Application of statistics to detection of green resources changes at Yangmingshan area using remote sensing imagery

Shu-Ping Teng 1, Ke-Sheng Cheng 2, Hann-Chung Lo 1 and Yeong-Kuan Chen 3
1 School of Forestry and Resource Conservation, National Taiwan University
No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
Tel.: + 886 233664624; Fax: +886 223654520
d90625004@ntu.edu.tw; hclo@ntu.edu.tw
2 Department of Bioenvironmental Systems Engineering, National Taiwan University
No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
Tel.: + 886 233663465; Fax: +886 223635854
rslab@ntu.edu.tw
3 Department of Leisure & Recreation Management, TOKO University
No.51, Sec. 2, University Road, Pu-Tzu City, Chia-Yi County, 613  Taiwan 
Tel.: + 886 233664624; Fax: +886 23366
ykchen@ntu.edu.tw

Abstract
Change detection is one of the most important remote sensing applications for environmental monitoring. Green resources investigation is essential for the sustainable development of natural resources. In this study, change detection of green  resources in the Yangmingshan area near Taipei was conducted using multi-temporal remote sensing images. The process of change detection in this study is composed of several steps. Firstly, preprocessing of satellite images including geometric and atmospheric  corrections was conducted. Supervised landcover classification using maximum likelihood method was then applied to extract unchanged vegetation pixels. A bivariate normal distribution for NDVI of unchanged vegetation pixels was then established and used to construct the critical region of change detection. At 5% level of significance, the proposed approach detected approximately 8.47% of green resources changes within a period of 15 years (1986 to 2001).

Keywords: change detection, remote sensing, geometric correction, statistics

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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