Google Earth Engine for GIS and Remote Sensing Analysis

Welcome to the world of Google Earth Engine, a powerful platform that brings together the realms of Geographic Information Systems (GIS) and Remote Sensing to revolutionize environmental analysis. This book is a comprehensive guide that will equip you with the knowledge and skills to leverage Google Earth Engine’s capabilities for exploring and understanding our planet from a whole new perspective. In this book, you will embark on a journey through various chapters and sections, each dedicated to unraveling the capabilities and applications of Google Earth Engine. Chapter 1: Introduction to Google Earth Engine The journey begins with an overview of Google Earth Engine, its historical context, and its significance in the fields of GIS and Remote Sensing. We explore the fundamental concepts of GIS and Remote Sensing, laying the groundwork for understanding how Google Earth Engine revolutionizes environmental analysis. Chapter 2: Data and Tools in Google Earth Engine Understanding the data is at the core of any analysis. In this chapter, we delve into the plethora of Earth Observation data available in Google Earth Engine, from satellite imagery to climate and weather datasets. We also learn about data preprocessing and preparation techniques, such as filtering, mosaicking, handling missing pixels, and managing projections. Chapter 3: Image Visualization and Analysis in Google Earth Engine Images convey valuable information, and visualization is an essential aspect of environmental analysis. Here, we learn how to visualize satellite imagery and enhance its display with image bands, composites, and custom color palettes. Basic image analysis techniques, including calculating vegetation indices and spectral profiles, are also covered, along with image classification and land cover mapping using both supervised and unsupervised approaches. Chapter 4: Geospatial Analysis and Processing in Google Earth Engine Spatial operations are the building blocks of spatial analysis. This chapter focuses on working with vector data, importing, and visualizing geospatial datasets. We explore spatial operations, such as buffering, clipping, and attribute querying, to extract meaningful insights from the data.