title: [NDVI difference rate recognition model of deciduous broad-leaved forest based on HJ-CCD remote sensing data].
abstract: 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.
authors.affiliation: International Institute for Earth System Science, Nanjing University, Nanjing 210023, China. wangyan_woshiwang@163.com
authors.forename: Yan
authors.initials: Y
authors.lastname: Wang
authors.forename: Qing-Jiu
authors.initials: QJ
authors.lastname: Tian
authors.forename: Yan
authors.initials: Y
authors.lastname: Huang
authors.forename: Hong-Wei
authors.initials: HW
authors.lastname: Wei
mesh_terms: D017753:Ecosystem; D008962:Models, Theoretical; D010788:Photosynthesis; D018515:Plant Leaves / Q000378:metabolism*; D058998:Remote Sensing Technology / Q000379:methods; D013057:Spectrum Analysis / Q000379:methods*; D014197:Trees / Q000254:growth & development / Q000378:metabolism*