Evaluation of Two Vegetation Indices (NDVI and VCI) Over Asi Basin in Turkey

Authors : Mehmet DİKİCİ, Murat AKSEL

Pages : 10995-11011

Doi:10.18400/tekderg.590356

View : 8 | Download : 2

Publication Date : 2021-07-01

Article Type : Research Paper

Abstract :Climate change and global warming are among the issues that humanity is most concerned about the future. The growing drought and flood risks that increase despite the taken measures have led to the adoption of an integrated understanding on the topic of water management in recent years. To manage the increased risk of drought and to make sustainable planning, the dimensions of drought should be known first. For this purpose, many drought indices have been developed. The Normalized Difference Vegetation Index insert ignore into journalissuearticles values(NDVI); and Vegetation Condition Index insert ignore into journalissuearticles values(VCI);, which determined by remote sensing, are two of these. In this study, in which the agricultural drought was analyzed with vegetation indices by taking into consideration the historical drought archive, the Asi Basin was addressed. The data of the Asi Basin, which covers an area of 7800 km2 and was obtained from the Moderate Resolution Imaging Spectroradiometer insert ignore into journalissuearticles values(MODIS); and Advanced Very High-Resolution Radiometer insert ignore into journalissuearticles values(AVHRR); satellites, was used in this study. With the satellites benefited in remote sensing and with the Coordination of Information on the Environment insert ignore into journalissuearticles values(CORINE);, where the layers of vegetation were determined, agricultural and forest areas were evaluated separately. The vegetation indices, which change with the increase in temperature, have revealed the necessity of a long-term drought management for the Asi Basin. Result of the work pointed that NDVI index is more appropriated to the Asi Basin than the VCI index to monitor drought.
Keywords : Remote sensing, drought index, NDVI, VCI