Category Archives: gis

The spatial password

A secret spot – a potential password? Hardly anyone knows about this 5 meter high rock face in the forests outside Trondheim.

Remembering passwords takes focus and time. I want to authenticate myself without having to write in a meanlingless stream of characters. I am on a weekly basis nagged by different systems to change my paswords.

We already have several biometrically based authentications metods. Fingerprints, iris scans, selfies, hand geometry and what have you. More are probably more to come. The jury is out on several of the metods. I will leave this to the experts.

Being a geographer my favourite authentication metod will rely on spatially referenced secrets buried deep inside my mind. I want to propose a novel metod for authentication. I want to use a map to navigate to a place which has a special meaning for me. It would basically work like this:

  1. I am stating my username (written)
  2. The system then asks me to authenticate my user status by asking me for one or several geographical position.

The position could be the answer to questions like these:

  • Where did you find your wallet when you lost it in 2012?
  • Where was your father born?
  • What is your favourite place to pick blueberries?
  • Where is the secret rockface outside Trondheim?
  • Where did you spend the night the 17th of november 1995?
  • and so on…

My answer would be made not by entering a string of characters. I would answer the question by panning and zooming a map to the  particular place. My answer would be to place a pin somewhere.

The method could be strengthening by asking for a combination of several places, or by varying the required precision in my answer. The answer (coordinates backoffice) would then be used to establish a string which again is the authentication variable (password).

Here are some combinations of the screen based password:

  • One position
  • Several positions
  • User traces a path

Real position combinations

  • Actual position represents the password
  • transport between several position srepresents the password
  • A track based on movements represents the password

The method will of course have it’s weaknesses. But it could work. And if someone already made this – then please send me a link!

An other variation of this method could be physical location or relocation in a given pattern. This would of course require a positional system which can not be spoofed, but where the position and its reporting is possible to confirm.

Coastlines fascinate

Seems like I am pulled to the coastlines. Seems like I am not alone. People tend to gravitate towards food resources, and where the ocean meets land, and even rivers, food has always been plenty. Trade too. And the boats of course.

I have a house, in the northern parts of Norway where the shoreline is but 200 meters away. From where I live in Trondheim I can see the fjord. The ocean has  always been around.

I am one of those with fond memories of small waves, a grandfather safely steering the boat, and days blessed with sun and fishing. When the weather was less than fair we stayed in or near my grandparents house enjoying our small adventures around the old farm.

Seems also that the places I travel to these days are close to the ocean. Zanzibar is one of these fantastic places where oportunities and challenges arise practically on the shoreline. Mapping those oportunities and challenges is part of what I do. It invoves drones, big databases, partners in many institutions, researchers and more. Sometimes it comes together in a map describing the sensitivities of a coastal area. I like the thought of it, but fear that we more often than not do not have enough knowledge to present detailed enough maps.

In September we took some time off from our QGIS workshop to play around with the EPA drone. Great fun in the tennis court.

Ghana is an other of those places. My stays are usually in Accra, and although the coastline is

never far away it is merely the frame of the ocean and not much more. Inaccessible because of restricted daytime for me, the workshop participant and meetings participant. Workshops outside Accra usually end up being in Sogakope, a 60 minute drive down to Keta. But my meetings usually revolve on issues related to the ocean and its shoreline.

What’s with the coastal areas then? Here are some of the processes I am involved in:

  • Environmental atlases
  • Coastal sensitivity analysis for emergency response
  • Digitalization of drone data in coastal areas (coastline/mangrove/substrate)
  • Methods development of sensitivity assessments (both coastal and terrestrial)

I have attached a video from a recent (September 2017) trip to the Keta Lagoon area in Ghana. On a small strip of land between the Keta Lagoon and the coastline thousands of people live their lifes. The inland areas which are not flooded (remember this is a lagoon) are occasionaly flooded rendering the areas uninhabitable for parts of they year.

In the video you can see the sand traps designed to “harvest”sand so that the thin strip does not erode. You can see this as big dumps of stone perpendicular to the shoreline.

Apart from letting us see some of the areas near the coast the video also shows some highlights form a QGIS training near Sogakope.

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.

Continue reading

Wilderness 3: About the examples

A philosophical approach towards wilderness analysis has been written. A FME-script has been designed and appropriately discussed. Now time has come to run the script on national level data to prove the concept and also open up for a discussion on challenges with the method and its results.

I have done this for several countries and will deliver the results and discuss them appropriately.

All examples are delivered as-is. There is no governmental context to the analysis. The data used for the analysis is OpenStreetMap data.

At the time of writing this article the number of examples has yet to be decided. The following are available as of writing this posting:

General challenges with the presented data are:

  • OSM data coverage
  • Encroachment criteria selection
  • Lack of context

In later postings I will look at the following:

  • Change analysis of wilderness
  • Cartography and wilderness mapping
  • Conclusions and discussion

Wilderness 3b: The Guinea analysis

The map in this posting is the results of a calculation of wilderness based on methods discussed earlier in this series using OpenStreetMap data for Guinea.

One of the reasons why I choose Guinea for a wilderness analysis is that I do not know the country. I have not worked with anyone in the conservation scene in Guinea. I barely know the geography of the country. Guinea did however seem to have a decent OSM coverage. It has also had a lot of focus lately due to the ebola virus.  Continue reading

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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QDGC-files updated

qdgc_logoThe 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