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Article Title :

Assessment of Soil Loss using Revised Universal Soil Loss Equation RUSLE: A Remote Sensing and GIS Approach

Remote Sensing of Land

2 (2018)



Soil loss , RUSLE , Remote Sensing , GIS , Shivganga Basin

Crossref citations: 13
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A comprehensive methodology that combines Revised Universal Soil Loss Equation (RUSLE), Remote Sensing data and Geographic Information System (GIS) techniques was used to determine the soil loss vulnerability of an agriculture mountainous watershed in Maharashtra, India. The spatial variation in rate of annual soil loss was obtained by integrating raster derived parameter in GIS environment. The thematic layers such as TRMM [Tropical Rainfall Measuring Mission] derived rainfall erosivity (R), soil erodibility (K), GDEM based slope length and steepness (LS), land cover management (C) and factors of conservation practices (P) were calculated to identify their effects on average annual soil loss. The highest potential of estimated soil loss was 688.397 t/ha/yr. The mean annual soil loss is 1.26 t/ha/yr and highest soil loss occurs on the main watercourse, since high slope length and steepness. The spatial soil loss maps prepared with RUSLE method using remote sensing and GIS can be helpful as a lead idea in arising plans for land use development and administration in the ecologically sensitive hilly areas.

RUSLE is used to estimate soil loss from agricultural and semi-urbanized mountainous watershed.

Remote sensing data such TRMM based rainfall, DEM, Satellite Image helped to identify more fine soil loss.

GIS environment helps to integrate, evaluate and map the potential annual soil loss.

The study highlights the importance of remote sensing data in soil loss analysis.

RUSLE is very subtle to analysis the soil loss in mountainous terrain and climatic parameters like rainfall.


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