the erodibility factor, based on calculating theK-factor values derived from soil property surfaces after interpolating soil sampling points. Soil erosion risk map was reclassified into five erosion risk classes and 19.3% of the Wadi Yalamlam is under very severe risk (37,740 ha). GIS and RS proved to be powerful instruments for mapping soil erosion risk, providing sufficient tools for the analytical part of this research. The mapping results certified the role of RUSLE as a decision support tool.

Integration of Remote Sensing and GIS for Evaluating Soil Erosion Risk in Northwestern Zhejiang, China

2012 ◽  
Vol 78 (9) ◽  
pp. 935-946 ◽  
Author(s):  
Jianqin Huang ◽  
Dengsheng Lu ◽  
Jin Li ◽  
Jiasen Wu ◽  
Shiquan Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Remote Sensing And Gis ◽  
Erosion Risk ◽  
Soil Erosion Risk

Assessment and Monitoring of Soil Erosion Risk and Land Degradation in Arable Land Combining Remote Sensing Methodologies and RUSLE Factors

2021 ◽  
pp. 704-716
Author(s):  
Biagio Tucci ◽  
Gabriele Nolè ◽  
Antonio Lanorte ◽  
Valentina Santarsiero ◽  
Giuseppe Cillis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Land Degradation ◽  
Arable Land ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Assessment And Monitoring
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