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Tag Archives: WorldClim
Importing WorldClim climate .bil datalayers in GRASS GIS II
I uploaded an update to the R script I posted earlier to import data downloaded from WorldClim into GRASS. The main change is that it unzips and imports one grid at a time into GRASS, thus requiring much less free … Continue reading
Posted in climate change, Data handling, Data sources, GIS, GRASS GIS, R computing environment
Tagged climate data, GRASS GIS, LinkedIn, R, WorldClim
6 Comments
Using DIVA-GIS to create bioclim data layers
Earlier I wrote more about how to calculate bioclim data layers in GRASS GIS. For people that do not use GRASS GIS, it is probably easier to generate these layers in DIVA GIS. You can get DIVA-GIS for free at … Continue reading
Posted in Data handling, Data sources, GIS
Tagged ArcGIS, bioclim, climate, DIVA GIS, GRASS GIS, WorldClim
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R script to import WorldClim datalayers in GRASS GIS
As I wrote before, you can download monthly climate data layers (rainfall, mean minimum and maximum temperature of the coldest and warmest month respectively) from WorldClim for current and future climate conditions. The latter can only be downloaded in generic … Continue reading
Posted in Data handling, GIS, GRASS GIS, R computing environment
Tagged .bil, data layers, import, WorldClim
2 Comments
Importing WorldClim climate .bil datalayers in GRASS GIS
In a previous post I wrote how you can generate bioclimatic data layers based on monthly rainfall and temperature data in GRASS GIS. Monthly climate data for future conditions can be downloaded from WorldClim in generic grid (raster) format only. … Continue reading
Posted in Data handling, GIS software, GRASS GIS, R computing environment
Tagged GRASS GIS, scripting, WorldClim
12 Comments
Calculating bioclim variables in GRASS GIS
A script is provided to calculate Bioclim variables in GRASS GIS on Linux using monthly temperature and rainfall data. Continue reading
Posted in GIS, GIS software, GRASS GIS, Modelling
Tagged climate data, GRASS GIS, open source, scripting, species distribution modeling, WorldClim
3 Comments
