Spatial-temporal Changes and Multi-scenario Prediction of Ecological Land in Karst Area Based on FLUS Model —A Case Study in Ningyuan County, Hunan Province
|更新时间:2025-03-12
|
Spatial-temporal Changes and Multi-scenario Prediction of Ecological Land in Karst Area Based on FLUS Model —A Case Study in Ningyuan County, Hunan Province
Bulletin of Soiland Water ConservationVol. 42, Issue 2, Pages: 219-227(2022)
Lin Tong, Feng Zhaohua, Wu Dafang, et al. Spatial-temporal Changes and Multi-scenario Prediction of Ecological Land in Karst Area Based on FLUS Model —A Case Study in Ningyuan County, Hunan Province[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 219-227.
DOI:
Lin Tong, Feng Zhaohua, Wu Dafang, et al. Spatial-temporal Changes and Multi-scenario Prediction of Ecological Land in Karst Area Based on FLUS Model —A Case Study in Ningyuan County, Hunan Province[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 219-227. DOI: 10.13961/j.cnki.stbctb.2022.02.030.
Spatial-temporal Changes and Multi-scenario Prediction of Ecological Land in Karst Area Based on FLUS Model —A Case Study in Ningyuan County, Hunan Province
[Objective] The quantity and distribution characteristics of ecological land in the karst area during 2000—2020 were analyzed and the changes in ecological land based on multi-scenario decisions in the future were predicted to seek the optimal scenario and coordinate ecological protection and development
in order to provide a theoretical foundation for the future land space development and protection
ecological space management and regional eco-economic sustainable development of the study area. [Methods] The land use transfer matrix and dynamic degree model was used to analyze the land-use change characteristics at Ningyuan County
Hunan Province. The FLUS (future land use simulation) model was used to simulate and predict the quantity and distribution of ecological land under different scenario decisions in 2030. [Results] ① Cultivated land was mainly concentrated in the central area of Ningyuan County
and the original ecological land of forest land and grassland was mainly distributed in the north
south
and west. Among the natural ecological land in 2020
forest land accounted for 56.69%
grassland for 12.85%
and water area for 0.60%
and semi-artificial ecological land of cultivated land
accounted for 27.80%. ② Under the ecological protection priority scenario
the forest land
grassland
and water area increased by 15.12
37.35
and 23.67 hm2
respectively
compared with those in 2020. ③ The policy had a significant regulating effect on the change of ecological land in the karst area
and socioeconomic development had a significant impact on water area increase. [Conclusion] The proportion of original ecological land in Ningyuan County is as high as 70.14%. The priority scenario of ecological protection ensures that ecological land is not occupied by non-ecological land at the maximum extent. This scenario is suitable for the urban development of Ningyuan County or the similar areas under the goal of building a forest city.
Carter R E, Mackenzie M D, Gjerstad D H. Ecological land classification in the Southern Loam Hills of South Alabama [J]. Forest Ecology and Management, 1999,114(2/3):395-404.
Klijn F, Haes H A U. A Hierarchical approach to ecosystems and its implications for ecological land classification [J]. Landscape Ecology, 1994,9(2):89-104.
Dale V H, Brown S, Haeuber R A, et al. Ecological principles and guidelines for managing the use of land [J]. Ecological Applications, 2000,10(3):639-670.
Rowe J S, Sheard J W. Ecological Land classification: A survey approach [J]. Environmental Management, 1981,5(5):451-464.
Joanna B, Michael G, David S K, et al. A paradigm for protecting ecological resources following remediation as a function of future land use designations: A case study for the department of energy’s Hanford Site [J]. Environmental Monitoring and Assessment, 2020,192(3):1-29.
Banerji S, Biswas M, Mitra D. Semi-quantitative analysis of land use homogeneity and spatial distribution of individual ecological footprint in selected areas of Eastern fringes of Kolkata, West Bengal [J]. Geocarto International, 2020,35(1):1-21.
Widaningrum D L, Surjandari I, Sudiana D. Analyzing land-use changes in tourism development area: A case study of cultural world heritage sites in Java Island, Indonesia [J]. International Journal of Technology, 2020,11(4):688-697.
Li Zuzheng, Cheng Xiaoqin, Han Hairong. Analyzing land-use change scenarios for ecosystem services and their trade-offs in the ecological conservation area in Beijing, China [J]. International Journal of Environmental Research and Public Health, 2020,17(22):8632-8651.
Chen Zhanzhuo, Huang Min, Zhu Daoye, et al. Integrating remote sensing and a Markov-FLUS model to simulate future land use changes in Hokkaido, Japan [J]. Remote Sensing, 2021,13(13):2621-2643.
Peng Jian, Zhao Mingyue, Guo Xiaonan, et al. Spatial-temporal dynamics and associated driving forces of urban ecological land: A Case Study in Shenzhen City, China [J]. Habitat International, 2017,60:81-90.
彭建,蔡运龙, P H Verburg.喀斯特山区土地利用/覆被变化情景模拟[J].农业工程学报,2007,118(7):64-70,292.
Liu Xiaoping, Liang Xun, Li Xia, et al. A future land use simulation model(FLUS) for simulating multiple land use scenarios by coupling human and natural effects [J]. Landscape and Urban Planning, 2017,168(168):94-116.