Quantitative evaluation of regional vegetation ecological environment quality by using remotely sensed data over Qingjiang, Hubei

Cheng Wang; Yan Sun; Lijun Li; Qiuwen Zhang

doi:10.1117/12.775247

10 November 2007 Quantitative evaluation of regional vegetation ecological environment quality by using remotely sensed data over Qingjiang, Hubei

Cheng Wang, Yan Sun, Lijun Li, Qiuwen Zhang

Author Affiliations +

Proceedings Volume 6795, Second International Conference on Space Information Technology; 67956W (2007) https://doi.org/10.1117/12.775247
Event: Second International Conference on Spatial Information Technology, 2007, Wuhan, China

Abstract

Vegetation cover is an important component and the best indication to the region ecological environment. The paper adopts a new method of integrating remote sensing technology and composite index appraisal model based multiple linear regression for quantitatively evaluating the regional vegetation ecological environment quality(VEEQ). This method is different to the traditional ecological environment research methods. It fully utilizes the advantages of quantitatively remote sensing technology, directly extracts the key influencing factors of VEEQ, such as vegetation indices (RVI, NDVI, ARVI, TMG), humidity indices(NDMI, MI, TMW), soil and landform indices(NDSI, TMB, GRABS) as the evaluating parameters from data the Landsat 5/TM remotely sensed images, and then puts these factors mentioned above into the multiple linear regression evaluating model. Ultimately we obtain the VEEQ evaluation rank figure of the experimental field-part of Qingjiang region. The handy multiple linear regression model, is proved to be well fit the experimental field for the vegetation ecological environment evaluation research.

Citation Download Citation

Cheng Wang, Yan Sun, Lijun Li, and Qiuwen Zhang "Quantitative evaluation of regional vegetation ecological environment quality by using remotely sensed data over Qingjiang, Hubei", Proc. SPIE 6795, Second International Conference on Space Information Technology, 67956W (10 November 2007); https://doi.org/10.1117/12.775247

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