RAVI
Sentinel-2 vegetation analysis. No code.

Analyze vegetation indices directly in QGIS

Authenticate with Google Earth Engine, select your AOI, compute vegetation indices, explore interactive time series, and export results — all without leaving QGIS.

View on GitHub How it works

Overview

Remote Analysis of Vegetation Indices

RAVI is a QGIS plugin that integrates with Google Earth Engine to process and visualize Sentinel-2 surface reflectance data — vegetation index calculation, visualization, and multispectral image download.

Features

Core Features

A complete workflow for vegetation analysis in QGIS with Google Earth Engine integration.

🌿

Vegetation Indices

Compute NDVI, EVI, SAVI, and GNDVI for single dates or composite images.

☁

Earth Engine Integration

Authenticate, process, and visualize Sentinel-2 surface reflectance data directly in QGIS.

📊

Interactive Time Series

Plotly charts with hover and zoom — filter dates, smooth with Savitzky-Golay, and export as CSV.

🌧

NASA POWER Precipitation

Overlay monthly precipitation data for cross-variable comparison alongside your index series.

🌍

RGB & Composite Layers

Load full multispectral RGB imagery for a date or generate composite index rasters across a period.

📍

Points & Polygon Analysis

Run single-pixel point time series or multi-polygon analysis over your areas of interest.

Workflow

How It Works

A three-step workflow from authentication to vegetation insights in QGIS.

01

Authenticate

Set up your Google Cloud project ID and authenticate with Google Earth Engine through the plugin.

02

Configure & Run

Load your AOI, set the time range, choose a vegetation index and filters, then run to build the time series.

03

Visualize & Export

Explore interactive charts, load RGB or index layers, smooth the series, and export as CSV or GeoTIFF.

GEE Setup

Getting Started

Set up Google Earth Engine and configure RAVI to start analyzing Sentinel-2 data.

01

Create a GEE account

Sign up for free at earthengine.google.com.

→ Go to Earth Engine
02

Create a Google Cloud project

Create a new project and link it to your GEE account.

→ Google Cloud Console
03

Enable Earth Engine API

In Cloud Console, search for Earth Engine API and enable it.

→ Enable API
04

Find your project ID

Open the Earth Engine Code Editor to find your project ID.

→ Code Editor
05

Authenticate in RAVI

Open RAVI in QGIS, click Setup Authentication, enter your Cloud project ID, and authorize access.

Resources

Source, Support & License

Everything you need to use, troubleshoot, and contribute to RAVI.

💻

Repository

Browse the source code, releases, and documentation on GitHub.

→ Open repository
💬

Report Issues

Found a bug or have a suggestion? Open an issue and help improve RAVI.

→ GitHub Issues

Project

About the Project

RAVI began as the undergraduate final project (TCC) of Caio Arantes, developed under the supervision of Prof. Dr. Lucas dos Rios Amaral. Today it is a free and open-source project maintained with the support of FARM Analytica, committed to technology diffusion and the open-source philosophy.

Supported by FARM Analytica

Technology and field intelligence working together to support practical operations.

Talk on WhatsApp adm@farmanalytica.com.br
Speak with FARM about exclusive custom solutions

Academic supervision by Prof. Dr. Lucas Rios do Amaral and M.Sc. Isabella Alves da Cunha.