Spatial data analysis | Institute of Geosciences

Title of course: Spatial data analysis

Code: TTGMG7044_EN

ECTS Credit points: 2

Type of teaching, contact hours

- lecture: -

- practice: - 2 hours/week

- laboratory: -

Evaluation: exam

Workload (estimated), divided into contact hours:

- lecture: -

- practice: 28 hours

- laboratory: -

- home assignment: -

- preparation for the exam: 16 hours

Total: 30 hours

Year, semester: 2 nd year, 4 th semester

Its prerequisite(s): -

Further courses built on it: -

Topics of course

The aim of the course is to demonstrate the possibilities of geospatial analysis through socioeconomic phenomena. Beyond simple visualisation, it aims to present the related methodology through practical exercises in vector datasets and specific analysis techniques for larger attribute sets. This includes a strong emphasis on hot spot analysis, spatial clustering, autocorrelation studies, the use of grid networks, and network analysis methods. The following topics will be covered: socio-economic spatial data and their management I - overview of data types, socioeconomic measures, spatial data; socio-economic spatial data and their management II. - data types, socio-economic measures, spatial data analysis; aggregation and disaggregation operations in QGIS and ArcGIS, operations using grid networks; point density analysis, hotspot analysis in QGIS and ArcGIS; spatial regression and spatial autocorrelation studies in ArcGIS and GeoDa software; spatial clustering operations, application and spatial representation of multivariate methods in QGIS and ArcGIS; using Network Analyst, basics of graph analysis, network analysis features, some metrics; using Network Analyst, calculation of accessibility metrics, attractiveness studies, facility location issues; using Network Analyst, community-detection issues based on commuting matrix.

Literature

• Netrdová, P. – Nosek, N. – Hurbánek, P. (2020): Using Areal Interpolation to Deal with Differing Regional Structures in International Research. International Journal of GeoInformation 9 (126): 1–14. https://doi.org/10.3390/ijgi9020126 
• https://desktop.arcgis.com/en/arcmap/latest/tools/spatial-statistics-to…outlier-analysis-anselin-local-moran-s.htm 
• Anselin, L. (1995): Local Indicators of Spatial Association-LISA. Geographical Analysis 27 (2): 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x

Requirements:

- for a signature

Attendance at lectures is highly recommended.

- for a grade

The course ends in a writing examination. The minimum requirement for the test respectively is 50%. Based on the score of the test, the grade for the test is given according to the following table:

If the score of any test is below 50, students can take a retake test in conformity with the EDUCATION AND EXAMINATION RULES AND REGULATIONS.

Person responsible for course: Dr. János Pénzes, PhD, Associate Professor