For students:

Spatial Methods and Satellite Data (3 cr)

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Code:
no code
Field:
Empirical methods
Targets:
Research Master's students PhD students
Instructor:
Dr. Tillmann von Carnap (University of Oslo )
Period:
Period 5
Format:
Lecture
Method:
Contact teaching
Venue:
UNU-WIDER Library, Katajanokanlaituri 6 B, Helsinki
Enrollment:
Registration form

Before taking and completing the course make sure that the credits can be counted towards your degree at your home university by checking which courses are included in your curriculum or by contacting your home university’s student/learning services.

Course description

Helsinki GSE, in collaboration with UNU-WIDER, is organizing a three-day intensive mini-course on spatial methods, with a focus on accessing and utilizing open-source satellite data for economic research. Such data is increasingly used in applied economics research, including in fields such as development, environmental and urban economics. Examples include geolocations of survey respondents, gridded weather and environmental data (such as particulate matter concentrations or air temperature) or high-resolution satellite images allowing the identification of phenomena such as informal settlements, periodic marketplaces or traffic. 

Effectively working with such data requires an understanding of the underlying geospatial concepts, the available data sources and appropriate processing tools. Combining theoretical and practical sessions, the course will provide participants with a solid foundation, enabling them to use spatial data in their own work.

Learning outcomes

After the course, students will be able to:

  • identify and manipulate common formats of spatial data (both vector-based and rasters) using open-source software, specifically QGIS.
  • evaluate various available spatial data products and determine their advantages for specific economic applications, including optical satellite imagery, remotely-sensed environmental data, and OpenStreetMap.
  • implement large-scale data handling and integration into analytical workflows using GoogleEarthEngine, including the definition and extraction of information from areas of interest, image manipulation, change detection, and supervised/unsupervised classification of raster data.
  • critically analyze and apply recent research that utilizes spatial data within the field of economics.

Evaluation

Students are able to get credits for the course (3 ECTS). Participants will be examined (pass/fail) based on a written research proposal that includes at least some of the methods taught in the course.  The proposal will be due two months after the course. After passing the course, you will receive a certificate. If you want to include the credits in your degree, please apply for credit transfer in Sisu. For more information, please contact jenni.rytkonen@aalto.fi.