Comparing NDVI and RVI for forest density estimation and their relationships with rainfall (Case study: Malekshahi, Ilam Province)

Changes in rainfall have significant effects on vegetation of an area, especially in arid and semi-arid regions. Nowadays, the vegetation can be assessed using indices derived from satellite imagery and remote-sensing techniques. The aim of this study was to evaluate the effect of rainfall on vegetation and to compare NDVI and RVI indices. The study area is Malekshahi, a city with an area of 1165 km2, located in the northeast of Ilam Province. The statistical data of 10 rain gauge stations in the region were used to investigate the rainfall fluctuations during the years 2000 and 2014. ETM images of Landsat satellite were used for the years 2000, 2007 and 2013. To evaluate the vegetation, NDVI and RVI were assessed using ENVI 4.7 software. The results showed that the highest and lowest rainfalls were 600 and 211 mm in 2000 and 2014, respectively. Comparison of the two vegetation indices showed that the NDVI index with the overall accuracy of above 70% has the highest capacity to separate the semi-dense forests from the dense ones. However, the RVI index showed a greater efficiency to separate the thin forests. The NDVI index had the highest correlation with precipitation compared to RVI index. Thus, NDVI is an appropriate parameter to assess the changing process of precipitation in the study area.