Remote sensing and GIS methode for assess erosion with satellite imagery at Citarik Sub-Watershed

Abstract

Soil erosion represents one of the most severe land degradation problems, starting from the decrease in the level of productivity of the land to natural disasters that cause material casualties and losses. Assessment of erosion through remote sensing methods and GIS can assist in the provision of erosion data, which can later be integrated with the database so that it can present in an update. Landsat 8 satellite image obtained from the USGS data. The satellite image data analysis to obtain data NDVI vegetation canopy density, also performed with the interpretation that with supervised classification using Likelihood method to obtain the land use data. Then Landuse data tested the level of accuracy. The results showed that Landsat 8 could determine land use with accuracy 92,67% with approach Supervised Classification by Maximum Likelihood method, the results of interpretation produces seven classes of land use, land use fields dominating with an area of 114.01 hectares or 88.80% of the total area, while land use at least is a primary forest with an area of only 0.36 hectares or 0.28%, NDVI analysis shows that density of vegetation was dominated by areas of research. The land-use who potential to be degradation is farm/field