Data-Driven-Map-Visualization-Web-App

During 2019 - 2020 summer season in Australia, aka the bush fire season, 46 million acres of land was burnt, 5900 buildings were destroyed and about 3 billion terrestrial animals and 34 people died in these wild fires. This had a huge impact on the Australian economy and the wild life.

The goal of this web-based application is to understand the spread of bushfires across different regions, based on the corrdinates and time-series data, by generating map visualisations.

Web-page: https://datadriven-map-visualization.herokuapp.com/

Contributors

Mourya Polaka

Vivek Velivela

Frameworks

• Flask
• Folium
• Pandas

Instructions

• This platform accepts CSV data as input to generate map visualisations.
• The map visualisation funtion for the Bushfire spread takes in a dataset with 3 columns; latitude, longitude and date (format - dd/mm/yyyy). This function generates a time-series heat-map generated by Folium.
• The plot-coordinates function takes in latitude, longitude, location (name of the place) and generates a map with marker plots.
• The temperature function takes in the name of the state, average temperature and date (format - dd/mm/yyyy) to generate a Choropleth time-series map.(Note: this function is still under development)

Run on local machine

Alternatively, you can run this web-app on your local machine by following these instructions.

1. Clone the repository

$ git clone https://github.com/mouryapolaka/Data-Driven-Map-Visualization-Web-App.git

2. Create a virtual environment

$ python3 -m venv <path of your Data-Driven-Map-Visualization-Web-App directory>
$ cd <path of your Data-Driven-Map-Visualization-Web-App>
$ source bin/activate

3. Install the requirements

$ pip3 install -r requirements.txt

4. Run the application

$ python3 application.py

Click on the generated local host IP address to view the website on your browser.