The project aims to address the challenge of accurately enumerating trees in forest areas earmarked for diversion due to developmental projects by developing an image analytics system utilizing satellite imagery or aerial photographs to automate tree enumeration. Traditional methods are time-consuming and prone to errors, making it crucial to develop an automated solution.
The project includes a website with a landing page and a dashboard offering the following tools:
- Tree Count: Allows accurate tree counting within designated forest areas(Using CNN AlexNet Model to produce density Map).
- Green Cover Estimator: Estimates green cover percentage.
- Google Map Image
- Optimal Pathing: Computes the optimal path between two points within the area (A star Algorithm).
- Historical Data: Provides historical data for analysis and comparison (Openweather historical weather).
- Landing Page: Showcases project overview with easy onboarding.
- Dashboard: Offers toggle switches to access various tools.
- Interface: User-friendly interface for easy interaction and exploration of results.
- Integration: Seamless integration with forest management systems.
- Visualization: Generates maps, reports, and visual representations of tree enumeration data.
- Clone the repository:
git clone https://github.com/your-username/your-repository.git