MaCT01 22/23 Digital Tools & Big Data III

INTRODUCTION TO SPATIAL ANALYSIS

Credits: www.fsm.ac.in/

With data analysis, data visualization and machine learning skills, we are finally ready to go deep into our main subject of study: space.

If the world today is driven by data, urban planning and design are no different. And being able to use this data in the profession of urban planner is what will enable us to design cities that are better and more adapted to this dynamic world.

The Digital Tools & Big Data III course program aims to bring the use of data for spatial planning and analysis, presenting the GIS possibilities, the different types of file formats, geometries, spatial operations, and how we can apply Machine Learning to these concepts.

At the end of the course, students are expected to be able to work with spatial archives, enrich them with data and be able to use the strategies seen throughout the course, including the first two terms, in their work as urban planners.

Learning Objectives

At course completion the student will:

• Understand the basic concepts of GIS, coordinates, projections, file formats and geometry types;
• Manage spatial files with Python, enrich them, edit them and use their possibilities;
• Understand the concept of spatial aggregation and use it for data analysis;
• Understand the concept of Network and how to apply them to spatial analysis;
• Understand what are isochrones and neighbours and be able to work with them;
• Design and use maps as a tool for analysis and urban design;
• Apply machine learning to an urban analysis project;