Introduction Machine Learning

Introduction

Lab Sign up for Google Earth Engine

Why to work with Google Earth Engine

Interface of Google Earth Engine Code Editor & Explorer

Overview of datasets in GEE

Using cloud platform for spectral indices & land cover analysis EO browser

Lab Declaring variables in Javascript in GEE

Lab Introduction to Javascript

Lab Image Calculations - Create a composite and calculate NDVI

Lab Working with image collections and image visualization

Lab Mapping and Reducing Collection - Landsat Example

Lab Export image data from Google Earth Engine

Lab Short introduction to functions - Maximum NDVI Example

Practice your skills - the task

Lab Image mosaicking, clipping, and reprojection

Section Overview

Understanding Remote Sensing for LULC mapping

Introduction to Machine Learning in GIS and Remote Sensing

Introduction to LULC classification based on satellite images

Supervised and unsupervised image classification

Stages of LULC supervised classification

Lab Machine Learning Classification in Google Earth Engine (Explorer)

Introduction to image data Landsat

Lab Import images and their visualization in Google Earth Engine

Lab Unsupervised (K-means) image analysis in Google Earth Engine

Common machine Learning algorithms for supervised learning

Accuracy Assessment of LULC maps

Lab Random Forest Classification in Earth Engine

Lab Supervised Machine Learning with CART

Lab Accuracy Assessment in GEE

Supervised classification with Google Earth Engine (explorer)

Mapping Burnt Severity witn Nornalised Burnt Ration (NBR) Index Theory

On change detection Theory

Lab Change Detection in GEE

Advance Change Detection Time Series Trend Analysis with Linear Regression

Your Final Project

BONUS