A comparison and evaluation of four vegetation analysis approaches based on remote sensing imagery

Abstract

Some analytical approaches have been developed and widely used for vegetation remote sensing, among which four popular methods are vegetation analysis via NDVI and other VIs, vegetation analysis using the vegetation abundance derived from unmixing, vegetation analysis by land cover classification, and the greenness component derived from K-T transform. There four approaches are used to extract vegetation information from Landsat TM image taking Xuzhou City as an example, and their performance is compared. Association analysis among vegetation types, NDVI values, vegetation abundance and greenness is conducted at first. It is found that the association among NDVI, vegetation abundance and greenness is quite obvious. Vegetation coverage ratio is derived based on different vegetation extraction approaches, and their consistency is analyzed. It is found that the unmixing-based approach outperforms others in terms of vegetation coverage ration estimation. By comparing the performance and effectiveness of four approaches, some suggestions are given for selecting suitable analytical approaches.