NDVI difference rate recognition model of deciduous broad-leaved forest based on HJ-CCD remote sensing data

The present paper takes Chuzhou in Anhui Province as the research area, and deciduous broad-leaved forest as the research object. Then it constructs the recognition model about deciduous broad-leaved forest was constructed using NDVI difference rate between leaf expansion and flowering and fruit-bea...

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Bibliographic Details
Published inGuang pu xue yu guang pu fen xi Vol. 33; no. 4; p. 1018
Main Authors Wang, Yan, Tian, Qing-Jiu, Huang, Yan, Wei, Hong-Wei
Format Journal Article
LanguageChinese
Published China 01.04.2013
Subjects
Ecosystem
Models, Theoretical
Photosynthesis
Plant Leaves - metabolism
Remote Sensing Technology - methods
Spectrum Analysis - methods
Trees - growth & development
Trees - metabolism
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Summary:The present paper takes Chuzhou in Anhui Province as the research area, and deciduous broad-leaved forest as the research object. Then it constructs the recognition model about deciduous broad-leaved forest was constructed using NDVI difference rate between leaf expansion and flowering and fruit-bearing, and the model was applied to HJ-CCD remote sensing image on April 1, 2012 and May 4, 2012. At last, the spatial distribution map of deciduous broad-leaved forest was extracted effectively, and the results of extraction were verified and evaluated. The result shows the validity of NDVI difference rate extraction method proposed in this paper and also verifies the applicability of using HJ-CCD data for vegetation classification and recognition.
ISSN:1000-0593
DOI:10.3964/j.issn.1000-0593(2013)04-1018-05