MODELING LAND DEGRADATION USING REMOTE SENSING DATA: THE CASE OF SEYHAN BASIN

Land degradation is a global barrier to ecological, economic and sustainable developments. Climate change, natural disasters, human activities may result changes in soil organic carbon content, land productivity and land use/cover. Climate change is accelerating and expanding these degraded areas. If land destruction is not minimized, cause increasing population, inappropriate land use, climate change and rapid depletion of natural resources etc. in the coming years. It is estimated that land degradation and desertification will be the most important environmental problems. Mapping of land degradation using remote sensing techniques; determining sensitive areas for land degradation and taking protection measures; sustainable management of natural resources, ensuring sustainable agricultural production, etc. are the key factors. This study was conducted in the Seyhan basin, which is suffer from soil loss processes, changes in land cover and land use. These indicators are; trends in land productivity dynamics, land cover change and change of soil organic carbon stocks. The data set utilized to reveal the land degradation was including; 1 km resolution Land Productivity from JRC GLOBAL (1999–2013) and 250 m resolution NDVI from MOD13Q1 (2000–2015), Land Cover ESA CCI's with 300 m resolution LC (2000–2015), SOC stock from LUCAS (JRC) with 250 m resolution, 2000–2018 data from CORINE. The land degradation of the Seyhan basin was mapped using the specified land degradation indicators together with the One Out All Out (1OAO) rule.