Soil Erosion Assessment by RUSLE, Google Earth Engine, and Geospatial Techniques over Rel River Watershed, Gujarat, India
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s41101-023-00223-x.pdf
Reference55 articles.
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3. Amundson R, Berhe AA, Hopmans JW, Olson C, Sztein AE, Sparks DL (2015) Soil and human security in the 21st century. Science 1979:348. https://doi.org/10.1126/science.1261071
4. Ayalew DA, Deumlich D, Šarapatka B, Doktor D (2020) Quantifying the sensitivity of NDVI-based C factor estimation and potential soil erosion prediction using spaceborne earth observation data. Remote Sens 12:1136. https://doi.org/10.3390/rs12071136
5. Bachaoui B, Bachaoui EM, Maimouni S, Lhissou R, El Harti A, El Ghmari A (2014) The use of spectral and geomorphometric data for water erosion mapping in El Ksiba region in the central High Atlas Mountains of Morocco. Applied Geomatics 6:159–169. https://doi.org/10.1007/s12518-014-0130-3
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1. Soil Loss Estimation by Water Erosion in Agricultural Areas Introducing Artificial Intelligence Geospatial Layers into the RUSLE Model;Land;2024-02-01
2. Soil Loss Estimation Using RUSLE in Hard Rock Terrain: a Case Study of Bundelkhand, India;Water Conservation Science and Engineering;2023-11-30
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