Monitoring the severity of degradation and desertification by remote sensing (case study: Hamoun International Wetland)

Monitoring degradation in arid and semi-arid areas is one of the main concerns for governments, given growing trend. Meanwhile, detecting subjected to requiring management shortest time at lowest cost a necessity, especially border such as Hamoun Wetland, located between Iran Afghanistan. Albedo normalized difference vegetation index (NDVI) were calculated using remote sensing technology monitor intensity different periods (August 1999, 2009, 2015, 2020). Change vector analysis brightness greenness indices 1999 2020 was used determine changes intensity. Linear regression run albedo NDVI. Finally, (DI) map developed A confusion matrix created change (CVA) albedo–NDVI model evaluate accuracy obtained from this 1,476 pixels classes. The linear NDVI showed negative correlation (R = ?0.849). results an increase regions with null, low, medium intensity, while expansion observed severe extreme degradation. indicated high (0.705) study area. These about 52.01% 7.07% 2009 56.26% 55.15% 2015 2020. Additionally, average rate 13.11%.