- Digitization – Territorial Modeling: Spatial elements and the characteristics
- This first week deals with the first step in digitizing terrain, namely territorial modeling. In this week, we will consider factors such as the scale and theme of interest in order to determine which objects or spatial phenomena should included in the model, and we will also see how the geographic positioning and intrinsic nature (e.g. raster or vector) of these elements factors into how they are characterized in a terrain model.
- Digitization - Geodata Capture and Documentation
- Digital data acquisition involves various techniques including the direct measurement of primary data, the semi-automated vectorization and digitization of spatial objects, or the georeferencing of digital images. In this week’s module we will begin with a lesson on metadata in which we will discuss the processes and rules for documenting a dataset, which are essential for data sustainability, and we will also introduce a case study on participatory GIS in Senegal and Seychelles.
- Digitization - Automated Capture and Use of Existing Geodata
- In this week we will continue to build on the topic introduced last week with automatic vectorization, and we will also review a non-exhaustive list of some important pre-existent data sources that are available for you to access. We will finish with a case study of a Senegal-Mauritania biodiversity project before you will test your knowledge in the first quiz of the module.
- Storage - Geodata Structure and Organization
- In this 4th week, which marks the beginning of the second module of the course devoted to data storage, we begin by reviewing the fundamental aspects of geodata storage and the most common data formats, before tackling the theme of relational databases and data modeling. The week concludes with a lesson on creating databases in the QGIS environment and a case study on the role of GIS in a transport and urban planning project in Senegal.
- Storage - Data Management with SQL
- The SQL language is the preferred vector for access to relational databases, and can be used to search for data meeting certain criteria (conditional queries), to aggregate and calculate statistics on subsets of data (aggregation queries), to combine the results of several queries (nesting and merging), to edit and modify data, or even to manipulate data structure (DDL, DML).
- Storage - Spatial SQL and NoSQL Databases
- While the previous week's lessons dealt with various general aspects of the SQL language, in this week we will learn about SQL queries specifically related to the spatial dimensions and the relationships that characterize geodata (geometric and topological spatial queries). We will also present a brief introduction into the rapidly expanding field of noSQL databases and finish the lesson portion of this module with a case study devoted to bushfire management in sub-Saharan Africa. Finally, this first MOOC on an introduction to geographic information systems will conclude with a second quiz to test your knowledge.
