A comparison of multi-resource remote sensing data for vegetation indices

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Cao, Liqin^1 ; Liu, Tingting^2 ; Wei, Lifei^1

School of Printing and Packaging, Wuhan University, Wuhan, China^1

Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, China^2

关键词: Coefficient of determination;    Normalized difference vegetation index;    Observation systems;    Quantitative remote sensing;    Remote sensing data;    Retrieval algorithms;    Strong correlation;    Universal patterns;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012067/pdf
DOI  :  10.1088/1755-1315/17/1/012067

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

With the development of the satellite sensor, multi-resource observation systems have become widely used. However, there is a huge difference between quantitative remote sensing products because of the different sensing observations and the quantitative retrieval algorithms. In this paper, the quantitative relationships between the normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) and the vegetation index based on the universal pattern decomposition method (VIUPD) of Landsat ETM+ and ASTER sensors are investigated. The difference in observations was examined between the two sensors, based on a pair of images. The results showed that: 1) There was a strong correlation between the different vegetation indices for the same sensor, with the coefficient of determination being greater than 0.9. 2) Whether for ASTER or Landsat, the information of VIUPD was richer than that of NDVI and SAVI. Furthermore, in dense vegetation areas, the values of NDVI and SAVI could easily reach saturation. 3) The values of SAVI were higher than NDVI in the areas of water or bare soil, while this was the opposite in areas of lush vegetation.