TY - GEN
T1 - Ecological Sensitivity Analysis of the Jiulian Mountain Scenic Area Based on Multi-Source DEM Remote Sensing Data
AU - Chen, Bowen
AU - Chen, Xiaolong
AU - In Wong, Cora Un
AU - Zhang, Hongfeng
AU - Zhang, Wenshuo
AU - Zhan, Jinghui
N1 - Publisher Copyright:
© 2024 SPIE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - DEM remote sensing data
KW - Jiulian Mountain
KW - analytic hierarchy process
KW - ecological sensitivity
KW - scenic area
UR - http://www.scopus.com/inward/record.url?scp=85187545540&partnerID=8YFLogxK
U2 - 10.1117/12.3023992
DO - 10.1117/12.3023992
M3 - Conference contribution
AN - SCOPUS:85187545540
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Second International Conference on Environmental Remote Sensing and Geographic Information Technology, ERSGIT 2023
A2 - Qin, Jun
A2 - Yu, Wenjin
PB - SPIE
T2 - 2023 2nd International Conference on Environmental Remote Sensing and Geographic Information Technology, ERSGIT 2023
Y2 - 10 November 2023 through 12 November 2023
ER -