Neat Geodata Stuff

2023-02-01

I'm working on a geodata analysis project. So I thought I'd share a few interesting links that have helped me along this project, for future reference (all links are https):

Selecting random points based on the distance between them

I struggled to come up with an algorithm that would help me avoid point clusters in locations with an abondance of points. This link above helped me come up with a solution using Geopandas.

Proximity analysis

This link, especially the last part of the page called 'Creating a buffer', was especially useful for implementing the solution detailed in the first link above. That is, to effectively reduce clusters of points, a buffer should be created around the points. Then each group of overlapping buffers is joined and dissolved to form one polygon. Then the point closest to the center is selected and removed.

I'm also planning on implementing a function that calculates the average distance between two sets of points, and this link also talks about calculating distances, so that might be useful.

Point in polygon

This wikipedia article explains how one can calculate if a point is in a certain polygon. It's conceptually easier than I had thought it would be!

Automating GIS Processes 2022

This is a graduate course from the University of Helsinki, the course material is available online for free! It seems that the 2022 is a revamped version of the course, as lesson 3 doesn't seem to allude to 'Nearest neighbour analysis` as was the case in the years before (this is also how I stumbled upon this course in the first place). Thus, it seems browsing through past years might be worthwile.

Some other interesting links in no specific order:

Voronoi Diagrams: Applications from Archaology to Zoology

Thorough explanation on Voronoi diagrams

How to create Voronoi regions with geospatial data

How to plot voronoi diagrams in python

Evenly distributing n points on a sphere

Probably won't use it for now but looks neat

The fascinating world of Voronoi diagrams

Explanation of Voronoi diagrams and cool visualisations

Lloyd's algorithm seems pretty interesting but with an additional step of deleting smallest polygons, or creating just the amount of polygons necessary for the n subset of points

Splitting polygon into equal area polygons using QGIS - Geographic Information Systems Stack Exchange

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