Spatio-Temporal Evolution, Prediction and Optimization of LUCC Based on CA-Markov and InVEST Models: A Case Study of Mentougou District, Beijing

Yang Yi; Chen Zhang; Jinqi Zhu; Yugang Zhang; Hao Sun; Hongzhang Kang

doi:10.3390/ijerph19042432

Spatio-Temporal Evolution, Prediction and Optimization of LUCC Based on CA-Markov and InVEST Models: A Case Study of Mentougou District, Beijing

Int J Environ Res Public Health. 2022 Feb 19;19(4):2432. doi: 10.3390/ijerph19042432.

Authors

Yang Yi^{1

2}, Chen Zhang³, Jinqi Zhu⁴, Yugang Zhang⁵, Hao Sun³, Hongzhang Kang²

Affiliations

¹ Key Laboratory of National Forestry and Grassland Administration on Ecological Landscaping of Challenging Urban Sites, National Innovation Alliance of National Forestry and Grassland Administration on Afforestation and Landscaping of Challenging Urban Sites, Shanghai Engineering Research Center of Landscaping on Challenging Urban Sites, Shanghai Academy of Landscape Architecture Science and Planning, Shanghai 200232, China.
² School of Design, Shanghai Jiao Tong University, Shanghai 200240, China.
³ Shanghai Foundation Ding Environmental Technology Company, Shanghai 200063, China.
⁴ Jiangxi Institute of Ecological Civilization, School of Resources, Environmental & Chemical Engineering, Nanchang University, Nanchang 330031, China.
⁵ Taihu Basin Monitoring Central Station for Soil and Water Conservation, Taihu Basin Authority of Ministry of Water Resources, Shanghai 200434, China.

Abstract

With the rapid advancement of urbanization and industrialization, the contradiction between the social economy and resources and the environment has become increasingly prominent. On the basis of limited land resources, the way to promote multi-objective comprehensive development such as economic, social development and ecological and environmental protection through structure and layout regulation, so as to maximize regional comprehensive benefits, is an important task of current land spatial planning. Our aim is to obtain land-use-change data in the study area using remote-sensing data inversion and multiple-model simulation. Based on land suitability evaluation, we predict and optimize the land use structure of the study area in 2030 and evaluate and compare ecosystem services. Based on remote-sensing images and eco-environmental data from 1985 to 2014 in the study area, land use/land cover change (LUCC) and future simulation data were obtained by using supervised classification, landscape metrics and the CA-Markov model. The ecosystem services were evaluated by the InVEST model. The analytic hierarchy process (AHP) method was used to evaluate the land suitability for LUCC. Finally, the LUCC in 2030 under two different scenarios, Scenario_1 (prediction) and Scenario_2 (optimization), were evaluated, and the ecosystem service functions were compared. In the last 30 years, the landscape in the study area has gradually fragmented, and the built-up land has expanded rapidly, increased by one-third, mainly at the cost of cropland, orchards and wasteland. According to the suitability evaluation, giving priority to the land use types with higher environmental requirements will ensure the study area has a higher ecosystem service value. The rapid development of urbanization has a far-reaching impact on regional LUCC. Intensive land resources need reasonable and scientific land use planning, and land use planning should be based on the suitability evaluation of land resources, which can improve the regional ecosystem service function.

Keywords: CA-Markov model; InVEST model; LUCC; Mentougou District; ecosystem service.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Beijing
China
Conservation of Natural Resources
Economic Development
Ecosystem*
Urbanization*