Mastering Earth Observation With Ai & Google Earth Engine

Mastering Earth Observation: Unlocking Geospatial Insights with GEE & Python

What you'll learn

Google Earth Engine

Remote Sensing and Earth Observation

Geospatial Analysis

Work on Real Projects

Various kind of hazard mapping including flood, forest fire, landslide etc

Multiple ways to prepare LULC maps in cloud environment

Requirements

Basic knowledge of remote sensing

Intermediate knowledge of deep learning

Description

Harness the power of Google Earth Engine (GEE) and Artificial Intelligence (AI) to analyze satellite imagery and monitor environmental changes. This comprehensive course will guide you through the fundamentals of remote sensing, machine learning, and deep learning for geospatial analysis.You will start with an introduction to GEE and remote sensing, learning how to access and process satellite imagery. From there, you’ll dive into Land Use and Land Cover (LULC) mapping, applying machine learning and deep learning techniques to classify landscapes effectively.The course also covers time-series image visualization, allowing you to create animated representations of changes over time. You’ll explore real-world environmental applications, including forest fire mapping, flood analysis using multiple satellite datasets, and landslide susceptibility mapping. Additionally, you will learn change detection analysis using deep learning, a crucial technique for tracking landscape modifications.By the end of this course, you will have the skills to:Utilize GEE for satellite image processing and visualizationImplement machine learning and deep learning for LULC classificationConduct disaster mapping for floods, forest fires, and landslidesApply change detection techniques to monitor environmental transformationsWhether you are a researcher, student, or GIS professional, this course will equip you with practical skills to analyze Earth’s dynamic surface using cutting-edge geospatial technologies.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Lecture Outline

Lecture 3 Remote sensing basics

Lecture 4 Google earth engine basics

Lecture 5 Resources and how to get help

Section 2: LULC mapping in GEE

Lecture 6 LULC mapping in GEE

Lecture 7 Compare map (slider interface)

Section 3: LULC Mapping using GEE and Deep Learning

Lecture 8 LULC mapping using 1D-CNN model

Section 4: Time Series Image Visualization

Lecture 9 Night Time Light Gif generation with vector and text overlay

Lecture 10 Daily Rainfall imagery animation

Section 5: Forest Fire Mapping

Lecture 11 LA forest fire mapping

Section 6: Change Detection using Deep Learning

Lecture 12 Intro and about data

Lecture 13 Building change detection

Section 7: Flood mapping and Analysis

Lecture 14 Dubai Flood 2024

Section 8: Landslide Susceptibility mapping in GEE

Lecture 15 Intro and Objective of this section

Lecture 16 Landslide Susceptibility in GEE

Lecture 17 Generate ROC curve and variable importance map

Section 9: Extra_resources

Lecture 18 Spectral Reflectance Curve

Lecture 19 Bonus Lecture

Early career researcher,Remote Sensing Beginners