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.
Highlights
Under the influence of natural and human factors, land use/land cover change (LUCC)has had a latent influence on the material cycle and energy conversion in the ecological chain with the continuous advancement of urbanization
Before 2000, the reduced area of CL was mainly transformed into built-up land (BUL) and WL
After 2000, CL was mainly transformed into OC and BUL
Summary
Our aim is to obtain land-use-change data in the study area using remote-sensing data inversion and multiple-model simulation. Using the methods of supervised classification, landscape metrics, spatial statistical analysis, scenario simulation, grey-linear model, analytic hierarchy process and ES evaluation, the LUCC and ES function in the study area were used, evaluated and predicted.
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