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

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TLDR
In this article , the authors used 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.
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.

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Site Selection of Urban Parks Based on Fuzzy-Analytic Hierarchy Process (F-AHP): A Case Study of Nanjing, China

TL;DR: Wang et al. as mentioned in this paper integrated geographic information systems and fuzzy hierarchical analysis (F-AHP) to evaluate the suitability of the site selection of urban parks in Nanjing, China.
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Spatio-Temporal Changes in Land Use and Habitat Quality of Hobq Desert along the Yellow River Section

TL;DR: Based on multi-temporal remote sensing from 1991 to 2019 in the Hobq Desert along the Yellow River section, a study selected spatial statistical methods (land-use monitoring and landscape metrics) to examine land-use change dynamics as discussed by the authors .
Journal ArticleDOI

Coupling Evaluation and Spatial–Temporal Evolution of Land Ecosystem Services and Economic–Social Development in a City Group: The Case Study of the Chengdu–Chongqing City Group

TL;DR: In this article , a coupling evaluation model of economic-social development and land ecosystem service by using the entropy weight method, coupling coordination degree model, gravity center model, and standard deviation ellipse model is presented.
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Optimising the relationship between ecological protection and human development through functional zoning

TL;DR: In this article , a combination method for optimising the functional zoning of national parks, taking the Yarlung Zangbo Grand Canyon national park (YZGCNP) as an example, under a new perspective of reconciling conflicts between national parks and human activities.
Journal ArticleDOI

Multi-Scale Spatiotemporal Pattern Analysis and Simulation (MSPAS) Model with Driving Factors for Land Cover Change and Sustainable Development Goals: A Case Study of Nepal

TL;DR: In this article , a multi-scale spatio-temporal pattern analysis and simulation (MSPAS) model with driving factors for sustainable development goals (SDGs) was proposed, which focused on four specific land cover classes of urban, farmland, forest and grassland to explore the pattern of Nepal's LCC from 2016 to 2019.
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