Cloud Based Remote Sensing With Google Earth Engine

This book guides its audience—which can range from novice users to experts— though a 55-chapter tour of Google Earth Engine. A sequenced and diverse set of lab materials, this is the product of more than a year of effort from more than a hundred individuals, collecting new exercises from professors, undergraduates, master’s students, PhD students, postdocs, and independent consultants. Cloud Based Remote Sensing with Google Earth Engine is broadly organized into two halves. The first half, Fundamentals, is a set of 31 labs designed to take the reader from being a complete Earth Engine novice to being a quite advanced user. The second half, Applications, presents a tour of the world of Earth Engine across 24 chapters, showing how it is used in a very wide variety of settings that rely on remote-sensing data This is an open access book.

This book guides its audience—which can range from novice users to experts— though a 55-chapter tour of Google Earth Engine. A sequenced and diverse set of lab materials, this is the product of more than a year of effort from more than a hundred individuals, collecting new exercises from professors, undergraduates, master’s students, PhD students, postdocs, and independent consultants. Cloud Based Remote Sensing with Google Earth Engine is broadly organized into two halves. The first half, Fundamentals, is a set of 31 labs designed to take the reader from being a complete Earth Engine novice to being a quite advanced user. The second half, Applications, presents a tour of the world of Earth Engine across 24 chapters, showing how it is used in a very wide variety of settings that rely on remote-sensing data This is an open access book.

In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.

FAO Pakistan in collaboration with the FAO headquarters Geospatial Unit is inviting to an introductory course on Google Earth Engine with the objective to provide the basic skills to operate the platform, select, pre-process and analyze satellite imagery relevant to agriculture and food security, in particular for the identification of specific crops in the land and more broadly for land cover mapping, by using an automatic classification approach. The Workshop is thought for specialists in the technical Departmental Units of Agriculture and Food Security. It requires an understanding of the main satellite missions and basic concepts of Remote Sensing. Limited knowledge of scripting language (e.g. Python, R) is a plus. It has the structure of a theoretical presentation and hands-on exercises on the Google Earth Engine code editor.

This book provides the users with quick and easy data acquisition, processing, storage and product generation services. It describes the entire life cycle of remote sensing data and builds an entire high performance remote sensing data processing system framework. It also develops a series of remote sensing data management and processing standards. Features: Covers remote sensing cloud computing Covers remote sensing data integration across distributed data centers Covers cloud storage based remote sensing data share service Covers high performance remote sensing data processing Covers distributed remote sensing products analysis

Remote Sensing will continue to replace slower, more costly data collection on the ground, providing fast and repetitive coverage of extremely large areas for everyday applications. With the fast-paced nature of the modern world economy, archaic data is rendered seemingly useless. Decision-makers and researchers alike need to analyse and present data in real time. The use of remotely sensed data has opened many unexplored opportunities for exciting and innovative research. It was Star Trek creator, Gene Roddenberry’s character, Captain James T. Kirk of the Starship Enterprise who said, “to boldly go where no man has gone before”. The View From Space: A Beginner’s Guide was written and designed to assist you in accomplishing just that. The View From Space lays the foundation for the understanding of the basic principles of remote sensing and the various open data courses available. The focus of The View From Space takes you on an interstellar journey, focusing predominantly on the use of the Google Earth Engine application. The public data catalogue contains nearly 600 datasets from more than 50 different data providers from across the world, and the list continues to grow. The View From Space contains numerous Google Earth Engine scripts or codes that will assist in accessing the data and information directly from the Google Earth Engine application. You don’t have to be a coding genius to access the wonderful world that is the Google Earth Engine. It is all included. The View From Space further engages in the open-source GIS software QGIS and statistical open-source R and R-Studio software as a crucial element of the journey into space. The View From Space delicately illustrates the wonderful world of remote sensing through the application of the Google Earth Engine and open-source software to several case studies. This completes your initial journey into space, having boldly gone where you have not gone before. I trust you will find this experience worthwhile. Our exhilarating exploration of remote sensing has just begun. Happy reading at maximum warp!

Google Earth Engine (GEE); (https://earthengine.google.org) is a cloud-based online earth observation data archive and distributed computing environment that represents a potential paradigm shift in processing earth observation data. The Forest Service USDA Remote Sensing Applications Center (RSAC) used GEE to automate and streamline the creation of baseline image products used in the Real-Time Forest Disturbance (RTFD) program.This work was sponsored by the Forest Service Remote Sensing Steering Committee (RSSC). The RTFD program detects changes in forest conditions as compared to an established baseline raster layer. Until recently the creation of the baseline layer was largely a manual process that required approximately 300 hours each year. Using GEE, we have reduced that effort to 60 hours-an 80 percent reduction in labor time. This application represents one of numerous projects wherin RSAC has leveraged GEE capabilities.

Get started, quickly, with Google Earth Engine and the powerful geemap Python package. Apply geemap to interactively analyze and visualize big geospatial data in a Jupyter environment. Google Earth Engine (GEE) is a cloud computing platform that offers access to a vast data catalog of satellite imagery and geospatial datasets. The platform has gained immense popularity in the geospatial community in recent years and has played a significant role in empowering numerous environmental applications at local, regional, and global scales. This book takes a hands-on approach to help users get started with the GEE Python API and geemap. It begins with the basics of geemap, including creating and customizing interactive maps. Then, users learn to load cloud-based Earth Engine datasets and local geospatial datasets onto the interactive maps. As readers progress through the chapters, they will explore practical examples of using geemap to visualize and analyze Earth Engine datasets and learn how to export data from Earth Engine. Additionally, the book covers more advanced topics, such as building and deploying interactive web apps with Earth Engine and geemap. Who this book is for This book is designed for students, researchers, and data scientists who want to explore Google Earth Engine using the Python ecosystem of diverse libraries and tools. Regardless of whether you are a new or experienced user of the Earth Engine JavaScript API, this book is suitable for you.