Landsat TM Image Based Dynamic Analysis of Desertification Landscape Pattern in Xilin Gol League
- DOI
- 10.2991/rac-18.2018.105How to use a DOI?
- Keywords
- landscape pattern of sandy land; dynamics of desertification; driving forces
- Abstract
This paper uses the Xilin Gol League as a research area, based on Landsat TM and meteorological data for the past 15 years, selects three periods of remote sensing images to use RS, GIS technology and dynamic degree and landscape index to select the landscape pattern and desertification dynamics of sandy land from 2000 to 2015. The driving force factor is analyzed. The results show that the degree of fragmentation of the sandy landscape in the Xilin Gol district was reduced from 2000 to 2015, the landscape patch area was regularized, and the disturbance intensity of human activities on sandy land was reduced; the degree of desertification generally showed a reversal trend, but there was a development trend during the period. Further research shows that from 2000 to 2015, the main factors affecting the reversal of desertification are the increase of precipitation and the implementation of national and local policies in order to provide a theoretical basis for the desertification control project of the motherland and the protection of ecological security in the Beijing-Tianjin-Hebei region.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yanqi Wang AU - Shan Yin AU - Enliang Guo AU - Xiuqing Peng AU - Yuwei Li AU - Lili Hou AU - Ru Ya AU - Lumen Chao PY - 2018/10 DA - 2018/10 TI - Landsat TM Image Based Dynamic Analysis of Desertification Landscape Pattern in Xilin Gol League BT - Proceedings of the 8th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2018) PB - Atlantis Press SP - 666 EP - 671 SN - 2352-5428 UR - https://doi.org/10.2991/rac-18.2018.105 DO - 10.2991/rac-18.2018.105 ID - Wang2018/10 ER -