GIS-E1030 - Introduction to Spatial Methods D, Lecture, 6.9.2022-20.10.2022

Guest access
Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

To understand the spatial extensions of conventional statistical, mathematical and computational methods including the concept of spatial autocorrelation. To recognize the special requirements of geodetic, photogrammetric, remote sensing and GIS applications in spatial processing. To apply suitable spatial analysis methods in these applications. To evaluate the quality of geographical data. To be able to program simple algorithms in Matlab and R.

Credits: 5

Schedule: 06.09.2022 - 20.10.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Petri Rönnholm

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: Finnish, Swedish, English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    This course introduces various mathematical, statistical and computational methods in their spatial forms. The contents of the course cover processing, analysis and quality issues of spatial data including measures of autocorrelation, spatial statistics, convolution, spatial interpolation, data classification and clustering methods, geometric problem solving and spatial algorithms, and quality concepts and measures.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Examination and assignments

Workload

  • valid for whole curriculum period:

    Lectures, assignments, self-study, preparation for examination + examination

DETAILS

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    9 Industry, Innovation and Infrastructure

    11 Sustainable Cities and Communities

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Autumn I
    2023-2024 Autumn I

    Enrollment :

    Registration for the courses via Sisu (sisu.aalto.fi).

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof