Extracting Drought Indicators using Google Earth Engine in Python

This repository provides a step-by-step guide for extracting drought indicators using Google Earth Engine (GEE) in Python. The workflow is implemented in a Jupyter Notebook format, which is particularly suited for use in Google Colab.

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📘 Overview

Monitoring and assessing drought conditions is critical for early warning systems and informed decision-making in climate-sensitive sectors. This repository demonstrates how to access and process remote sensing datasets via the Google Earth Engine Python API to derive drought-related indicators efficiently.

The notebook in this repository shows:

• How to initialize the Google Earth Engine Python API
• How to access relevant Earth observation datasets for drought monitoring
• How to compute basic drought indicators (e.g., NDVI anomalies, precipitation deficits)
• How to visualize and export the results

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🚀 Getting Started

1. Prerequisites

To run the notebook, you need:

• A Google Earth Engine account
  👉 Sign up here: https://earthengine.google.com/signup

• A Google account to access Google Colab:
  👉 https://colab.research.google.com/

2. Recommended Environment

The notebook is optimized for Google Colab, which provides:

• Pre-installed dependencies (e.g., geemap, earthengine-api, folium)
• Easy access to cloud storage for saving outputs
• Interactive map visualization