REMOTE SENSING DETECTION AND IMPACT ANALYSIS OF TIBETAN HUMAN LANDSCAPE IN JIUZHAIGOU

Autor: J. Ma, D. R. Li, M. E. Huq, Q. M. Cheng
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W10, Pp 629-633 (2020)
Druh dokumentu: article
ISSN: 1682-1750
2194-9034
DOI: 10.5194/isprs-archives-XLII-3-W10-629-2020
Popis: The qualitative analysis of human landscape vulnerability is widely recognized, but quantitative analysis needs a lot of manpower, material resources as well as time to carry out the social observation. Based on remote sensing and spatial data, quantitative analysis of human landscape vulnerability will change this situation. This paper put forward a vulnerability evaluation model for change detection with remote sensing time series images and spatial tourism data. It is not only a quickly analysis tool which spans from the earth observation to the social observation for quantitative evaluation, but also an assistant tool for decision-making from change detection analysis to trend analysis.The vulnerability evaluation model of Jiuzhaigou Tibetan human landscape highlights the vulnerability of the whole region has increased significantly. The good structure ratios of bio-abundance are the basis of the human landscape protection, but the activities of ice and snow areas may be a natural factor for the migration of native along the tour roads in the valley from hillsides. The impact of tourism activities is far less than the natural environment. But tourism activities have inevitably affected the human landscape protection, and its negative index benefit is almost three times as much as the positive index benefit of protection measures. Especially, with the change of production and lifestyle of native brought by tourism activities, the human landscape is gradually disappearing. Further development of tourism activities will also extend the impact to the Balance Zone. It is urgent to reconstruct the current management model of human landscape.
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