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 space on your hard-disk.

It moreover has the option to import and convert the layer to the region settings of the mapset you are working in. Alternatively, you can import rasters in their original extend and resolution. Continue reading “Importing WorldClim climate .bil datalayers in GRASS GIS II”

Spatial datasets on the web

For my work I am spending much time finding spatial data including environmental, administrative and land use coverage data. I started to record links with short description and keywords in a simple table for future references. I tried out two online spreadsheet programs to keep my records; Google docs and Zoho. I decided to stick with the latter former because it allows me to publish tables on my webpage with filters and column sorting (edit: I switched from Zoho to Google docs, mostly because I am using Google Docs for other projects and rather keep my documents in one place). Continue reading “Spatial datasets on the web”

TACCIMO – a template for Assessing Climate Change Impacts

Collecting and producing data is one thing, combining it and making it easily accessible and useful for the end-users another.

The Template for Assessing Climate Change Impacts and Management Options (TACCIMO) is a nice example of a Web-based tool that provides land owners, managers, and planners in the United States with the most current climate change science available. Continue reading “TACCIMO – a template for Assessing Climate Change Impacts”

Calculating bioclim variables in GRASS GIS

I am currently working on the modeling of the distribution of different vegetation types and associate species in eastern Africa. In absence of more detailed climate data for the region, a great source of global climatic data is the WorldClim website. Besides the usual monthly temperature and rainfall data, it provides bioclimatic variables which are derived from these monthly temperature and rainfall values in order to generate more biologically meaningful variables. However, it only does this for the current conditions (interpolations of observed data, representative of 1950-2000) but not yet (?) for the future conditions (downscaled data from global climate model (GCM) output, IPPC 3rd assessment). Thus, I had to calculate them myself, which I did using GRASS GIS and R. Continue reading “Calculating bioclim variables in GRASS GIS”