Modis Land Cover Mapping And Analysis In Google Earth Engine

Remote Sensing Land Cover Change Detection Using MODIS Data in Google Earth Engine

What you'll learn

Understand the fundamentals of remote sensing and the significance of land cover change detection for environmental monitoring and management.

Gain hands-on experience accessing and processing MODIS satellite datasets within Google Earth Engine (GEE).

Learn to visualize and analyze land cover data for different years, enabling effective change detection and temporal analysis.

Develop skills to export processed land cover maps as GeoTIFF files for further use in GIS applications and reporting.

Requirements

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

Description

This course, “MODIS Land Cover Mapping and Analysis in Google Earth Engine” offers a comprehensive exploration of satellite-based land cover monitoring and analysis using state-of-the-art Earth observation tools. Students will begin with foundational knowledge of remote sensing principles, understanding how electromagnetic signals captured by satellites translate into meaningful information about Earth’s surface. The course emphasizes the critical importance of land cover data in environmental management, urban planning, agriculture, and climate studies, highlighting real-world applications and decision-making processes supported by such data.Next, learners will be introduced to Google Earth Engine (GEE), a powerful cloud-based geospatial analysis platform that enables efficient processing and visualization of large satellite datasets. The course details how to access, filter, and manipulate MODIS land cover products, focusing on the MCD12Q1 dataset, which classifies global land surface types annually with multiple classification schemes.Students will gain hands-on experience interpreting MODIS land cover classes and learn how to apply these datasets for detecting changes over time, critical for tracking urban expansion, deforestation, and habitat alteration. The curriculum culminates in practical implementation exercises within GEE, guiding users to create multi-year land cover visualizations, generate time series analyses, and export high-quality geospatial data outputs like GeoTIFFs for further research or reporting.By the end of the course, students will be proficient in leveraging MODIS land cover data and GEE tools to conduct robust land cover change detection workflows applicable to academic research, environmental monitoring, and industry projects.

Overview

Section 1: Introduction

Lecture 1 Lecture 1: Fundamentals of Remote Sensing

Lecture 2 Lecture 2: Land Cover – Importance and Applications

Lecture 3 Lecture 3: Introduction to Google Earth Engine (GEE)

Lecture 4 Lecture 4: MODIS Land Cover Product – Classes and Usage

Lecture 5 Getting Started with the Google Earth Engine Interface

Lecture 6 Lecture 5: Practical Implementation of Land Cover Change Detection in GEE

Lecture 7 Extra: Land Cover mapping of Ireland

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