LEARNING OUTCOMES
The student can identify appropriate analysis approaches for different geospatial tasks and describe data needs and suitable methods for the analysis process. The student understands the basic principles of spatial data structures and algorithms. The student can apply modeling techniques and algorithms, as well as spatial extensions of standard statistical, mathematical, and computational methods to solve spatial problems in Python. The student can evaluate the suitability of solutions and assess the quality of geographical data. The student can discuss the strengths and limitations of the methods.
Credits: 6
Schedule: 03.09.2024 - 28.11.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Jussi Nikander, Henrikki Tenkanen
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:
The course introduces various mathematical, statistical and computational methods in their spatial forms. The contents cover spatial data modeling methods, data management and maintenance as well as spatial algorithms, data structures, and indexing methods. The course covers various methods and techniques related to processing and analysis of spatial data including measures of autocorrelation, spatial statistics, spatial interpolation, data classification, network analysis and clustering methods, map algebra, geostatistics, and geometric problem solving. In addition, different quality concepts and measures, as well as visual analysis and multivariate visualization techniques are covered in the course.
Assessment Methods and Criteria
valid for whole curriculum period:
Examination and assignments
Workload
valid for whole curriculum period:
Lectures (40 h), assignments (20 h), self-study (82 h), preparation for examination + examination (20 h)
DETAILS
Study Material
valid for whole curriculum period:
Lecture notes and additional material
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
4 Quality Education
9 Industry, Innovation and Infrastructure
11 Sustainable Cities and Communities
15 Life on Land
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn I - II
2025-2026 Autumn I - IIRegistration:
Registration for the courses via Sisu (sisu.aalto.fi).