Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

作者:Li, XK (Li, Xueke)[ 1 ] ; Wu, TX (Wu, Taixia)[ 2 ] ; Liu, K (Liu, Kai)[ 3,4 ] ; Li, Y (Li, Yao)[ 2,4 ] ; Zhang, LF (Zhang, Lifu)[ 2 ]

REMOTE SENSING

卷: 8  期: 5

文献号: 438

DOI: 10.3390/rs8050438

出版年: MAY 2016

摘要

The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1) opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, China, by comparing the TG-1 (with a spatial resolution of 10 m) to EO-1 Hyperion (with a spatial resolution of 30 m). The spectral feature of TG-1 was first analyzed and, thus, finding out optimal hyperspectral wavebands useful for the discrimination of urban areas. Based on this, the pixel-based maximum likelihood classifier (PMLC), pixel-based support vector machine (PSVM), hybrid maximum likelihood classifier (HMLC), and hybrid support vector machine (HSVM) were implemented, as well as compared in the application of mapping urban land cover types. The hybrid classifier approach, which integrates the pixel-based classifier and the object-based segmentation approach, was demonstrated as an effective alternative to the conventional pixel-based classifiers for processing the satellite hyperspectral data, especially the fine spatial resolution data. For TG-1 imagery, the pixel-based urban classification was obtained with an average overall accuracy of 89.1%, whereas the hybrid urban classification was obtained with an average overall accuracy of 91.8%. For Hyperion imagery, the pixel-based urban classification was obtained with an average overall accuracy of 85.9%, whereas the hybrid urban classification was obtained with an average overall accuracy of 86.7%. Overall, it can be concluded that the fine spatial resolution satellite hyperspectral data TG-1 is promising in delineating complex urban scenes, especially when using an appropriate classifier, such as the hybrid classifier.

通讯作者地址: Wu, TX (通讯作者)

Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China.

通讯作者地址: Liu, K (通讯作者)

Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources, Beijing 100101, Peoples R China.

通讯作者地址: Liu, K (通讯作者)

Univ Chinese Acad Sci, Beijing 100094, Peoples R China.

地址:

[ 1 ] Univ Connecticut, Dept Geog, Storrs, CT 06269 USA

[ 2 ] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China

[ 3 ] Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources, Beijing 100101, Peoples R China

[ 4 ] Univ Chinese Acad Sci, Beijing 100094, Peoples R China