Ecological sensitivity analysis of the Jiulian Mountain scenic area based on multi-source DEM remote sensing data

Bowen Chen; Xiaolong Chen; Cora Un In Wong; Hongfeng Zhang; Wenshuo Zhang; Jinghui Zhan

doi:10.1117/12.3023992

21 February 2024 Ecological sensitivity analysis of the Jiulian Mountain scenic area based on multi-source DEM remote sensing data

Bowen Chen, Xiaolong Chen, Cora Un In Wong, Hongfeng Zhang, Wenshuo Zhang, Jinghui Zhan

Author Affiliations +

Proceedings Volume 12988, Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023); 129880K (2024) https://doi.org/10.1117/12.3023992
Event: Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023), 2023, Xi’an, China

Abstract

In order to study the ecological sensitivity of the Jiulian Mountain scenic area and provide a basis for promoting the development and implementation of ecological planning in this region, we assessed the current state of the local environment. This article takes the Jiulian Mountain Scenic Spot in Hui County, Xinxiang City, Henan Province, as the research object and selects altitude, slope, aspect, water body, land use type, and vegetation coverage. 6 Each ecological factor is used as an ecological sensitivity evaluation index, which is divided into four evaluation levels: insensitive, mildly sensitive, moderately sensitive, and highly sensitive. The analytic hierarchy process is used to determine the weight, and the spatial distribution of single-factor and multi-factor ecological sensitivity is analyzed through GIS spatial analysis technology and multi-source DEM remote sensing data. The results show that the overall ecological sensitivity of the Jiulian Mountain scenic area is high. The highly sensitive area accounts for 28.52% of the total area; the medium sensitive area accounts for 26.25% of the total area; the low sensitivity area accounts for 21.51% of the total area, distributed in the northwest of the scenic spot; and the insensitive area accounts for 18.48% of the total area, evenly distributed in scenic spots. Finally, in light of the current conditions in the Jiulian Mountain scenic area, I propose targeted recommendations and strategies for the various sensitive regions. My goal is to advance ecological planning practices and sustainable development across the Jiulian Mountain region.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bowen Chen, Xiaolong Chen, Cora Un In Wong, Hongfeng Zhang, Wenshuo Zhang, and Jinghui Zhan "Ecological sensitivity analysis of the Jiulian Mountain scenic area based on multi-source DEM remote sensing data", Proc. SPIE 12988, Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023), 129880K (21 February 2024); https://doi.org/10.1117/12.3023992

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KEYWORDS

Vegetation

Analytical research

Environmental sensing

Remote sensing

Ecosystems

Geographic information systems

Analytics

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