A spectral index for highlighting  forest cover from remotely sensed imagery

Wentao Ye; Xi Li; Xiaoling Chen; Guo Zhang

doi:10.1117/12.2068775

8 November 2014 A spectral index for highlighting forest cover from remotely sensed imagery

Wentao Ye, Xi Li, Xiaoling Chen, Guo Zhang

Proceedings Volume 9260, Land Surface Remote Sensing II; 92601L (2014) https://doi.org/10.1117/12.2068775
Event: SPIE Asia-Pacific Remote Sensing, 2014, Beijing, China

Abstract

Forest cover maps are essential for current researches of biomass estimation and global change, but traditional methods to derive forest maps are complex. These methods usually need training samples or other ancillary data as input, and are time- and labor- consuming for large scale applications. To make the process of forest cover mapping simple and rapid, in this paper, a simple spectral index called forest index (FI) was proposed to highlight forest land cover in Landsat scenes. The FI is derived from three bands, green, red and near-infrared (NIR) bands and an FI image can be classified into forest/non-forest map with a threshold. The overall accuracies of classification maps in the two study areas were 97.8% and 96.2%, respectively, which indicates that the FI is efficient at highlighting forest cover.

Citation Download Citation

Wentao Ye, Xi Li, Xiaoling Chen, and Guo Zhang "A spectral index for highlighting forest cover from remotely sensed imagery", Proc. SPIE 9260, Land Surface Remote Sensing II, 92601L (8 November 2014); https://doi.org/10.1117/12.2068775

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