BloomWatch
An Earth Observation Platform for Monitoring Global Blooming Phenology NASA Space Apps Challenge 2025 – Top 15 Project
🚀 Overview
BloomWatch is a web-based platform that leverages NASA Earth observation data, satellite imagery, and intelligent data analytics to monitor, detect, and visualize blooming (flowering) events and vegetation phenology around the world. This tool helps researchers, environmentalists, and agricultural planners understand how ecosystems respond to environmental changes over space and time. cps.sp.gov.br +1
🧠 Motivation
Plant blooming is a crucial ecological indicator — it reflects:
seasonal changes
biodiversity health
effects of climate variability on plant life
Understanding and tracking these patterns at a global scale provides critical insights into ecological resilience and informs environmental policy. BloomWatch was developed to transform raw satellite data into actionable, interactive insights for users across disciplines. cps.sp.gov.br
📊 Key Features
✔ Global Bloom Detection & Visualization Interactive temporal–spatial maps showing bloom intensity and timing across regions.
✔ Satellite Data Integration Uses open NASA Earth data (e.g., NDVI or other vegetation indices) to analyze and detect vegetation changes. cps.sp.gov.br
✔ Climate Correlation Dashboard Visual tools to explore how climatic variables influence phenological patterns.
✔ AI & Machine Learning Support Incorporates smart prediction models (optional) to forecast bloom events and identify trends.
✔ User-Friendly Interface Accessible for researchers, scientists, students, and even non-technical users.
📦 Technology Stack
Frontend
React / HTML / CSS / JavaScript Backend
Python (Flask / FastAPI)
Data processing with pandas, numpy Data Sources
NASA Earth Observation APIs / satellite imagery Visualization
D3.js / Chart.js / GIS mapping (depending on implementation)
(Modify this section based on your actual stack.)
🛠 How It Works
Data Collection Fetch remote sensing data from NASA sources for vegetation indices.
Preprocessing Clean and organize satellite imagery time-series.
Bloom Detection Compute bloom signatures using vegetation indices like NDVI and temporal change detection.
Visualization & UI Map and chart interactive phenological events on a dashboard.
Optional ML Integration Use AI to identify patterns and predict bloom shifts.