AUTOMATIC DEFORESTATION DETECTION USING TIME SERIES LANDSAT IMAGES IN A TROPICAL FOREST OF CHINA

被引：3
|
作者：
Pang Yong [1 ]
Zhang Lianhua [1 ,2 ]
Huang Chengquan [3 ]
Yu Xinfang [4 ]
Li Zengyuan [1 ]
机构：
[1] CAF, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China
[2] Guangxi Forest Inventory & Planning Inst, Nanning 530011, Peoples R China
[3] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[4] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
来源：
2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年
基金：
国家高技术研究发展计划(863计划);
关键词：
Tropical forest; deforestation; time series Landsat image; integrated forest index; disturbance index;
D O I：
10.1109/IGARSS.2013.6723677
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we compared two versions of the Vegetation Change Tracker (VCT) algorithm, one based on the Integrated Forest Index (IFI) and the other on Disturbance index (DI) derived using the tasseled cap transformation. Time series Landsat ETM+ data from 1999 to 2010 were used in a tropical site of Xishuangbanna, Yunnan province of China. The results were evaluated using 376 field plots. The accuracies of IFI-VCT and DI-VCT are 82.7% and 79.9%, respectively. These two algorithms had different performances in different areas. The DI enhanced the separability between some tall agriculture and forest. Haze and seasonality affect DI result more than IFI.
引用
收藏
页码：3872 / 3875
页数：4
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