BloomWatch AI 🌸

Real-Time Global Vegetation Analysis and Anomaly Detection

BloomWatch AI is an interactive web application developed for theNASA Space Apps Challenge to monitor the health and seasonal changes of global vegetation using NASA satellite data. It provides instant anomaly detection and long-term time-series analysis, empowering users to track environmental changes without needing specialized GIS software.

Table of Contents

Important Links

1. 🚀 Challenge and Theme
2. ✨ Key Features
3. 💻 Technologies Used
4. 🛰️ NASA Data & Resources
5. 🛠️ Getting Started
6. 💡 Project Summary

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Important Links

1. Global Nasa Hackathon
2. 2025 Challeneges
3. Team- Last Minute Runner
4. Project Detail
5. Demo Video

🚀 Challenge and Theme

This project addresses the BloomWatch challenge. The goal was to create an accessible tool that utilizes satellite imagery to monitor and analyze changes in global vegetation cover, specifically focusing on identifying anomalies (unusual greening or drying) that indicate environmental stress or major bloom events.

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✨ Key Features

BloomWatch AI provides a simple, structured interface (using Streamlit Tabs) to access complex geospatial analysis:

• Anomaly Detection: Instantly calculates and visualizes the difference between the current year's and a historical reference year's vegetation index (NDVI/EVI). This highlights areas that are significantly greener (positive anomaly) or drier (negative anomaly).
• NDVI/EVI Time-Series Trend: Generates a clean, interactive line chart showing the long-term average index value for any selected region across a range of years, aiding in climate trend analysis.
• Flexible Area of Interest (AOI): Allows users to select regions by name or use the integrated Folium drawing tools (pencil icon on the map) to define and analyze any custom geographic area.
• Interactive Mapping: Provides dynamic visualization of NDVI and EVI layers with customizable color palettes.

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💻 Technologies Used

Category	Tool / Language	Role in Project
Data Platform	Google Earth Engine (GEE)	Cloud computing platform for processing large-scale satellite data.
Primary Language	Python	Core logic and data manipulation.
Web Framework	Streamlit	Built the fast, interactive, and user-friendly web application interface.
Mapping	geemap (Folium backend) & folium.plugins	Interactive map creation and integration of user drawing tools.
Libraries	Pandas, NumPy	Data preparation and statistical analysis for charts.

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🛰️ NASA Data & Resources

To be eligible for the Global Award, BloomWatch AI relies entirely on open NASA satellite data products:

Resource Name	Data Used	Link
MODIS/Terra Vegetation Indices (MOD13Q1 V6.1)	NDVI and EVI layers (250m resolution) for all time-series and anomaly calculations.	https://doi.org/10.5067/MODIS/MOD13Q1.061
GEE Data Catalog	The cloud-hosted access point for querying and processing the MODIS product.	https://developers.google.com/earth-engine/datasets/catalog/MODIS_061_MOD13Q1
NASA Earthdata	Core documentation and scientific context for Vegetation Indices.	https://www.earthdata.nasa.gov/topics/biosphere/vegetation-index

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🛠️ Getting Started

Prerequisites

1. Python (3.8 or higher)
2. Google Earth Engine (GEE) Account: You must have initialized Earth Engine on your system.

Installation

1. Clone this repository:

   git clone https://github.com/muhammadfahd/Bloom-Watch-AI.git
   cd Bloom-Watch-AI

2. Install the required Python packages:

   pip install -r requirements.txt
   # Alternatively, manually install the main dependencies:
   # pip install streamlit geemap pandas numpy ee

3. Ensure your Earth Engine credentials are set up (if running for the first time outside a GEE environment):

   ee authenticate --google

Running the App

Run the Streamlit application from your terminal:

streamlit run bloomwatchai.py

The app will open automatically in your web browser.

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💡 Project Summary

BloomWatch AI provides a powerful and intuitive platform for environmental monitoring. It successfully integrates complex GEE geospatial analysis (including the fixed caching issues for unhashable geometries) into a user-friendly web interface, making high-value NASA data accessible to a global audience for tracking climate impacts and bloom dynamics.