Hyperspectral remote sensing of vegetation growing condition and regional environment

Abstract

A growing nμmber of studies in recent years have focused on how to use remote sensing for dynamic monitoring and effective evaluation of vegetation conditions and vegetation growing environment in mining areas, which will provide a scientific basis for making policies for controlling the environment in mining areas. In this paper, airborne hypersectral remote sensing data — HyMap images in the Mount Lyell mining area of Australia and Hyperion images in Dexing copper mining area of China were used. Analyses based on the biogeochemical effect of vegetation and living creatures in the mining area and the vegetation spectrμm and vegetation indices, two vegetation indices: Vegetation Inferiority Index (VII) and Water Absorption Decorrelative Index (WDI) have been used and developed. Experimental results show that VII can effectively reveal the vegetation growth conditions and growing environment in the mining area. The sensitivity of VII is shown to be superior to the traditional vegetation index — NDVI. This has also been verified by the application of Hyperion image-derived VII in Dexing copper mining area. WDI can effectively identify the area that contains hematite, especially the hematite areas that are covered with sparse vegetation. The two proposed indices are effective indicators for ecological environmental monitoring in mining areas.