Remote Sensing Remote Sensing-Based Soil Erosion Rate Estimation Using the E30 Model and Sentinel-2 Imagery - Badaruddin; Ali, Syamani D. (Foresty Faculty of Hasanuddin University, 2025)
Estimating the rate of soil erosion generally takes time, money, and energy. There are many parameters that must be accommodated, such as the physical properties of the soil, land cover, rainfall, topography, and so on. One alternative method for estimating erosion rates is to use a remote sensing approach. The aim of this research is to estimate the rate of soil erosion in the Special Purpose Forest Area of the University of Lambung Mangkurat (KHDTK ULM) Mandiangin, using the E30 model and Sentinel-2 imagery. The erosion rate are measured directly in the field with a number of sample points. According to the E30 model concept, field erosion samples are only measured on land that has a slope of 300. The topographic data itself is extracted from DEMNAS data. Meanwhile, soil bulk density data was obtained from https://soilgrids.org/, and solum data was taken from https://daac.ornl.gov/. From the Sentinel-2 imagery, Normalized Difference Vegetation Index (NDVI) data was extracted, which is one of the parameters in the E30 model. The estimated results of the erosion rate at KHDTK ULM Mandiangin show that, in general, the highest erosion rate at KHDTK ULM Mandiangin is around 480 tons/ha/year. Additionally, almost 80% of the KHDTK ULM Mandiangin area has a very serious erosion hazard level. Of course, the fastest rate of erosion is located on hill slopes with steep topography. Apart from having steep topography, one of the factors causing the high rate of erosion at KHDTK ULM is the thin soil layer and the lack of dense forest cover. This finding indicates the need to conserve vegetation cover on steep lands.