This repository contains the project of the cityLabor seminar course at WWU Münster WiSe 21/22.
In this project, a web application was developed for urban gardeners. It aims to help them in two ways: based on the user's location and garden size, the app helps to 1) determine what plants are suitable to plant, and 2) determine at what time of the year a plant should be planted. The recommendations for "What to plant" are based on a Survival Analysis function with an ROC of about 74% and a Köppen-Geiger Climate Map. The recommendations for "When to plant" are solely based on filtering our extensive dataset, which was webscraped from a north-american gardenplanner website featuring 259 popular plants for gardening. The application covers a major extent of the European area. Feel free to visit here
New people who are trying to get into the urban gardening world often don't have a background in this field and lack the knowledge of how to grow their desired plants. This is a difficult issue, because growing plants is an activity that requires awareness of many parameters, such as e.g. the available space and climate influence. Our application makes it easy and intuitive for users to make important decisions in terms of what and when to plant. Just by specifying some fields the user gets an overview of what is possible for his location and can choose from our recommendations. Users of our application need no preliminary experience with growing plants and are able to inform themselves in a very quick and easy manner.
- Huriel Reichel
- Simon Meissner
- Merel Vogel
- Eesha Ahluwalia
- Jonas Raabe
Our app was developed only using the R programming language and the Shiny package to build our web dashboard. By following these instructions you can install this repository to edit code locally and test our app in localhost.
git clone https://github.com/SimonMeissner/citylabor-project.git- Navigate to the cloned directory in your preferred environment, e.g. RStudio
shiny::runApp()
We are not liable for any of the received recommendations or outcomes that are based on them