This course is organized into two parts presenting the theoretical and practical foundations of geographic information systems (GIS). Together theses courses constitute an introduction to GIS and require no prior knowledge. By following this introduction to GIS you will quickly acquire the basic knowledge required to create spatial databases and produce high-quality maps and cartographic representations. This is a practical course and is based on free, open-source software, including QGIS.
Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.
If you study or work in the fields of land management or the analysis of geographically distributed objects such as land use planning, biology, public health, ecology, or energy, then this course is for you!
In this first part of the course, we will focus on the digitization and the storage of geodata. In particular, you will learn:
- To characterize spatial objects and/or phenomena (territory modeling) with respect to their position in space (through coordinate systems, projections, and spatial relationships) and according to their intrinsic nature (object/vector mode vs. Image/raster mode);
- About the different means used to acquire spatial data; including direct measurement, georeferencing images, digitization, existing data source, etc.);
- About the different ways in which geodata can be stored - notably, files and relational databases;
- How to use data modeling tools to describe and create a spatial database;
- To query and analyze data using SQL, a common data manipulation language.
The second part of this course will focus on methods of spatial analysis and geodata representation. In this section, you will learn:
- How to describe and quantify the spatial properties of discrete variables, for example through spatial autocorrelation;
- To work with continuous variables. In particular, we will look at sampling strategies, how to construct contour lines and isovalue curves, and we will explore different interpolation methods;
- To use digital elevation models and create their derivative products (i.e. slope, orientation);
- How to evaluate the interaction between different types of geodata through overlay and interaction techniques;
- How to create effective maps based around the rules of graphic semiology;
- Finally, we will also explore other, increasingly common, forms of spatial representation such as interactive web-mapping and 3D representations.
Syllabus
Week 1
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.
Week 2
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.
Week 3
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.
Week 4
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.
Week 5
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).
Week 6
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.
