High-performance Spatial Computational Intelligence Lab @ China University of Geosciences (Wuhan)
- 126 followers
- Wuhan, Hubei, China
- guanqf@cug.edu.cn
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Patch-generating_Land_Use_Simulation_Model
Patch-generating_Land_Use_Simulation_Model PublicThe PLUS model integrates a rule mining framework based on Land Expansion Analysis Strategy (LEAS) and a CA model based on multi-type Random Patch Seeds (CARS), which was used to understand the dri…
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Mixed_Cell_Cellullar_Automata
Mixed_Cell_Cellullar_Automata PublicThe Mixed-Cell Cellullar Automata (MCCA) provides a new approach to enable more dynamic mixed landuse modeling to move away from the analysis of static patterns. One of the biggest advantages of mi…
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Open-Space-Cellular_Automata
Open-Space-Cellular_Automata PublicA spatio-temporal approach based on Cellular Automata (CA) for simulating the spatial dynamics of open spaces (include urban green spaces, parks, squares, trails, courtyards, and other natural spa…
Repositories
- Patch-generating_Land_Use_Simulation_Model Public
The PLUS model integrates a rule mining framework based on Land Expansion Analysis Strategy (LEAS) and a CA model based on multi-type Random Patch Seeds (CARS), which was used to understand the drivers of land expansion and project landscape dynamics.
HPSCIL/Patch-generating_Land_Use_Simulation_Model’s past year of commit activity - intPLUS Public
HPSCIL/intPLUS’s past year of commit activity - ASTHCRN Public
HPSCIL/ASTHCRN’s past year of commit activity - mcPLUS Public
HPSCIL/mcPLUS’s past year of commit activity - Open-Space-Cellular_Automata Public
A spatio-temporal approach based on Cellular Automata (CA) for simulating the spatial dynamics of open spaces (include urban green spaces, parks, squares, trails, courtyards, and other natural spaces), by considering a set of spatial data that represents the infrastructural and socio-economic factors, namely the OS-CA (Open Space Cellular Autom…
HPSCIL/Open-Space-Cellular_Automata’s past year of commit activity - MSTGAN-airquality-prediction Public
MSTGAN is an innovative method designed for multi-station urban air quality prediction, which fully considers the individual, global, and local multi-scale information of air quality spatiotemporal sequences. It incorporates an attention-based dynamic graph modeling approach to capture global spatiotemporal dependencies.
HPSCIL/MSTGAN-airquality-prediction’s past year of commit activity - mcMCCA Public
HPSCIL/mcMCCA’s past year of commit activity - Mixed_Cell_Cellullar_Automata Public
The Mixed-Cell Cellullar Automata (MCCA) provides a new approach to enable more dynamic mixed landuse modeling to move away from the analysis of static patterns. One of the biggest advantages of mixed-cell CA models is the capability of simulating the quantitative and continuous changes of multiple landuse components inside cells.
HPSCIL/Mixed_Cell_Cellullar_Automata’s past year of commit activity
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