![]() ![]() Those operations are called “server-side”. GEE takes care of all the infrastructure and parellelization decisions on the back end for you. ![]() Google Earth Engine is designed for cloud-based, parallelized geospatial data analysis. Reason # 2: Free cloud processing with built-in functions Some example GEE scripts for visualizing the data The website published in conjunction with the paper This work can pinpont areas with little access to services in order to inform public health efforts and policy decisions.Ī global map of travel time to cities to assess inequalities in accessibility in 2015 - The original paper published in Nature describing the distribution of travel times to the nearest densely population area from any spot on the globe. ![]() The Oxford Malaria Atlas Project, the European Commission’s Joint Research Centre, and the University of Twente teamed up to create a map of travel times from any point in the world to the nearest urban center. The Global Surface Water Data Explorer that was published in conjunction with the dataset to allow users to visualize changes in surface water.Ī Data Users Guide describing the dataset in detail.Ĭelebrity Use Case 3: Global Travel Times High-resolution mapping of global surface water and its long-term changes - The original paper published in Nature. In other words, they mapped the loss and gain of water at a global scale since 1984. In 2016 the European Commission’s Joint Research Centre released a dataset, the Global Surface Water Occurrence dataset, that showed the change intensity of surface water occurrence around the world. Credit: Hansen, Potapov, Moore, Hancher et al., 2013Ĭelebrity Use Case 2: Global Surface Water Occurrence Hansen Tutorial for GEE Learn GEE by stepping through these beginner-oriented tutorials that engage participants with the dataset.įorest loss in Sumatra’s Riau province, Indonesia, 2000-2012. High-Resolution Global Maps of 21st-Century Forest Cover Change original publication in Science by Hansen, et al (2013). The underlying Hansen deforestation dataset is available in Google Earth Engine and leverages over 3 million Landsat images to map global forest dynamics. This forest monitoring and conservation tool interactively shows forest gain and loss at a global scale. Released in 2013, Global Forest Watch fundamentally changed our understanding of planetary-scale forest loss. The following three examples show the datasets, high-impact publications and web-based data explorers that have been generated from research conducted in GEE.Ĭelebrity Use Case 1: Global Forest Watch Since GEE came online, several ground-breaking studies have emerged thatĭemonstrate the power of bringing large-scale computing to bear on environmental and social problems. Enhancing inclusive access has spurred the growth of earth observation at scales previously unimaginable. Google Earth Engine enables users to compute on petabytes of data on the fly without having the navigate the complexities of cloud-based parallelization. Water management, climate monitoring and environmental protection. Including deforestation, drought, disaster, disease, food security, Geospatial analysis that brings Google’s massive computationalĬapabilities to bear on a variety of high-impact societal issues Google Earth Engine is a cloud-based platform for planetary-scale (2017) write in the 2017 Remote Sensing of the Environment article: Understand the power of Google Earth Engineīasic understanding of the system architecture and philosophyĪs Gorelick et al. ![]()
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