Tag Archives: gis

Wilderness 3d: The Canary Islands wilderness

Wilderness on Lanzarote, Canary Islands, Spain.

Wilderness on Lanzarote, Canary Islands, Spain.

Like many other Europeans I have had my share of visits to the Canary Islands (three and counting). The climate is decent from February until November. Some even like it in December and January. Most of us go to the Canary Islands for sunbathing, for long walks, to swim, spend time with friends or just get away from it all.

Few, if any, go to the Canary Islands for the wilderness. In this article I will be looking at your options if you were interested in getting away from people in the Canary Islands. It is not easy, but it is possible. If you are looking for wilderness in the Canary Islands I would suggest going to Lanzarote. Parque National de Timanfaya is the easiest accessible wilderness area.

The above map is based on publicly available vector data from the OpenStreetMap-project covering the Canary Islands. 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 Spanish authorities. It will not be used by the authorities and the audience (GIS geeks) of this posting is anyway quite limited.

The criterias used to map the wilderness areas based on OpenStreetMap in the Canary Islands are as follows:

  • Roads: primary, secondary, tertiary, unclassified, motorway, trunk
  • Land use: industrial, reservoir, military, farmland, residential, orchard, commercial, quarry, farmland and salt_pond
  • Railways
  • Waterways: canal

Like it or not – the presented map is what you get.

Wilderness 4: Wilderness degradation analysis

Area with wilderness and encroachment. Visualization of change of wilderness status.

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. QGISGeoKettle and even PostGIS could be good alternatives. The GitHub project has room for alternative implementations.

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Wilderness 3a: The Bulgaria analysis

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:

  • Roads: primary, secondary, tertiary, unclassified, motorway, trunk
  • Land use: industrial, reservoir, military, farmland, residential, orchard, commercial, quarry, farmland and salt_pond
  • Railways
  • Waterways: canal

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.

Wilderness 2: A practical approach to wilderness analysis using FME

Psalter World Map ca 1265

Psalter World Map ca 1265

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.

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Converting shapefiles to Mission Planner .poly-files

15-9-plannedMission Planner by Michael Oborne is an impressive piece of software. It is used to program the open-source APM autopilot. The autopilot is used to control planes, copters and rovers. I have used Mission Planner a lot and I can not do without.

Some years ago I started making a map for the Mindland island in the archipelago of Norway using a GPS, OpenStreetMap and Bing aerial imagery. The main driver for this project was to document old place names. With the drones becoming somewhat of a hobby last year I thought it would be nice to also establish a proper open license ortophoto for the island. Mission planner has what it takes to approach such a task in a structured manner, save for one thing. The polygon tool only imports .poly-files.

When working with maps some of us tend to stick with shapefiles or geodatabases. I have made a small script which allows for the conversion of a shapefile with a geographic coordinate system (wgs84) to as many .poly files as there are objects in the shapefile. Adding the functionality to Mission Planner has been indicated as possible, but has yet to materialise. So until then the script associated with this posting remains relevant. Continue reading

Processing Sentinel 2 satellite imagery in Norway

ANB-11-05_frontpage_shadowThe second report on “Preparations for acquisition and application of optical satellite data for Norway Digital” (Gjertsen et al) written for the Norwegian Space Agency has now been published.

This report is a continuation of the work presented in the report “Preparations for acquisition and application of optical satellite data for Norway Digital” (Trollvik et al., 2012). The main goal has been to specify the requirements for a national satellite data centre for optical satellite data from the Sentinel-2 and Landsat series Earth observation satellites. The main objective of a national satellite data centre is to facilitate easy access to and use of Sentinel-2 and Landsat 8 data for Norwegian users. Continue reading

Clearinghouse for the environment – the girders (II)

In February 2012 I wrote about “Environmental Spatial Data Infrastructure” on this blog. Later that year the case complex matured somewhat and in August I wrote the posting “Clearinghouse for the environment – the scaffolding (I)“.

Since then I have together with my colleagues had the opportunity to test systems in full scale by contributing to the implementation of clearinghouses in partner countries.

Last time I showed how a stack consisting a hardware layer with vmWare as one of the basic modules could form the basis of an environmental spatial data infrastructure. In some ways this was a rather optimistic setup.

A stack of hardware and software which could become very usefull...

Some of our main challenges with the above set up was maintenance of physical equipment. So we removed that layer. Maintaining a complex setup with a virtual machine environment, or getting access to local environments proved in general to be difficult. So we ditched it.

To get the systems running we needed:

  • Shared access to the systems for administrative purposes
  • A flexible backup-system
  • An option to duplicate successful setups
  • Scalability
  • High availability
  • Flexible security system

Other things we considered important

  • The system should not tie our partners up in future licensing costs
  • Compliance to central standards
  • An option for partners to move the systems to physical infrastructure if necessary
  • Option to keep traffick outside our own company networks – since they are de-facto external systems paid for by external partners

As you all can see in all a lot of considerations which we had to relate to.

AWS_LOGO_CMYK-588x214Since internet access across borders in any case would be relevant for retrieving external map layers we started looking at how we could use Amazon services. I already had experience in running virtual macines using Amazon EC2. Amazon helped us out with many of the issues mentioned above. So in short we moved the whole setup to Amazon. The following figure illustrates the setup.

sdi_onestop_amazon

In addition to the components relying on EC2 we have also found that using Amazon Simple Storage (S3) for storing survey data of some size could be a good ide. S3 allows the user to distribute files using “secure” links and even using the bit-torrent protocol for files up to 5 Gb.

We now have one such system built up and under testing. It looks good but as always the technology is but a small part of the equation. Establishing information flows, using standards etc represents the major parts of a national envoronmental spatial data infrastructure.

Should the need arise to develop custom made solutions it should be possible to add more virtual machines in the setup.

sdi_onestop_amazon

Given that our partners find this setup trustworthy we will probably suggest this as an entry level spatial data infrastructure for environmental data.

WordPress directly, and through countless plugins, supports many standards for embedding information. How information should flow between the different systems in this setup has been given some thought. I will try to elaborate on this in a later posting – hopefully in less than two years time.