The effect of land use and land cover changes on soil erosion in semi-arid areas using cloud-based google earth engine platform and GIS-based RUSLE model

Maryam Nourizadeh, Hamed Naghavi () and Ebrahim Omidvar ()
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Maryam Nourizadeh: Lorestan University
Hamed Naghavi: Lorestan University
Ebrahim Omidvar: University of Kashan

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 7, No 41, 6922 pages

Abstract: Abstract Soil erosion has attracted the attention of researchers and managers as an environmental crisis. One of the effective factors in soil erosion is land use and land cover (LULC) change. Accordingly, the purpose of the present study is to explore the effect of LULC change on soil erosion in a semi-arid region in the southwest of Iran. LULC change map was generated over a period of 30 years (1989–2019) using a new approach in which the Normalized Difference Vegetation Index (NDVI) time series of each year was classified in the google earth engine (GEE). For classifying the NDVI time series, a nonparametric Support Vector Machine (SVM) classification method was employed. The LULC maps were also used as an input factor in the soil erosion estimation model. The amount of soil erosion in the region was estimated using the Revised Universal Soil Loss Equation (RUSLE) empirical model in the Geographical Information System (GIS) environment. Validation of LULC maps generated in GEE indicated overall accuracy higher than 86% and the kappa coefficient higher than 0.82. The study of LULC change trends revealed that the area of forests, pastures, and rock outcrop in the region has diminished, while the area of agricultural and residential LUs has been expanded. Also, the highest rate of LULC conversion was related to the conversion of forests to agricultural lands. Estimating the amount of soil erosion in the region using the RUSLE model indicated that the average annual erosion in 1989 and 2019 was 15.48 and 20.41 tons per hectare, respectively, which indicates an increase of 4.93 tons in hectares, while the hot spots of erosion in the area have increased at the confidence levels of 90, 95, and 99%. Finally, matching the LULC change map with the soil erosion map revealed that the degradation of forests and pastures as well as their conversion to agricultural lands has had the greatest impact on the increase in soil erosion.

Keywords: Satellite images; NDVI; SVM; Empirical models; Time series (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-023-06375-2

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