Paper
28 October 2006 Analyses and simulation to spatial pattern of land utilization in Guangzhu City
Xin-chang Zhang, Wen-jiang Zhang, Kun Ma
Author Affiliations +
Proceedings Volume 6418, Geoinformatics 2006: GNSS and Integrated Geospatial Applications; 64181T (2006) https://doi.org/10.1117/12.713225
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China
Abstract
Based on Landsat TM remote sensing images in 1990 and 2000, we analyses the temporal and spatial pattern Characters of land use in the 1990s in Guangzhou city. We also simulate the scenarios of land-use pattern in 2010 by integrating the Markov process into cellular automata model. The results show that the area of constructions was rapid increasing during the last ten years of the 20th century, at the same time the arable land, woodland and unused land areas were decreasing, the orchard and water areas were rarely changed; In the first ten years of 21st century, land use pattern keep the change trend in the 1990s, land of constructions continue rapid increasing; arable land and unused land areas continue rapid decreasing; woodland, orchard and water areas keep steadily. Research shows that the extent of urban area has increased exponentially in Guangzhou city, no evidences show that the arable land decreasing rate will slow down in the near future. So, it is necessary to enhance the control functions of land use planning and take actives measures to protect arable land.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xin-chang Zhang, Wen-jiang Zhang, and Kun Ma "Analyses and simulation to spatial pattern of land utilization in Guangzhu City", Proc. SPIE 6418, Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 64181T (28 October 2006); https://doi.org/10.1117/12.713225
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Geographic information systems

Remote sensing

Data modeling

RGB color model

Earth observing sensors

Landsat

Process modeling

Back to Top