Building sensitivity atlases

Researchers, environmental managers, ecologists, researchers – we are all looking for a better perspective. Fieldwork, remote sensing and systemic understanding lets us piece together knowledge which in turn can be used to prioritize human interaction with our environment. All this knowledge represents generalizations. The paradox of generalisations is that they are some times needed for us to see our world in a manageable way. The less we see, the better some of our decissions will be.

A sensitivity atlas is a generalization. The sensitivity atlas method does not represent a method which is usually associated under laws, regulations or international agreements. It is currently a lump bag of methods given one name. More than 20 different implementations of the method are around – if not more. Given the helpful nature of most of these implementations it has been intersting to try to find one unified method. We’re working on it.

Where do they come from? Well… doing some research I found that one of the firs sensitivity atlases was South African. I found a copy of it at Oxfam in Great Britain and bought a copy. Excellent!

The method as such has a history going back over 35 years in time. In its many forms it has been a central tool for creating priority maps for land use, emergency response and more. The processes of implementation have often been associated with high costs, many man hours and high in technical capacity requirements with its many practitioners.

By establishing a better documented and more light-weight method, we hope to see many positive consequences. Here are some of them:

  • A well described method can more easily be shared through training and other communication.
  • Supporting technical implementations will be more harmonized while still being developed using different technical platforms.
  • The resulting sensitivity atlas products are easier to understand and put into context as the methods will not vary.
  • A unified method will promote the establishment of a wider community of practitioners.

At a workshop presenting a new step towards a unified method in Arusha in September 2019, representatives from 8 environmental agencies were invited and present. Our guests were from Uganda, Ghana, Tanzania, Zanzibar, Mozambique, Kenya, Somalia and Lebanon. The workshop was held by representatives from the Norwegian Environment Agency and UNEP-WCMC.

Presented at the workshop was a first draft of a method where different data sets were prepared and processed according to tis method. In preparation a scripted procedure was prepared. Together with the procedure we also distributed country packages with prepared test data sets, grid sets down to around 800×800 meters and QGIS project files.

The software used for the processing was FME from Safe Software. It was chosen because it represented a straightforward way to implement the necessary procedure. The developed procedure requirements were written by NEA and UNEP-WCMC. The procedure was rapidly developed by the Norwegian company Norkart using FME from SAFE software. It works like a charm!

The visual programming interface of FME,

FME is a tool which is used by many commercial entities and government offices to prepare, process and deliver data. Being a commercial tool, it would usually require the participants at a workshop like this to have their own licenses. Upon asking for in kind licenses for this work, SAFE software said yes and provided the 30 participants with licenses. We are extremely happy for this opportunity to use FME!

The presentation software for the resulting data sets was QGIS. It was primarily chosen because it is open and free software. Relevant templates for presenting the data were made and they were used at the workshop. QGIS is an excellent tool both for managing data and for presenting it in dynamic ways.

The reception of the tools at the workshop were overwhelming. Within 5 days all participating agencies had established their own sensitivity atlases using the available tool. For many of them this has been planned for years, but now the tools let them do this with test data prepared for his workshop. Birdlife International, IUCN, Protectedplaned.org and many more have provided data for us to use in this workshop.

In using this method both ecological and technical knowledge is required. A crucial part of the method is to evaluate what in this method is referred to as sensitivities and priorities. This can not be done without knowledgeable ecologists and biologists. Neither can this work be done and presented without someone which can nurture the process on a technical level.

With this tool the participating environmental agencies have been emancipated. They are now technically able to process national sensitivity atlases. Continued support and advice on using different asset layers will be important. Follow up on

We will continue to document our tools on a researchgate project and will also try to post project updates as we go. If you are interested in the use of the Quarter Degree Grid Cells used in this project please read this paper.

This workshop represents an important step forward!

The following institutions deserve a special mention: Safe Software, Norkart, Tanzania Conservation Resource Centre, Obscom, #norad, #oilfordevelopment and many others.

Data Availability and Reliability report for Ghana coastal areas

Some years ago the Norwegian Directorate for Nature Management contributed to the Oil for development program under The Norwegian Agency for Development (NORAD). The program contributes to projects in Africa, Asia and South America. Ghana was, and still is, one of the partners to the Oil for Development Program.

As part of this mission it was agreed with the Ghanaian partners that Ragnvald Larsen and Howard Frederick (as an external consultant) should visit EPA and other relevant institutions to establish a firmer basis for further collaboration on environmental data management.

The attached report is from work done in Ghana in 2012. The work was mainly done by Howard Frederick, but contributions were also done by Roger Lewis Leh (EPA) and Ragnvald Larsen.

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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.

Mindværet – nordligst del

Jeg har laget noen ortofoto av de nordligste delene av Mindværet. Mindværet er en skjærgård som ligger rett sør for øya Mindland på helgelandskysten. Øyområdet er godt egna for dagsturer med båt/kajakk. Det fins mange naturlige ankringssteder.

Området  har et rikt fugleliv. Det er dessverre amerikansk mink i området, noe som går sterkt ut over fuglelivet i området.

Ortofotoene er satt sammen av 1.355 enkeltbilder tatt fra en høyde på 120 meter over havet. Bildene er bearbeidet ved hjelp av spesialprogramvare.

Et spesielt vakkert parti med svært gode muligheter for både fortøyning og bading.

Sammenstillingen er laget med utgangspunkt i bilder som er i berøring med landområder. Oppløsningen på kartene er i full størrelse så god at de kan egne seg til utskrift i størrelsesorden 1×1 meter.

Kartene kan lastes ned og kan benyttes vederlagsfritt.

Ortofotoet viser de største øyene i området. Sjøområdene mellom mer ikke tatt med. Filen er om lag 150 Megabyte stor og kan lastes ned. Et trykk på bildet vil ta deg til en nedlastingsside.

 

Ortofotoet/kartet viser de største øyene i området. OpenStreetMap er benyttet som bakgrunnskart. Dermed vises også øyer i omrdet uten ortofoto. Filen er om lag 125 megabyte stor og kan lastes ned. Et trykk på bildet vil ta deg til en nedlastingsside.

 

Brørholmen – ortofoto

Brørholmen ligger et par hundre meter fra Mindtangen på Mindland. Kartet/ortofotoet er satt sammen av 95 separate vertikalbilder tatt med drone. Bildene er tatt fra en høyde på 120 moh. Bildene er tatt om ettermiddagen den 19. juli 2017.

Det er fritt frem å laste ned og å skrive ut kartet til utskrift og lignende.

Mulig det dukker opp flere slike bilder  fra Mindland i løpet av sommeren.

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