Crop Health Monitoring With Modis In Google Earth Engine

Satellite Crop Health Monitoring

What you'll learn

Understand the fundamentals of remote sensing and its application in agricultural monitoring.

Learn how to access and process MODIS satellite data using Google Earth Engine.

Analyze key vegetation indices to assess crop health and detect stress conditions.

Develop practical skills to create time-series visualizations and interpret crop health trends over time using GEE.

Requirements

No prior experience with Google Earth Engine is required — the course will guide you step-by-step.

Description

This course, Crop Health Monitoring with MODIS in Google Earth Engine, is designed to help learners understand and apply satellite-based remote sensing techniques for monitoring crop conditions. By using MODIS satellite data and the cloud-based power of Google Earth Engine (GEE), students will learn how to analyze vegetation health using indices like NDVI and VHI across multiple years. The course begins with the fundamentals of remote sensing, introduces vegetation indices relevant to crop monitoring, and then progresses to hands-on implementation in GEE. Learners will write scripts, visualize changes in crop health, and extract useful insights from large-scale satellite imagery. This practical approach is ideal for those in agriculture, environmental science, or resource management who want to integrate geospatial data into their work. No previous coding or satellite data experience is required, making this course accessible to beginners while still offering value to advanced users. By the end, learners will be equipped with the tools to assess vegetation stress, monitor crop performance, and support data-driven agricultural decisions using free, global satellite data. The skills gained can be applied in research, policy planning, agritech, and precision farming, making this course valuable for both academic and professional growth. It also fosters spatial thinking and remote monitoring skills essential in climate-resilient agriculture.

Overview

Section 1: Introduction

Lecture 1 Intro

Lecture 2 Lecture 1: Fundamentals of Remote Sensing

Lecture 3 Lecture 2: Crop Health Mapping

Lecture 4 Lecture 3: Introduction to Google Earth Engine

Lecture 5 Lecture 4: Crop Health Vegetation Indices Using MODIS

Lecture 6 Getting Started with the Google Earth Engine Interface

Lecture 7 Lecture 5: Practical Implementation in Google Earth Engine (GEE)

Lecture 8 Extra Learning: Extract crop health conditions for a specific agricultural area

Students and researchers in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.