High-performance Spatial Computational Intelligence Lab @ China University of Geosciences (Wuhan)

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1. Patch-generating_Land_Use_Simulation_Model Patch-generating_Land_Use_Simulation_ModelPublic

   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 dri…

   190 50

2. cuSTARFM cuSTARFMPublic

   cuSTARFM is a GPU-enabled Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM)

   Cuda 72 35

3. cuESTARFM cuESTARFMPublic

   cuESTARFM is a GPU-enabled enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM)

   Cuda 69 25

4. Mixed_Cell_Cellullar_Automata Mixed_Cell_Cellullar_AutomataPublic

   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 mi…

   56 12

5. cuFSDAF cuFSDAFPublic

   cuFSDAF is an enhanced FSDAF algorithm parallelized using GPUs. In cuFSDAF, the TPS interpolator is replaced by a modified Inverse Distance Weighted (IDW) interpolator. Besides, computationally int…

   C++ 43 8

6. Open-Space-Cellular_Automata Open-Space-Cellular_AutomataPublic

   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 spa…

   27 10