About the Project:

High Level Requirements:

1. User Friendly Interface: An intuitive interface accessible by non-technical users, particularly forest service managers and researchers.
2. Data Visualization: The system should display complex bird prediction data in an easy to understand format.
3. Scalability: The system should be able to handle large datasets at different scales of analysis such as local, regional, and national.
4. Exportable Results: Users should be able to export results as CSV or other geospatial files for further analysis and research.
5. Data Querying and Filtering: Users should be able to filter data by various attributes, such as location, species, time range, and other relevant parameters.
6. Data Storage: The database must be easy and quick to access, while also being secure and reliable.

Solution:

FireFlight is a web-based application designed to assist forest service managers and researchers to easily visualize and understand predicted bird presence data. Calculated from data collected over the past ten years, this tool will help the Forest Service to decide which management methods are the most effective, and how often they should be used.

Key features include an interactive map showing the predicted bird presence for an area, and the option to export the displayed results as an easy to read CSV file. The map features a heat map overlayed onto a map of the United States, with a legend that explains the color scale of the heat map. Using the querying options, different data on different bird species can be displayed and exported using our tool.

Our application:

Examples of different species predicted presence:

Technologies:

• Front-End: HTML/CSS/JavaScript - We chose to use the core web-based technologies HTML, CSS (Bootstrap), and Javascript for the front-end of our application. HTML provides the foundational structure for content and navigation, while CSS ensures a clean and user-friendly design. We opted to use the Bootstrap CSS library to streamline the styling process. JavaScript is responsible for making the interface responsive and interactive. These are well-established web development tools that ensure compatibility across various web browsers. They also allow for simple integration with back-end and visualization frameworks.
• Back-End: Django - Because of its robust features and rapid development capabilities, we chose Django for our back-end. Django is a high-level, Python web framework that encourages rapid development and comes with built-in database integration. Django's built-in security features, scalability, and compatibility with other Python libraries make it an ideal choice for our project.
• Database: MySQL - For data storage, we are using MySQL. MySQL is a high-performance database system with the tools and resources we need to efficiently retrieve relational data used in our project. It is open-source, and has extensive documentation available for reference. It is a relatively simple and straightforward database management system, which is perfect for the data we are storing.
• Mapping & Data Visualization: Folium - For mapping and data visualization, we chose Folium. It is a Python library that allows for the creation of interactive maps using Leaflet.js. Folium is a powerful tool that allows for the integration of geospatial data from various sources, making it easy to visualize complex data in a user-friendly format. We chose Folium because it simplifies the process of embedding maps in a web-based application, that also works well with other Python libraries.
• Version Control: GitHub - Version control is managed via GitHub, which enables our team to collaborate efficiently by tracking changes. GitHub's branching and pull request features help us manage our codebase with minimal conflicts. GitHub is a powerful collaboration tool that empowers our team to work together effectively and efficiently.