Socio-economic analysis with nighttime light series. Step 1: downloading shapefile of the study area

Context: we analyze economic changes in Colombian municipalities between 1993 and 2020.

We need to download ArcGis, a geographic information system (GIS) for working with maps and geographic information maintained by the Environmental Systems Research Institute (Esri). It is used for creating and using maps, compiling geographic data, analyzing mapped information, sharing and discovering geographic information, using maps and geographic information in a range of applications, and managing geographic information in a database. Particularly important for the purpose of this post is ArcMap, one of the applications, which is primarily used to view, edit, create, and analyze geospatial data. In the absence of license for this software, you can use free software such as GVSig.

Once installed either of the GIS software you use, it is time to upload the cartography of your study area. Normally, that cartography is in a geospatial vector data format called shapefile. VDS Technologies provides shapefile of administrative division across the globe. We download the administrative division of Colombia. The file includes 23 documents, including the dataset of data and the proper geospatial vector data (.shp). COL_adm0 corresponds to the boundaries of the whole country, COL_adm1 the department and COL_adm2 the municipalities, our basic analysis unit.

In ArcMap, we “add data”, look in our folder and select COL_adm2

The boundaries of the municipalities will show up in the visor Clicking in Windows, Table of Content, another window shows up in the left side with a list of the layers you can visualize.

Clicking right bottom above COL_adm2 layer, you can see the table properly, with all the values associated to each of the municipalities showed in the visor. This table of content often contains demographic and other data and we can do some basic analysis. For instance, visualize population density using a scale of colors where the intensity works as an indicator of the number of inhabitants in that particular region.

Now that we have the cartographic basis for our analysis, next post is about “downloading nighttime images”, that is the “raw data” we are considering to analyze economic performance in each of the Colombian municipalities between 1993 and 2020, something that, using more official statistics would be more difficult.

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