Spatial-temporal evolution of environment along the Ming Great Wall in Ningxia and Shaanxi Provinces based on multi-resource remote sensing data

Lanwei Zhu; Huadong Guo; Changlin Wang

doi:10.1117/12.748566

14 November 2007 Spatial-temporal evolution of environment along the Ming Great Wall in Ningxia and Shaanxi Provinces based on multi-resource remote sensing data

Lanwei Zhu, Huadong Guo, Changlin Wang

Author Affiliations +

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 679017 (2007) https://doi.org/10.1117/12.748566
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

The Great Wall segments in Ningxia and Shaanxi Provinces, built in Ming dynasty, actually lies in several transition zones, such as agriculture and pasture land, semi-humid and semi-arid zone, monsoon area and non-monsoon area and so on. As a result, the ecological environment around the Great Wall is very sensitive and fragile, and is easily to be destroyed. So in this paper, we used a new technical route to analyze the environmental change around this part of the Great Wall and meanwhile put forward some measures to protect its environment. To describe the spatial-temporal pattern of environment along the Ming Great Wall, we choose some indices to analyze its change, such as the vegetation, soil, moisture and so on [1]. All of them are retrieved from multi-temporal and multi-source remote sensing images. By comparing above parameters, we draw the conclusion that is the environment along the Ming Great Wall is becoming worse and worse.

Citation Download Citation

Lanwei Zhu, Huadong Guo, and Changlin Wang "Spatial-temporal evolution of environment along the Ming Great Wall in Ningxia and Shaanxi Provinces based on multi-resource remote sensing data", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679017 (14 November 2007); https://doi.org/10.1117/12.748566

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KEYWORDS

Vegetation

Earth observing sensors

Landsat

Environmental sensing

Remote sensing

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Agriculture

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