Details

Autor(en) / Beteiligte

• Elhag, Mohamed
• Boteva, Silevna
• Al-Amri, Nassir

Titel

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

Ist Teil von

• Open Geosciences, 2021-03, Vol.13 (1), p.345-358

Ort / Verlag

Warsaw: De Gruyter

Erscheinungsjahr

2021

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

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