Virdis - Sorry for the issues lately, hopefully the fix will be there soon

Virdis is a satellite-powered agricultural and land analytics platform that combines Sentinel-2 satellite imagery, Google Earth Engine processing, real-time weather data, soil science databases, and AI-driven crop planning into a single web dashboard.

Users draw polygonal regions on an interactive map and receive vegetation health analysis (NDVI), climate analytics, soil profiling, air quality data, land use classification, land suitability scoring, and AI-generated crop planning recommendations.

Preview

What Virdis Does

Virdis enables users to:

• Map and manage regions on an interactive satellite map with polygon drawing tools
• Monitor vegetation health using NDVI analysis from Sentinel-2 10m resolution imagery
• Access detailed soil health profiling from the ISRIC SoilGrids database
• Monitor air quality with PM2.5, PM10, and AQI readings
• Classify land use from ESA WorldCover satellite data via Google Earth Engine
• AI-based crop planning with visual field layouts, intercropping strategies, and crop rotation plans
• Compare two regions side-by-side with synchronized analytics charts
• Export crop plans as PDF documents

Key Features

Interactive Satellite Mapping

• Satellite and dark basemap styles powered by Mapbox GL JS
• Polygon drawing with a pen tool for custom region boundaries
• Region editing and deletion with boundary modification
• Fly-to animations when selecting regions from the list
• NDVI overlay from Google Earth Engine tile service
• Location search with Mapbox geocoding and reverse geocoding
• Auto-detection of region type (rural vs urban) using GEE land use data

NDVI Vegetation Analysis

Sentinel-2 imagery is processed through Google Earth Engine to calculate the Normalized Difference Vegetation Index. This NDVI data is displayed as a semi-transparent raster layer above the satellite basemap,

NDVI = (NIR - Red) / (NIR + Red)

NDVI Range	Vegetation Status
Below 0.2	Critical / bare soil
0.2 to 0.4	Stressed vegetation
0.4 to 0.6	Moderate vegetation
Above 0.6	Healthy vegetation

Climate Analytics Dashboard

Per-region weather analysis with current conditions, precipitation trends (incl. evapotranspiration), temperature ranges, soil moisture (surface & deep), and selectable date range

Air quality monitoring with AQI , PM2.5 levels, and color-coded indicators.

Soil Health Profiling

Soil data fetched from the ISRIC SoilGrids REST API at 250m resolution:

• Soil classification (WRB taxonomy) with descriptions and icons
• pH measurement with rating
• Organic carbon content
• Total nitrogen content
• Cation exchange capacity (CEC)
• Bulk density
• Coarse fragment percentage
• Soil composition (sand, silt, clay percentages) with USDA texture class
• Water retention: field capacity, wilting point, available water capacity
• Donut chart to visualize soil composition

Land Use Classification

ESA WorldCover 10m land cover classification via Google Earth Engine:

• Cropland, tree cover, grassland, shrubland, built-up, water, bare/sparse, wetland, snow/ice, mangroves, moss/lichen
• Interactive donut chart with percentage breakdown
• Used for urban region detection (30%+ built-up area triggers urban mode)
• Water body edge case detection (80%+ water blocks crop planning)

Land Suitability Scoring

Radar chart of six land suitability metrics :

• Soil quality (from SoilGrids data)
• Water access (rainfall and soil moisture)
• Climate suitability (temperature and precipitation patterns)
• Topography (elevation and slope from SRTM 30m DEM)
• Drainage assessment
• Nutrient level scoring

AI Crop Planning

Dual-approach crop planning system:

Local Agronomy Model

A client-side scoring engine with 50+ crop profiles that runs immediately:

• Detects climate region from location text (tropical, Mediterranean, temperate, arid, continental, highland, coastal, humid, subtropical)
• Scores each crop against field signals: temperature, rainfall, soil pH, NDVI health, water index, humidity, soil quality, climate quality, topography
• Allocates area proportionally to suitability scores (best crop gets 40-55%, not equal splitting)
• Generates intercropping pairs and 3-season rotation plans
• Penalizes crops that do not match the detected climate region

Planner (Background)

Calls Google Gemini 2.5 Pro with full field context (NDVI, soil, weather, suitability, land use data). The AI response replaces the local model when available.

