This is an advanced course focusing on analysing the first and second-order relationship between observations geospatially. The course will introduce analysis techniques utilising both R studio and QGIS. The session will last appropriately 2 hours covering the following headings,
- Introduction to Point Pattern Analysis
- Density-based vs distance-based analysis (relationship with 1st order and 2nd order dynamics)
- Kernel Density Estimation (KDE)
- Nearest Neighbour Analysis (NNA)
- Ripley’s K-Function
To access the course materials, please download all folders and files from the repository.
- .ppt presentations used during the course
- example code (Spatial Dynamics)
- gis file (project.qgz)
- shapefile (Boundary for determining the extent of analysis)
- shapefile (bike_theft_2023 for performing the analysis)
The csv and the gis_data folder are exercise files that you will need for the exercise. Project.qgz is the file for performing KDE and NNA. The SpatialDynamics R file contains the codes for performing Ripley's K-Function. The powerpoint has a summary of the presentation in class and contains descriptions for the fundamentals regarding point pattern analysis and their applications. We hope you will find the course useful.