Hyggebike 🚲

Exam project for Geospatial Data Science - By Mads Høgenhaug, Marcus Friis & Morten Pedersen

Introducing Hyggebike: A framework to get the hyggeligste route from point A to point B. Based on various factors such as nearby birds, trees and noise, we compute a "hygge score" for each road. This hygge score used in the shortest path computation from A to B, such that we find the path with 🔥maximum hygge🔥.

Overview

This repository contains and documents all steps in creating the _Hygge_bike pathfinder. There are 4 important notebooks that produce our results

• bird-edges.ipynb --> bird_edges.csv
• tree-edges.ipynb --> tree_edges.csv
• noise-edges.ipynb --> noise_edges.csv
• hyggefinder.ipynb --> Hyggebike pathfinding algorithm 😎

The first 3 notebooks wrangle and proces spatial data to produce edge level features, used for creating the algorithm. The last notebook, hyggefinder.ipynb, produces the actual pathfinding algorithm and all other results. All notebooks are run using the Docker Image gds_py:8.0.

Data

We use various datasets for this project. All are briefly described here.

Bird observations

Bird observations originate from DOFbasen. It cotains an entry for each bird observation registered by users. We use bird observations in Copenhagen between 2020 and 2024.

Trees

The tree data contains all municipal trees in Copenhagen municipality. It is downloaded from Open Data DK. Due to it being for Copenhagen municipality, it does not have data for Frederiksberg.

Noise

The noise data comes from Copenhagen municipality. It contains projected traffic noise for areas of Copenhagen, excluding Frederiksberg.
Noise data for Copenhagen municipality only. It can be downloaded from Opendata.dk. The data is displayed at Copenhagen's Municipality's website.