Crop Visualization

• Satellite minimap showing the field boundary on Mapbox satellite imagery
• Static dot grid fills the entire field polygon with crop markers using point-in-polygon testing
• Variable dot sizes: trees get 16px dots, small grains get 7px
• Color-coded legend with crop filtering (click to show/hide individual crops)

Plan Outputs

• Zone allocation pie chart with percentage breakdown
• Per-zone details: area percentage, spacing, water needs, yield estimate, season, reasoning
• Intercropping pair suggestions with spacing guidance
• 3-season crop rotation plan with current season highlighted
• Water saving percentage and revenue boost estimates
• PDF export of the complete crop plan

Edge Case Detection

The system detects unsuitable regions and blocks crop planning:

Edge Case	Detection Method	Threshold
Water bodies	ESA WorldCover "Water" land use percentage	80% or more
Extreme deserts	Annual rainfall from CHIRPS via GEE	Below 50mm, or keyword match (Sahara, Atacama, etc.)
Polar regions	Average latitude of polygon coordinates	Above 66 degrees, or keyword match (Antarctica, etc.)
High altitude	Elevation from SRTM via GEE	Above 5000m
Urban regions	ESA WorldCover "Built-up" percentage	30% or more (switches to urban analytics mode)

Region Comparison

• Side-by-side comparison of two regions with synchronized charts
• Selectable comparison target from existing regions
• Independent chart rendering per region

Architecture

User / Browser
      │
      ▼
   Frontend
React + Mapbox GL JS + Tailwind + shadcn
      │
      ▼
Edge Functions (Supabase - Deno)
      │
 ┌───────────────┬───────────────┬───────────────┬───────────────┬───────────────┬───────────────┐
 ▼               ▼               ▼               ▼               ▼               ▼               
Mapbox Token   Field Analysis   Land Analytics  NDVI Tiles      NDVI Series     Soil Data
(Mapbox API)   (GEE + AI)       (GEE)           (GEE)           (GEE)           (SoilGrids)
                   │               │               │               │               │
                   ▼               ▼               ▼               ▼               ▼
             AI Crop Planning   Land Use        Tile Service    Time-Series     Soil Properties
             (Gemini 2.5 Pro)   + Suitability                                   (250m)
                   │
                   ▼
            Crop Recommendations

      │
      ▼
External Data Sources
      │
 ┌───────────────┬───────────────┬───────────────┬───────────────┐
 ▼               ▼               ▼               ▼               ▼
Google Earth    Open-Meteo     SoilGrids       Mapbox         Sentinel-2 
Engine          (Weather)      (Soil Data)     (Maps API)    ESA WorldCover
                                                              SRTM • CHIRPS

Tech Stack

Layer	Technology	Purpose
Frontend	React 18 + TypeScript 5	UI framework with type safety
Build Tool	Vite 5	Development server and production bundling
Styling	Tailwind CSS 3 + shadcn/ui (Radix primitives)	Utility-first CSS with accessible component library
Mapping	Mapbox GL JS 3	Interactive 3D satellite map rendering
Charts	Recharts	Data visualization (area, bar, line, pie, radar charts)
Routing	React Router 6	Client-side SPA navigation
Server State	TanStack React Query 5	Async data fetching and caching
Backend	Supabase Edge Functions (Deno)	Serverless API endpoints
Satellite	Google Earth Engine	Sentinel-2 NDVI, ESA WorldCover, SRTM, CHIRPS
AI	Google Gemini 2.5 Pro	Crop planning and field analysis
Weather	Open-Meteo	Current forecast, historical archive, air quality
Soil	ISRIC SoilGrids	Soil properties (pH, carbon, nitrogen, texture)
PDF	jsPDF	Client-side PDF export of crop plans
Animations	tailwindcss-animate	UI transition animations

