Issue |
E3S Web Conf.
Volume 237, 2021
3rd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2020)
|
|
---|---|---|
Article Number | 04038 | |
Number of page(s) | 5 | |
Section | Ecological Environment, Urban Planning and Construction | |
DOI | https://doi.org/10.1051/e3sconf/202123704038 | |
Published online | 09 February 2021 |
Landscape ecological risk assessment and spatiotemporal change analysis in Yonghe County
1
College of Water Resources and Hydropower Engineering, Gansu Agricultural University, Lanzhou 730070, China
2
College of Forestry, Gansu Agricultural University, Lanzhou 730070, China
* Corresponding author’s e-mail: lig@gsau.edu.cn
On the basis of land use data, combined with ArcGIS and fragstats4.2, the landscape ecological risk spatial mode and process feature of Yonghe county from 1980 to 2018 were analyzed. The results showed that: (1) from 1980 to 2018, the landscape pattern of Yonghe county changed obviously, the area of arable land and holt decreased, while the area of grassland, water and buildings grow a number. The conversion area between arable land and grassland is the largest. In Yonghe County, the fragmentation degree of landscape is on the rise, and the separation degree is also on the rise. The overall dominance of construction land is the largest, and the dominance of grassland is the smallest. (2) The landscape ecological risk level gradually subsided, the area of middle risk area decreased, and moderate risk areas are falling. From the spatial distribution analysis, the risk types of Yonghe County subsided from southeast to northwest. The high-risk areas were principally scattered in sangbi town and Jiaokou township. The main landscape type in this area was grassland, which was easily disturbed by human activities; the low-risk areas were principally scattered in Potou Township in the north and Yonghe County in the middle of the study area, and Woodland and buildings are the main landscape types land have strong anti-interference ability and low risk value.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.