Estimation of soil erosion for a sustainable land use planning: RUSLE model validation by remote sensing data utilization in the Kalikonto watershed - Andriyanto, C; Sudarto, S; Suprayogo, D (Journal of Degraded and Mining Lands Management, 2015)
Technology of Geographic Information Systems (GIS) and Remote Sensing (RS) are increasingly used for planning and natural resources management. GIS and RS is based on pixels is used as a tool of spatial modeling for predicting the erosion. One of the methods developed for predicting the erosion is a Revised Universal Soil Loss Equation (RUSLE). RUSLE is the method used for predicting the erosion associated with runoff gained from five parameters, namely: rain erosivity (R), soil erodibility (K), length of slopes (L), slope (S), and land management (CP). The main constraint encountered in the process of operating the GIS is the calculation of the slope length factor (L).This study was designed to create a plan of sustainable land use and low erosion through the RULSE erosion modeling by utilizing the remote sensing data. With this approach, this study was divided into three activities, namely (1) the preparation and analysis of spatial data for the determination of the parameters and estimating the erosion by using RUSLE models, (2) the validation and calibration of the model of RUSLE by measuring soil erosion at the scale of plots on the field, and (3) Creating a plan of sustainable land use and low erosion with RUSLE. The validation erosion shows the value of R2 = 0.56 and r = 0.74. Results of this study showed that the RUSLE model could be used in the Kalikonto watershed. The erosions at the value of the actual estimation, spatial Plan (RTRW) and land capability class in the Kalikonto watershed were 72t / ha / year, 62 t / ha / year and 58 t / ha / year, respectively