Data Sources and APIs

Satellite and Earth Observation

Source	Resolution	Data Provided	Usage
Sentinel-2 (via GEE)	10m multispectral	NIR and Red bands	NDVI vegetation health analysis
ESA WorldCover (via GEE)	10m land cover	11 land cover classes	Land use classification, urban/water detection
SRTM (via GEE)	30m elevation	Digital elevation model	Elevation, slope, topography scoring
CHIRPS (via GEE)	5km rainfall	Daily rainfall estimates	Annual precipitation for suitability analysis

Weather and Climate

Source	Endpoint	Data Provided	Usage
Open-Meteo Forecast API	/v1/forecast	Current temperature, humidity, wind, weather code, feels-like, soil moisture	Real-time conditions and soil moisture display
Open-Meteo Archive API	/v1/archive	Historical daily precipitation, temperature range, evapotranspiration, soil moisture	Climate analytics charts with configurable date range
Open-Meteo Air Quality API	/v1/air-quality	PM2.5, PM10, European AQI, US AQI	Air quality monitoring cards

Soil Science

Source	Endpoint	Data Provided	Usage
ISRIC SoilGrids	REST API at 250m resolution	pH, organic carbon, nitrogen, bulk density, CEC, sand/silt/clay texture, coarse fragments, water retention (field capacity, wilting point, available water)	Soil health profiling, texture pie chart, crop suitability input

Mapping and Geocoding

Source	Data Provided	Usage
Mapbox GL JS	Vector and satellite tile rendering	Interactive map with satellite basemap
Mapbox Geocoding API	Forward and reverse geocoding	Location search bar, auto-detection of region location

AI

Source	Model	Usage
Google Gemini 2.5 Pro	Large language model	Crop planning with native plant enforcement, field analysis, region-specific recommendations

Edge Functions

Function	Method	Input	Output	External Calls
get-mapbox-token	POST	(none)	{ token }	Reads MAPBOX_TOKEN secret
analyze-field	POST	polygon coordinates, field metadata, weather, soil data	NDVI stats + AI analysis text	GEE (Sentinel-2 NDVI), Gemini 2.5 Pro
gee-analytics	POST	polygon, analyses array	land_use, vegetation, suitability objects	Google Earth Engine (WorldCover, Sentinel-2, SRTM, CHIRPS)
gee-ndvi-tiles	POST	polygon, date	Tile URL template	Google Earth Engine
ndvi-timeseries	POST	polygon	90-day NDVI array, growth stage, growth rate, canopy cover, biomass	Google Earth Engine (Sentinel-2)
soil-data	POST	lat, lon	classification, metrics, texture, water_retention	ISRIC SoilGrids REST API
crop-planning	POST	field name, crop, area, location, coordinates, NDVI/soil/weather/suitability data	zones, intercropping, rotation_plan, summary, tips, scores	Gemini 2.5 Pro
keepalive	GET	(none)	{ status: "ok" }	(none)

📁 Project Structure

``` src/ ├── components/ │ ├── MapView.tsx # Main map with drawing, NDVI overlay, field rendering │ ├── MapToolbar.tsx # Left toolbar (zoom, draw, layers, NDVI, compass) │ ├── SidePanel.tsx # Right sidebar with field list & detail view │ ├── FieldDetailView.tsx # Per-field detail: weather, NDVI, soil, AI analysis │ ├── FieldCard.tsx # Compact field card for lists │ ├── FieldEditDialog.tsx # Edit field name, crop, color, group │ ├── FieldComparisonColumn.tsx# Side-by-side field comparison charts │ ├── WeatherView.tsx # Full analytics dashboard │ ├── CropPlanningSection.tsx # AI crop planning with map visualization │ ├── NewFieldDialog.tsx # Create new field from drawn polygon │ ├── SearchBar.tsx # Map search with geocoding │ ├── LocationAutocomplete.tsx # Location input with Mapbox suggestions │ ├── NdviLegend.tsx # NDVI color scale legend │ ├── Nd