Introductory Course To Google Earth Engine

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.

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.

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.

Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications explores a wide range of transformative data fusion techniques of Artificial Intelligence (AI) technologies applied to Google Earth Engine (GEE) techniques. The book includes a wide range of scientific domains that can utilize remote sensing and geographic information systems (GIS) through detailed case studies. It delves into the challenges of AI-driven tools and technologies for Earth observation data analysis, offering possible solutions and directly addressing current and upcoming needs within Earth Observation. This is a useful reference for geospatial scientists, remote sensing experts, and environmental scientists utilizing remote sensing to apply the latest AI techniques to data obtained from GEE for their research and teaching. Includes utilization of AI with GEE tools for a spectrum od scientific domains in remote sensing and geographic information systems (GIS), such as natural hazard assessment, aquatic and hydrological applications, and forest cover Highlights the challenges and possible solutions for AI-driven tools and technologies for Earth observation data analysis Provides detailed case studies that show specific considerations and exceptions for applications of AI in GEE for Earth observation

This is the eBook version of the printed book. Using Google™ Maps and Google Earth is more than just a book: it’s the fastest, easiest way to master Google’s amazing mapping applications! Don’t just “read” about it: see it, hear it, live it, with step-by-step screencasts and expert audio tips. Discover how to map your favorite places with Google Maps…see actual locations with Street View…generate driving, walking, and public transit directions…find and learn more about businesses…create and share custom maps and mashups…use Google Maps on iPhone…navigate Google Earth to find locations fast…create life-like Google Earth roadmaps, and tour your route…even explore Google Sky, Google Moon, and Google Earth’s Flight Simulator! Exclusive online Show Me video walks through tasks you’ve just got to see…Tell Me More audio delivers practical, “straight from the experts” insights…Point-Counterpoint audio compares alternative solutions—so you can pick the one that’s best for you. It’s all the help you’ll ever need…where you want it, when you want it!

This catalogue aims to improve the dissemination and outreach of FAO’s knowledge products and overall publishing programme. By providing information on its key publications in every area of FAO’s work, and catering to a range of audiences, it thereby contributes to all organizational outcomes. From statistical analysis to specialized manuals to children’s books, FAO publications cater to a diverse range of audiences. This catalogue presents a selection of FAO’s main publications, produced in 2023 or earlier, ranging from its global reports and general interest publications to numerous specialized titles. In addition to the major themes of agriculture, forestry and fisheries, it also includes thematic sections on climate change, economic and social development, and food safety and nutrition.

Google Earth is a geographic browser or geobrowser which means that it can access images from satellites, the air, ocean, and other geographical data by using the internet. It represents the Earth as a three-dimensional globe. In simpler terms, it is a computer program that uses satellite imagery to provide a representation of the earth. It was first released on June 11, 2001. Subsequent versions were released thereafter, including the most recent version called Google Earth Update. Google Earth displays satellite imagery of the Earth’s surface so that users can view cities, oceans, and pretty much almost all of the earth in 3D, or three dimensions. Users can also add their own data and make them available. There are many other things that users can do with Google Earth, and they will be mentioned further on in the book.

GSA Special Paper 492 consists of 35 papers that collectively synthesize the development and current uses of Google Earth and associated visualization media in geoscience education and research. Chapters focus on Google Earth and related tools, such as SketchUp, Google Fusion Tables, GigaPan, and LiDAR. Many of these papers include digital media that illustrate and highlight important themes of the texts. This volume is intended to document the state of the art for geoscience applications of geobrowsers, such as Google Earth, along with providing provocative examples of where this technology is headed in the future.

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.