Remote Sensing Monitoring of Vegetation Coverage in Southern China Based on Pixel Unmixing: A Case Study of Guangzhou City
ZHANG Zhi-xin1, DENG Ru-ru1, LI Hao1, CHEN Lei1,2, CHEN Qi-dong1, HE Ying-qing1
1. School of Geographic Science and Planning, Sun Yat-sen University, Guangzhou 510275, China;
2. South China Sea Marine Engineering and Environment Institute, SOA, Guangzhou 510300, China
Based on the measurement of the ground spectral reflectance of basal land covers and the accurate atmospheric correction for Landsat TM data,the authors improved the linear spectral mixture model (LSU)and developed a vegetation coverage retrieval model suitable for southern China. The effects of the atmospheric environment and the imaging time of remote sensing data were both reduced,contributing to the multi-temporal comparison,by the utilization of the ground spectral reflectance from field survey. The soil moisture factor was considered to eliminate its remarkable spatial differentiation error in southern China. The vegetation coverage retrieval model was proved to be efficient with high precision over the in situ field verification and was applied to extract the vegetation coverage information in Guangzhou from 1998 to 2009. It is inferred that the urbanization, the large-scale architectural engineering and the reclamation activities constitute the main factors responsible for the formation of the spatio-temporal vegetation change in this area.
张志新, 邓孺孺, 李灏, 陈蕾, 陈启东, 何颖清.  ̄基于混合像元分解的南方地区植被覆盖度遥感监测——以广州市为例[J]. 国土资源遥感, 2011, 23(3): 88-94.
ZHANG Zhi-xin, DENG Ru-ru, LI Hao, CHEN Lei, CHEN Qi-dong, HE Ying-qing. Remote Sensing Monitoring of Vegetation Coverage in Southern China Based on Pixel Unmixing: A Case Study of Guangzhou City. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(3): 88-94.
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