Project Overview: SpiderSense is a web-based farming simulation game designed to help farmers in Bangladesh make informed decisions under climate uncertainty. The game focuses on wheat cultivation and simulates three critical stages: sowing, flowering under heat stress, and harvesting under flood risk.
How It Works:
- Integrates NASA satellite data: soil moisture (SMAP), land surface temperature (MODIS), and flood forecasts (Flood Data Pathfinder).
- Players make decisions on sowing, irrigation, and harvesting, with outcomes affecting yield, profit, water efficiency, and crop resilience.
- Real-time data visualization allows users to understand climate risks and resource management.
Technical Details:
- Frontend: React with TypeScript, styled using Tailwind CSS.
- Backend: Express.js.
- Data Processing: Python notebook (
data_read_from_datasets) reads and preprocesses satellite datasets.
Start the Game:
- Use Node.js version 20 or lower
- Open terminal
- Run
npm run dev - Access the game at localhost:5000
Creativity & Impact:
- Simplifies complex satellite data into an engaging, interactive game.
- Helps farmers understand and respond to climate variability.
- Promotes sustainable agriculture, risk management, and resource efficiency.
Intended Impact: SpiderSense empowers farmers to make data-driven decisions, improving crop outcomes, conserving water, and increasing resilience against climate threats.