Missing villages
In recent years, we have managed to map millions of buildings which can help us determine the distribution of the population. In our latest project called Missing villages – by using open-source government data about water sources in Tanzania – We’ve created a workflow that made it possible to give a name and delimit most of the Tanzanian settlements. A currently running project consisting of 3 parts. The first is completed, the second is ongoing, and the third is in the planning phase.
In phase one, Thiessen polygons were calculated from the water points layer, to get the influence zone of each water point. Then, the polygons were merged by attribute, where the village name is the same. The resulting polygons can help to determine the area where the village has to be. At the same time, the Mean centre was calculated for the points inside a polygon → potential position of the village. (Since in a few cases the name of a village occurs more than once in the country, a “village+district” combined data was used to help us to find the real mean centre.) This is our village data POI which needs to be implemented to OSM. The validated POIs were uploaded to OSM. 6776 POIs were added with this method to OSM.
In phase two, A building aggregation tool was prepared in ArcGIS to aggregate the building footprints to produce settlement layers. (Each settlement patterns area was measured, also the covered buildings were counted for each “building cluster”. These two data could help us to calculate inter alia – building density; Number of buildings, which data can help to predict the number of the population; The building density and building number can help in the classification of settlements like an Urban or rural area, or for settlement type: hamlet, village, or town
Phase three – The final steps will estimate the existing population number by using the latest census data from 2011, and calculates the difference of the human traces of activity by using satellite pictures from 2011 and 2018-2020 – when the Maxar satellite pictures were taken. (Unsupervised change detection in satellite images, which can help us to estimate the difference (increase/decrease), so to using data from the census, we can estimate the population number by the time the latest satellite pictures were taken.