Temporal and spatial changes analysis of arable land in Zhongshan city based on GIS and RS

Yuan Fang

doi:10.1117/12.836381

10 July 2009 Temporal and spatial changes analysis of arable land in Zhongshan city based on GIS and RS

Yuan Fang

Proceedings Volume 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering; 74910B (2009) https://doi.org/10.1117/12.836381
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China

Abstract

Land use change is the most significant aspect in the research field of globe changing. Affected by both of natural and artificial factors, the land use and land resources quality varied continually. Zhongshan City where the zone has a typical feature of land use change and significant ecological effects is selected as a case. Applying the satellite images of Landsat-TM and the integrating techniques of RS and GIS, this paper analyzed the temporal and spatial processes and the spatial conversion of arable land in Zhongshan City from 1988 to 2002. The classified results of multi-temporal TM remote sensing image data and transfer matrix of land use show that land use has been changed significantly from 1988 to 2002 in Zhongshan City. Various types of land use converted frequent, which mainly reflects in the waters, the cultivated land loss and construction land increase. After 1995 land use degree of the study area grows slower, which shows Zhongshan City emphasized the overall development after the rapid expansion. The arable land area reduces rapidly and experienced rapid change under the pressure of urban expansion. It is the main period about the arable land to reduce from 1988 to 1995. More than 70 percent of arable land is converted to construction sites. Other types of lands also are converted to the arable land, which waters and the forest land were the major types.

Citation Download Citation

Yuan Fang "Temporal and spatial changes analysis of arable land in Zhongshan city based on GIS and RS", Proc. SPIE 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering, 74910B (10 July 2009); https://doi.org/10.1117/12.836381

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KEYWORDS

Remote sensing

Geographic information systems

Image classification

Earth observing sensors

Accuracy assessment

Image processing

Landsat

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