10 July 2009 Ecological landscape classification and dynamic change mapping in the Taoer River basin, Northeast China
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Proceedings Volume 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering; 749111 (2009) https://doi.org/10.1117/12.836691
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
Ecological landscape classification (ELC) plays a significant role in sustainable planning and management of natural resources from large scales to fine scales, because it provides an understanding of ecosystem with a holistic concept by linking biotic and abiotic factors together. In this research, Taoer River basin of Northeast China was taken as a typical study area, for its present situation of environment is imperiling the regional sustainable development, with rapid salinization expansion in midstream and downstream especially. A hierarchical system with four levels of landscape ecoregion, landscape ecocatena, landscape ecosection and landscape ecotope was adopted, and the components of ecosystem used to delineate ecounits of each level include climate normals and hydrological data across nearly 50 years, lithology data in 1:500000 scale, soil data in 1:1000000 scale, topographic factors and landform data from SRTM DEM in 90m resolution, and vegetation and land use and land cover data from Landsat remotely sensed images of 1976 and 2000 by interactive interpretation method. Through spatial overlay and geographical relationship analysis methods with the support of GIS technique, each specific level of details was presented with a series of maps. And based on the dynamic factors, mainly referring to climate and land use and land cover, the dynamic change maps from 1976 to 2000 were produced to analyze the environmental evolutive process.
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Jiuchun Yang, Jiuchun Yang, Shuwen Zhang, Shuwen Zhang, } "Ecological landscape classification and dynamic change mapping in the Taoer River basin, Northeast China", Proc. SPIE 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering, 749111 (10 July 2009); doi: 10.1117/12.836691; https://doi.org/10.1117/12.836691
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