Kaisa_2012_3_photo by Veikko Somerpuro

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Timetable

Here is the course’s teaching schedule. Check the description for possible other schedules.

DateTimeLocation
Mon 13.1.2020
09:15 - 11:45
Mon 20.1.2020
09:15 - 11:45
Mon 27.1.2020
09:15 - 11:45
Mon 3.2.2020
09:15 - 11:45
Mon 10.2.2020
09:15 - 11:45
Mon 17.2.2020
09:15 - 11:45

Description

Compulsory in the USP-SYSTEMS line

USP/Architecture programme is responsible for the course

Belongs to the USP-300

Is available to students from Geography programme, but the number of students may be limited (applications via JOO-system).

The course UrbanGIS needs to be passed

  • Understand the principles and methods of varying spatial data formats and live data resources.

  • Create on overview of open data repositories and use of open application programming interfaces.

  • Understand the basic concepts of spatial data analysis and get familiar with structural details such as distributions, noise, randomness, spatial autocorrelation and patterns.

  • Apply learned skills to use multiple industry standard data to acquire sufficient data for urban planning exercise.

Recommended time for completion: first year

The course is offered in spring term, period 3.

The course equips participants with tools to acquire, analyze and simulate spatial data, and use this data input for urban research and planning exercises. By the end of the course participants are familiar with available spatial data formats and are capable on analyzing the availability and quality of open data sources. Participants will understand the software and hardware specifications required for specific data types. The emphasis will be on rapid development of specifications, data acquisition and requirements for simulation and visualization. The course is supported by USP industry partners who offer the most recent insight on daily use of spatial data in planning practice.

Specifications and technical documentations defined in lectures.

  • Lectures

  • Class discussions supported by industry partners and guest lecturers

  • Hands-on data acquisition exercises

Grading scale 0-5. Course completion is based on successfully accomplished weekly exercises. No exam.

Total 135 hours. Tutored studies 35 hrs (lectures, class assignments, feedback reviews), independent study 100 hrs (exercises and assignments).