Extraction of land cover change information from ENVISAT-ASAR data in Chengdu Plain

Wenbo Xu; Jinlong Fan; Jianxi Huang; Yichen Tian; Yong Zhang

doi:10.1117/12.712611

28 October 2006 Extraction of land cover change information from ENVISAT-ASAR data in Chengdu Plain

Wenbo Xu, Jinlong Fan, Jianxi Huang, Yichen Tian, Yong Zhang

Proceedings Volume 6419, Geoinformatics 2006: Remotely Sensed Data and Information; 641905 (2006) https://doi.org/10.1117/12.712611
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China

Abstract

Land cover data are essential to most global change research objectives, including the assessment of current environmental conditions and the simulation of future environmental scenarios that ultimately lead to public policy development. Chinese Academy of Sciences generated a nationwide land cover database in order to carry out the quantification and spatial characterization of land use/cover changes (LUCC) in 1990s. In order to improve the reliability of the database, we will update the database anytime. But it is difficult to obtain remote sensing data to extract land cover change information in large-scale. It is hard to acquire optical remote sensing data in Chengdu plain, so the objective of this research was to evaluate multitemporal ENVISAT advanced synthetic aperture radar (ASAR) data for extracting land cover change information. Based on the fieldwork and the nationwide 1:100000 land cover database, the paper assesses several land cover changes in Chengdu plain, for example: crop to buildings, forest to buildings, and forest to bare land. The results show that ENVISAT ASAR data have great potential for the applications of extracting land cover change information.

Citation Download Citation

Wenbo Xu, Jinlong Fan, Jianxi Huang, Yichen Tian, and Yong Zhang "Extraction of land cover change information from ENVISAT-ASAR data in Chengdu Plain", Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 641905 (28 October 2006); https://doi.org/10.1117/12.712611

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KEYWORDS

Databases

Data acquisition

Buildings

Remote sensing

Objectives

Classification systems

Environmental sensing

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