Journal Article10.1016/J.LANDURBPLAN.2018.04.016
Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method.
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TL;DR: This paper argues that the delineation needs to integrate the top-down approach with CA for projecting complex land use changes under designed scenarios, and proposes a CA-based method called the future land use simulation (FLUS) that can support urban planning by generating feasible patterns for UGBs under different planning scenarios.
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About: This article is published in Landscape and Urban Planning. The article was published on 01 Sep 2018. The article focuses on the topics: Spatial planning & Urban planning.
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Citations
Multi-scenario simulation and optimization of habitat quality under karst desertification management
Xiang Li,Shunmin Zhang,Xiaona Li,Rong Chen,Huang Xiao-yuan,Jiansong Peng +5 more
TL;DR: This study simulates and optimizes habitat quality under karst desertification management using InVEST and FLUS models, revealing a decline in habitat quality due to urbanization and land use changes, with implications for ecological restoration and policy-making in karst desertification zones.
Impact of Land Use Change on Carbon Storage Based on FLUS-InVEST Model: A Case Study of Chengdu–Chongqing Urban Agglomeration, China
Zhou-Ling Shao,Chunyan Chen,Yuanli Liu,Jie Cao,Gui-tang Liao,Zhengyu Lin +5 more
TL;DR: This study examines the impact of land use change on carbon storage in the Chengdu-Chongqing urban agglomeration, China, using the FLUS-InVEST model, finding significant decreases in carbon storage due to land use conversions, particularly from farmland to built-up land.
A whale optimization algorithm-based cellular automata model for urban expansion simulation
TL;DR: In this paper , a whale optimization algorithm-based cellular automata (WOA-CA) model was proposed to help mining the transition rules of the CA model, which was also evaluated and utilized in the case study of Guangzhou, simulating urban expansion from the year of 2000 to 2010.
Multi Scenario Simulation of Land Use in Chaohu Lake Basin Based on PLUS Model
Jiang Jia,Weiling Guo,Li Xu,Gerard J. Chang +3 more
TL;DR: The LUCC of Chaohu Lake Basin from 2000 to 2020 is analyzed based on the PLUS model. The results show that urban land and cultivated land are the main changing land types. Annual precipitation and population are the main drivers of changes in urban land and arable land. The expansion of urban land is restricted under the CP scenario while also ensuring the total amount of farmland.
Ecological redline policy strengthens sustainable development goals through the strict protection of multiple ecosystem services
Lijuan Wang,Hua Zheng,Yongzhe Chen,Binbin Huang +3 more
References
Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model
Peter H. Verburg,Welmoed Soepboer,A. Veldkamp,Ramil Limpiada,Victoria Espaldon,Sharifah S.A. Mastura +5 more
TL;DR: A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S that explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability.
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A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects
Xiaoping Liu,Xun Liang,Xia Li,Xia Li,Xiaocong Xu,Jinpei Ou,Yimin Chen,Yimin Chen,Shaoying Li,Shaojian Wang,Fengsong Pei +10 more
TL;DR: A future land use simulation (FLUS) model that explicitly simulates the long-term spatial trajectories of multiple LUCCs, and the simulation accuracy is higher than other well-accepted models, such as CLUE-S and CA models.
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Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore.
TL;DR: A cellular automaton model, that was calibrated by using historical digital maps of urban areas and can be used to predict the future extent of an urban area, is applied to two rapidly growing, but remarkably different urban areas.
Neural-network-based cellular automata for simulating multiple land use changes using GIS
Xia Li,Anthony Gar-On Yeh +1 more
TL;DR: A three-layer neural network with multiple output neurons is designed to calculate conversion probabilities for competing multiple land uses and has been successfully applied to the simulation of multiple land use changes in a fast growing area in southern China.
Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model
TL;DR: In this paper, the authors introduce a modeling approach that integrates demand-driven changes in land area with locally determined conversion processes to simulate the evolution of natural vegetation on abandoned farmland in Europe.
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