Paper
22 October 2004 Developing Land Use/Cover Classification System Based on Remote Sensing Data in China
Jing Wang, Ting He, Qing Zhou, Xudong Guo
Author Affiliations +
Abstract
A land use/cover classification system is important for land resource management and it is one of the key research issues in Land Use /Cover Change (LUCC) and land change science research. Lots of work has been done in this area, however, a universally-accepted classification system has not been available yet. This paper proposed several guidelines for building a land use/ cover classification system, which encompasses the basic concept of land use and land cover. Then a preliminary framework for Chinese land use/cover classification system at different scale based on remote sensing data was detailed. The framework is made up of four scales, including national scale, regional scale, county scale and country scale. The classes of first level at national scale in the system are agriculture land, woodland, natural grassland, built-up land, water, wetland and barren land. The regional scale includes 27 classes of land use/cover and the county scale includes 43 types. The general diagnostic criterion of the first level of classification system is the situation of existing vegetation, soil and water, artificial and natural surface. Monitoring on land resource in Beijing-around area as an example, this paper introduce the respects need to be paid attention of this classification system. Because of the complexity and difficulty of this question itself, this system was based on synthesis of relevant research achievement; its actual feasibility still remains to be verified.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jing Wang, Ting He, Qing Zhou, and Xudong Guo "Developing Land Use/Cover Classification System Based on Remote Sensing Data in China", Proc. SPIE 5574, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IV, (22 October 2004); https://doi.org/10.1117/12.567770
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KEYWORDS
Classification systems

Remote sensing

Vegetation

Agriculture

Spatial resolution

Diagnostics

Mining

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