Relationship between Tree Density and Vegetation Index of Juniper Forest in the Northeast of Iran

摘要

It is generally agreed that there is a relationship between productivity and biodiversity, and productivity can be measured by remote sensing, so it should be possible to use remote sensing for monitoring biodiversity. Objects of this study; estimating tree density per hectare, calculation of other vegetation indices, introduction of new vegetation indices and finding the best relationship between tree density and vegetation indices. For this study ALOS, multispectral (AVNIR-2) and Panchromatic (PRISM) data have been analyzed. In this paper, the new indices TRVI, TRSAVI and TRVI_4 have been presented for estimating vegetation in arid and semi-arid forests with R~2=0.88, R~2=0.78 and R~2=0.41 with CV%=10.65, 20.98 and 5.92 respectively. Versus NDVI, SAVI and OSAVI R~2=0.79, 0.79, 0.87, CV%=19.22, 19.27, 19.22 respectively. The NDVI vegetation index is able to distinguish between grassland and shadows, but was not able to identify between trees and high-density grassland. TRVI was the best index to distinguish between trees and high-density grassland. TRVI4 has a very weak ability in discerning between high-density grassland, medium vegetation, areas of no vegetation, trees and shadows. We have found a good index possible for calculating Vegetation Indices (VIs) in arid and semi-arid regions, so hope that it will be the best option for better decision-making in natural resource management and environmental studies.