Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), 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: 08.09.2020 - 15.10.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Petri Rönnholm
Teacher in charge (applies in this implementation): Petri Rönnholm
Contact information for the course (applies in this implementation):
petri.ronnholm@aalto.fi
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: Finnish, Swedish, English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
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 01.08.2020-31.07.2022:
Examination and assignments
Applies in this implementation:
Because of COVID-19 situation, the final examination is replaced with weekly Quizzes and a learning diary.
Workload
Valid 01.08.2020-31.07.2022:
Lectures (20 h), assignments (58 h), self-study (30 h), preparation for examination + examination (27 h)
DETAILS
Study Material
Valid 01.08.2020-31.07.2022:
Lecture notes and additional literature
Substitutes for Courses
Valid 01.08.2020-31.07.2022:
Maa-57.3110 Käytännön kaukokartoitus (6 op) OR Maa-123.3520 Principles of Geostatistics (3 cr) AND Maa-123.3410 Fuzzy Modeling of Geographic Information (4 cr)
SDG: Sustainable Development Goals
9 Industry, Innovation and Infrastructure
11 Sustainable Cities and Communities