Area with wilderness and encroachment. Visualization of change of wilderness status.
Wilderness degradation happens when new encroachments are made changing the wilderness status of an area. It is a complex issue which does not easily lend it self to a GIS based analysis. I will refer to my posting on wilderness for a peek into the complex world of wilderness philosophy.
It is possible to set up a system like FME to do an analysis of changes in wilderness due to new encroachments. The procedure I made generates a wilderness degradation data set based on wilderness and (new) encroachment data. It is based on procedures used by the Norwegian government in their analysis of wilderness and encroachment. The system should however be easy to accommodate for different preconditions by manipulating the number of wilderness zones and/or their buffer distances.
To visualize the degradation of wilderness it is necessary to make a categorization and furthermore establish a cartography to carry the information to the reader. In my view this can not be done unless the author/mapmaker to some extent takes side in what is good or not good related to wilderness degradation. This will be the focus on a forthcoming posting, but I will touch into the issues here as well.
FME is but one of the potential solutions for producing the results. QGIS, GeoKettle and even PostGIS could be good alternatives. The GitHub project has room for alternative implementations.
I visited Bulgaria in December 2014. Based on discussions with BBF while contributing to their GIS training I decided to do a national wilderness analysis for Bulgaria. The Bulgaria analysis was done using OpenStreetMap data.
The above map is based on publicly available vector data from the OpenStreetMap-project covering Bulgaria. A wilderness analysis based on insufficient data will only represent a map of more or less mapped areas. In this case the basis for the analysis is decent. There will still be many errors.
The analysis has not in any way been sanctioned by Bulgarian authorities. But then again, why should it be? A map like this could be made by anyone having access to encroachment data and the tools to do the analysis.
The criteria used to map the wilderness areas based on OpenStreetMap in Bulgaria is as follows:
Land use: industrial, reservoir, military, farmland, residential, orchard, commercial, quarry, farmland and salt_pond
The choice of data representing encroachments is highly subjective. A Bulgarian might have a completely different view of what qualifies as encroachment. And based on this one might establish a constructive dialogue on land use issues.
In a former posting I discussed how wilderness is not only about politics, religion, philosophy and legal instruments. Unless we force it into a practical context, the term “wilderness” remains an intangible size. Geographers have a long history for making representations of the intangible – be it disease (John Snow), social justice and injustice, demography and more. To my knowledge one of the first impressions of wilderness or “the wild” is what we can find in some older maps. “Hic sunt dracones” (here be dragons) is an expression which can be found on the “Hunt-Lenox Globe” (c. 1503–07). Other maps bear similar indications of uncharted or remote areas. We, the geographers, have moved on. Today we paint our dragons in more sophisticated ways.
The use of technology to “find” or delimit wilderness has a long history in Norway and other countries. I will continue this tradition and do an analysis which in many ways is similar to those done in Norway. The encroachment types will be slightly different. So will the technology used to do the analysis.
In this posting I will look at how FME can be used to establish a wilderness areas data set. The results will be presented in a separate posting.
Any analysis of wilderness areas will be based on an understanding of environmental, philosophical, religious, human and political factors. In Norway this understanding has over the years led to a categorization of wilderness into different area classes based on distance to defined encroachments. Roads, railways, towers, and more represent encroachments in the context of wilderness.
Through a couple of blog posts I will look more broadly at terrestrial wilderness analysis using different GIS tools. The tools this time will be FME desktop, QGIS and Geonode. I will present methods for generating a wilderness layer and visualization. I will also present tools for analyzing changes in wilderness status based on new encroachments. The work will be done in collaboration with Tanzania Conservation Resource Centre which allowed me to use their FME license for this work.
Recreational road/track in Serengeti, June 2006. (photo: Ragnvald Larsen)
The term wilderness deserves more than a flat technical consideration. In my view our definition of wilderness also defines us as humans – for better and worse. In this posting, the first in this series, I will focus on the more philosophical side of the term wilderness. I did however choose to be a geographer and not a philosopher, so bear with me… Had I chosen to be a philosopher it would probably have been a lousy one – I hope I am a better geographer.
The Quarter Degree Grid Cells (QDGC) data set has been updated. It is well over a year since last time. Some errors in the current release has made this necessary.
One of the things which kept me from doing the update was the rather complicated python-scripts combined with using the arcpy-library. The whole process was in it self complex. I dreaded sticking my head down into the python/arcpy/manual processing soup.
Through the last year or so I have started using FME more and more. Once you know a tool well you start thinking – what if… So I thought – what if I instead of going one more round with python and arcpy tried solving this challenge using FME? Continue reading →