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Application of ASTER Data for Land-Use Classification in Coastal Area of East Shenzhen

TIAN Bo1, ZHOU Yun-xuan1, 2, JIANG Yun-an3, HOU Chang-mou4   

  1. 1.State Key Laboratory of Estuarine & Coastal, East-China Normal University, Shanghai 200062, China;2.College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;3.Middle Southern Institute of Forestry Inventory, Planning and Design, SFA, Changsha 410014, China;4.Guangdong Province Forestry Department, Guangzhou 510173, China
  • Received:2007-03-27 Revised:1900-01-01 Online:2008-01-26 Published:2008-01-26
  • Contact: TIAN Bo

Abstract: Based on radiometric and geometrical correction of ASTER imagery data, the land-use classification of coastal area in the east of Shenzhen were investigated in this study. The sample sites were established through field investigation and vectorization. The reflectance map of each ASTER band and the overlay map of 12 classes of land-use type between bands were derived from the sample sites vector data. Also vegetation index and PCA of the five SWIR bands were mapped and analyzed. With a GIS tool, the study area was classified using knowledge-based decision-tree, which contains information from single ASTER bands, SWIR PCA1, vegetation index, and terrain parameters derived from ASTER stereo-pairs. The classification was validated with an accuracy of 85.1% and the case study showed that the ASTER imagery data can be used in land resource investigation with a low cost and acceptable accuracy.

Key words: ASTER imagery data, landuse, reflectance overlay map, remotely sensed classification, vegetation index

CLC Number: 

  • F301.2
[1] Zhou Linfei, Chen Qixin, Cheng Qian, Zhang Jing. Remote Sensing Classification Information Extraction Based on Rough Set Theory [J]. Journal of Jilin University(Earth Science Edition), 2015, 45(4): 1246-1256.
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