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- 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.
- 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.
mcMCCA
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.
rupMC
PublicrupMC is a parallel Marching Cubes (MC) program based on the ray-unit. Firstly, ray-units are used in rupMC as the basic voxel to determine how the surface intersects. Secondly, rupMC uses multiple computing processes and threads on a CPU/GPU heterogeneous architecture to process the points concurrently.mcPLUS
PubliccuFSDAF
PubliccuFSDAF 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 intensive procedures are parallelized using the Compute Unified Device Architecture (CUDA), a parallel computing framework for GPUs. Moreover, an adaptiv…CSD-RkNN
PublicCSD-RkNN: Conic Section Discriminances for Large Scale Reverse k Nearest Neighbors QueriesintCBDS
PubliccuESTARFM
PubliccuESTARFM is a GPU-enabled enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM)cuSTSG
PubliccuSTSG is a GPU-enabled spatial-temporal Savitzky-Golay (STSG) program based on the Compute Unified Device Architecture (CUDA). Firstly, the cosine similarities between the annual NDVI time series are used to identify and exclude the NDVI values with inaccurate quality flags from the NDVI seasonal growth trajectory. Secondly, the computational p…- 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…
CHN6-CUG-Roads-Dataset
PubliccuSTARFM
PubliccuSTARFM is a GPU-enabled Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM)cuSTNLFFM
PubliccuSTNLFFM is a GPU-enabled Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM)SSDGL
PublicSSDGL: A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification (TCYB2021) https://ieeexplore.ieee.org/document/9440852mcRPL
PublicSCMA-MCAE
PublicpRPL
Publicparallel Raster Processing Library (pRPL) is a MPI-enabled C++ programming library that provides easy-to-use interfaces to parallelize raster/image processing algorithms