Google Earth Engine: Planetary-scale geospatial analysis for everyone

Noel Gorelick, M. Hancher, Mike Dixon, Simon Ilyushchenko, David Thau · Remote Sensing of Environment · 2017

Summary

Google Earth Engine is a cloud-based platform for planetary-scale geospatial analysis that brings Google's massive computational capabilities to bear on a variety of high-impact societal issues including deforestation, drought, disaster, disease, food security, water management, climate monitoring and environmental protection.

Type: article
Published: 2017-12-01
Cited by: 12,544
References: 27
Access: Open access
DOI: https://doi.org/10.1016/j.rse.2017.06.031
OpenAlex: https://openalex.org/W2725897987
Semantic Scholar: https://api.semanticscholar.org/CorpusID:134638494

Keywords

Geospatial analysis, Cloud computing, Scale (ratio), Remote sensing, Earth observation

References

Bigtable: a distributed storage system for structured dataFay W. Chang, Jay B. Dean, Sanjay Ghemawat — 2006
GeoMesa: a distributed architecture for spatio-temporal fusionJames Hughes, Andrew M. Annex, Christopher N. Eichelberger — 2015
A scalable satellite-based crop yield mapperDavid B. Lobell, David Thau, Christopher Seifert — 2015
Building a Better Urban Picture: Combining Day and Night Remote Sensing ImageryQingling Zhang, Bin Li, David Thau — 2015
FlumeJava: easy, efficient data-parallel pipelinesCraig Chambers, Ashish Raniwala, Frances Perry — 2010
High-Resolution Global Maps of 21st-Century Forest Cover ChangeMatthew C. Hansen, Peter Potapov, Rebecca Moore — 2013
Collaborative Supercomputing for Global Change ScienceR. R. Nemani, P. Votava, Andrew Michaelis — 2011
A roadmap for a dedicated Earth Science Grid platformR. Cossu, M. Petitdidier, Julian Linford — 2010
Methods, markers and mechanisms for protective immunity in the controlled human malaria infection modelRobert W. Sauerwein — 2014
Landsat: building a strong futureThomas R. Loveland, John L. Dwyer — 2012
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale MachinesLuiz André Barroso, Urs Hölzle — 2009
Free Access to Landsat ImageryCurtis E. Woodcock, Richard G. Allen, Martha C. Anderson — 2008
Google fusion tables: web-centered data management and collaborationHéctor González, Alon Halevy, Christian S. Jensen — 2010
Fine-scale malaria risk mapping from routine aggregated case dataHugh J. W. Sturrock, Justin M Cohen, Petr Keil — 2014
A Landsat surface reflectance dataset for North America, 1990-2000J. G. Masek, Éric Vermote, Nazmi Saleous — 2006
Building Your Next Big Thing with Google Cloud PlatformS. P. T. Krishnan, Jose L. Ugia Gonzalez — 2015
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed SystemsMartı́n Abadi, Ashish Agarwal, Paul Barham — 2016
Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth EngineJinwei Dong, Xiangming Xiao, Michael A. Menarguez — 2016
GeoSpark: a cluster computing framework for processing large-scale spatial dataJia Yu, Jinxuan Wu, Mohamed Sarwat — 2015
Tracking changes and preventing loss in critical tiger habitatAnup R. Joshi, Eric Dinerstein, Eric Wikramanayake — 2016

Cited by

Global long-term observations of coastal erosion and accretionLorenzo Mentaschi, Michalis Vousdoukas, Jean‐François Pekel — 2018
Assessing vulnerability of densely populated areas to air pollution using Sentinel-5P imageries: a case study of the Nile Delta, Egyptصدیقه عسگری, علی رضا قنادی, شهریار ادیبی — 2023
Forecasting GDP Growth from Outer SpaceJaqueson K. Galimberti — 2018
Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Advanced Natural Resource Monitoring and Process UnderstandingJustin Huntington, Katherine C. Hegewisch, B. Daudert — 2017
A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United StatesNathaniel Robinson, Brady Allred, Matthew Jones — 2017
Annual Irrigation Dynamics in the U.S. Northern High Plains Derived from Landsat Satellite DataJillian M. Deines, A. D. Kendall, D. W. Hyndman — 2017
The Geometry of Large Tundra Lakes Observed in Historical Maps and Satellite ImagesIvan Sudakov, Almabrok Essa, Luke Mander — 2017
Relative Humidity Has Uneven Effects on Shifts From Snow to Rain Over the Western U.S.A. A. Harpold, S. Rajagopal, J. B. Crews — 2017
Big Remotely Sensed Data: tools, applications and experiencesFrancesco Casu, Michele Manunta, P. S. Agram — 2017
Weak bedrock allows north-south elongation of channels in semi-arid landscapesSamuel A. Johnstone, N. J. Finnegan, G. E. Hilley — 2017
Optical Remote Sensing Potentials for Looting DetectionΆθως Αγαπίου, Vasiliki Lysandrou, Diofantos Hadjimitsis — 2017
Forest Harvest Patterns on Private Lands in the Cascade Mountains, Washington, USAChristopher E. Soulard, Jessica J. Walker, Glenn E. Griffith — 2017
REMAP: An online remote sensing application for land cover classification and monitoringNicholas Murray, David A. Keith, Daniel Simpson — 2017
Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth EngineJun Xiong, Prasad S. Thenkabail, James C. Tilton — 2017
Marsh Recession and Erosion study of the Fraser Delta, B.C., Canada from Historic Satellite ImageryRichard Marijnissen, Stefan Aarninkhof — 2017
Utilization of Landsat Imagery to Assess the Impacts of Oil and Gas Extraction on the Tazovsky Peninsula, SiberiaNicholas B Kline — 2017
Mapping rice areas with Sentinel-1 time series and superpixel segmentationKersten Clauss, Marco Ottinger, Claudia Kuenzer — 2018
The role of satellite remote sensing in structured ecosystem risk assessments.Nicholas Murray, David A. Keith, Lucie M. Bland — 2018
Online Global Land Surface Temperature Estimation from LandsatDavid Parastatidis, Zina Mitraka, Nektarios Chrysoulakis — 2017
A versatile data-intensive computing platform for information retrieval from big geospatial dataPierre Soille, Abigail Burger, Davide De Marchi — 2018

Google Earth Engine: Planetary-scale geospatial analysis for everyone

Summary

Keywords

References

Cited by

Related papers