Deforestation rates in Africa are in general high, but differences between countries are large. I want to illustrate these differences in a series of deforestation maps (change in forest and woodlands cover, including and excluding forest plantations, etc.). Normally I would use GRASS GIS or QGIS for such a task, but this should be easy to do in R too. Below I give a step-by-step description of my first attempt to make a Choropleth map in R (with the deforestation rates for 1990-2000 and 2000-2005). Continue reading
Well, in my (admittedly limited) experience, that is actually one of the weaker points of many open source GIS programs. Take for example GRASS or SAGA GIS. Both are very powerful analytical tools, but at the same time options to create nice looking maps from the results of your analyses are fairly limited. From the open source software I have tried, QGIS offers the best options to produce nice maps for printing. It is not yet on par with ArcGIS in terms of ease of use and results, but almost every release brings improvements over previous versions. And what I really like about it is that you can easily combine data layers from very different sources, e.g, raster and vector layers from a GRASS database with shapefiles and geotiff or ascii raster files.
And now with the Quantumnik plugin you can generate mapnik xml mapfile from an existing project, which can then be used in Mapnik. Mapnik is , to quote their website, “a free Toolkit for developing mapping applications. Above all Mapnik is about making beautiful maps”. I haven’t tried it out yet, but see this blog for more information. It sounds like a promising option and I will definitely try this out next time I have to make some printed maps.
Recently I received an excel file with the coordinates of 144 vegetation sample plots, with the request to get the altitude values for the plots. For those with little experience in GIS, this is easy enough in most GIS programs. Here is a simple tutorial/example how to extract raster values at point locations in QGIS. Continue reading
To create more synergy between projects and research efforts of one or more organizations, it is essential to have a good overview of ongoing projects, including where those projects are being implemented. A good example is the The CGIAR (the consultative Group on International Agricultural Research). This is a strategic partnership of 15 international agricultural research centers, working in collaboration with many hundreds of government and civil society organizations as well as private businesses around the world. The centers have offices and projects all over the world, making it rather a challenge for the managers or scientists within these institutes, but also for the many donors financing their work, to keep a good overview of what is happening and where.
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. As indicated on the WorldClim website, ESRI software assumes that the data files (.bil) do not have negative values. These values (x) are replaced by (65535 + x); E.g., -10 becomes 65525. This also means that the nodata value of -9999 is not recognized. Unfortunately, gdal, used by GRASS GIS to import the data, seems to make the same assumption. As a workaround, WorldClim recommends to use Diva-GIS. Although free, it doesn’t run on Linux. So, then what? Continue reading
See The grunts of the jaguar on Forestalis for a nice story by Jeroen van der Horst about his trip in Madidi National Park in Bolivia. I had no clue where to find this park so decided to look it up, and to share the result for those interested…
As it turns out, it is fairly easy it is to make your own map and share it through Google maps. First you need to create a kml layer with the park boundaries. This can easily be done in QGIS using the QGIS plugin OGR Layer converter. To enable this plugin, go to the menu ‘Plugins | Manage plugins’ and select ‘OGR Layer Converter’. Now you will find ‘OGR Converter’ in the drop down menu of Plugins. Next: Continue reading