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Digital Geomorphological Information Extraction and Spatial Pattern Analysisin Shanxi Province

Author: LinSong
Tutor: QiaoYuLiangï¼›ChengWeiMing
School: Taiyuan University of Technology
Course: Cartography and Geographic Information Engineering
Keywords: Digital landform Classification System Information Extraction Pattern Analysis Shanxi landforms
CLC: P931
Type: Master's thesis
Year: 2009
Downloads: 79
Quote: 0
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Abstract


Landscape elements is one of the most important elements in the earth surface system, it directly affects other ecological and environmental factors and even determine the distribution and variation, and thus become the core and foundation of the study of geography one. The paper selected as a demonstration area in Shanxi Province, of digital landform feature extraction and spatial analysis, to provide a basis for national geomorphological research. Geomorphic units across the Loess Plateau, the Taihang Mountains and the Ordos Plateau in Shanxi Province, which loess widespread, cutting strong ground erosion, loss of a large number of water and soil resources, and geomorphological processes are frequent disasters, industrial and agricultural construction and people's lives and safety hazards therefore study the geomorphic position for effective implementation of soil and water conservation, ecological restoration, and environmental construction and so has important guiding significance for the implementation of the sustainable development of economy and society, with far-reaching strategic significance. First, on the basis of summing up the results of previous studies, was constructed to adapt to the current medium scale mapping and reflect Shanxi geomorphic characteristics of digital landform classification system. Background conditions, the classification system on a basis consistent with the the geomorphologic classification system of the country 1:1000000 full account of regional landforms morphology causes different levels of the classification scheme and propose appropriate coding system. Then presented based on SRTM-DEM and remote sensing plain - mountains automatic / semi-automatic extraction method. SRTM-DEM and remote sensing image data source SRTM-DEM derived slope model, slope grading method is a reasonable choice, and connectivity analysis and slope area threshold setting clastoporphyritic processing to achieve the plains the mountain preliminary automatically extract; into the expert knowledge on this basis, the integrated use of multi-thematic area of ??vegetation, soil, hydrology, geology, and other elements of information and cartographic knowledge to improve the accuracy of expert correction. The final will be computer-based automatic extraction of information and knowledge experts amendment combined with the initial realization of SRTM-DEM and Remote Sensing, plains, mountains automatic semi-automatic extraction of. The extraction result of the method can be more accurate with the improvement of accuracy of the data source and having a certain degree of scalability. Finally, based on the theory of geographic graphic information geoscience information map theory, combined with the use of mathematical statistics, index analysis and geographic information systems methods such as a detailed analysis of the Shanxi Province at different scales, different types of landforms pattern characteristics, and analysis of digital landform Shanxi Province, the land use status. Mathematical statistical analysis of quantitative geomorphological map plaques and landform type in landscape pattern of Shanxi Province, on the one hand, on the other hand, the combination of space and configuration of the landform types abstract, general mining its inherent laws.

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CLC: > Astronomy,Earth Sciences > Physical Geography > Department of Physical Geography > Geomorphology ( topography )
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