9 skills found
dymaxionlabs / Dask RasterioRead and write rasters in parallel using Rasterio and Dask
HPSCIL / PRPLparallel Raster Processing Library (pRPL) is a MPI-enabled C++ programming library that provides easy-to-use interfaces to parallelize raster/image processing algorithms
bbarker505 / Ddrp V2A final production version of the DDRP platform that includes cohorts, parallel processing, and improving mapping routines. The objective of the Degree-Day, establishment Risk, and Pest event mapping system (DDRP) is to predict phenology and climate suitability of invasive, biocontrol, and IPM species for the conterminous United States. DDRP is written entirely in the R statistical programming language (R Development Core Team 2019), making it flexible and extensible, and has a simple command-line interface that has already been adapted for online use. The platform can use a variety of gridded weather and climate data types for any historical (post-hoc), real-time, or future (downscaled GCM) time period. Model products include gridded (raster) and graphical outputs of number of completed generations, phenological/pest events, and climate suitability (i.e., establishment risk maps). The platform is described in a peer-reviewed paper in PLoS ONE (https://doi.org/10.1371/journal.pone.0244005).
rsh249 / RasterExtrasTowards a framework for parallel computing with raster and other geospatial data objects in R.
kadyb / Stars ParallelTutorial on parallel processing of raster data in the {stars} package
lspatial / SptemExpThe approach of ensemble spatiotemporal mixed models is to make reliable estimation of air pollutant concentrations at high resolutions. (1) Extraction of covariates from the satellite images such as GeoTiff and NC4 raster (e.g NDVI, AOD, and meteorological parameters); (2) Generation of temporal basis functions to simulate the seasonal trends in the study regions; (3) Generation of the regional monthly or yearly means of air pollutant concentration; (4) Generation of Thiessen polygons and spatial effect modeling; (5) Ensemble modeling for spatiotemporal mixed models, supporting multi-core parallel computing; (6) Integrated predictions with or without weights of the model's performance, supporting multi-core parallel computing; (7) Constrained optimization to interpolate the missing values; (8) Generation of the grid surfaces of air pollutant concentrations at high resolution; (9) Block kriging for regional mean estimation at multiple scales.
jakimowb / Eo Time Series ViewerA QGIS Plugin to visualize raster time series in parallel.
tmcdonell / Gloss Raster AccelerateParallel rendering of raster images using Accelerate
brasilbrasil / Ensemble SDMThis repository contains a set of r scripts that allow for ensemble species distribution modeling based on biomod2 package. It has build in parallel processing and many scripts for additional functionality such as output of rasters and jpegs for projections, nice looking ggplot figures from model evaluation, predictor importance, improved response curves. It also has a set of scripts for considering results across multiple species such as map of areas with largest number of potential species range gain, loss, etc.
