Forest cover assessment using remote-sensing techniques in Crete Island, Greece

Abstract Remote-sensing satellite images provided rapid and continuous spectral spatial information of the land surface in Sougia River catchment by identifying major changes that have taken place over 20 years (1995–2015). Vegetation indices (VIs) normalized difference vegetation index (NDVI), enhanced (EVI) leaf area were derived for monitoring mapping variations cover. The quantified decrease NDVI was found to be 4% between 1995 2005, further decreased 77.1% 2005 2015; it declined back almost initial status 1995. EVI results inconsistent suggesting seasonal crops influence temporal distribution VIs important input parameters modelling management catchment’s hydrological behaviour. Image classification 4- 6-class classifications unstable produced, respectively, a 13.8% 16.2% total change classes. Meanwhile, 8-, 10- 12-class showed an horizontal line with minor fluctuation less than 0.05%. post-classification detection analysis indicated degradation terms natural losses sparser or even no