Google Earth Engine: Planetary-scale geospatial analysis for everyone

Abadi, 2016

Barroso, 2013, The datacenter as a computer: an introduction to the design of warehouse-scale machines, Synth. Lect. Comput. Archit., 8, 1

Câmara, 2000, TerraLib: technology in support of GIS innovation. Proc. II Brazilian Symposium on GeoInformatics, 2, 1

Chambers, 2010, FlumeJava: easy, efficient data-parallel pipelines, ACM SIGPLAN Not., 45, 363, 10.1145/1809028.1806638

Chang, 2008, Bigtable: a distributed storage system for structured data, ACM Trans. Comput. Syst., 26, 4, 10.1145/1365815.1365816

Climate Engine

Collect Earth

Coltin, 2016, Automatic boosted flood mapping from satellite data, Int. J. Remote Sens., 37, 993, 10.1080/01431161.2016.1145366

Copernicus Data Access Policy

Corbett, 2013, Spanner: Google's globally distributed database, ACM Trans. Comput. Syst., 31, 8, 10.1145/2491245

Cossu, 2010, A roadmap for a dedicated earth science grid platform, Earth Sci. Inf., 3, 10.1007/s12145-010-0045-4

Dong, 2016, Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine, Remote Sens. Environ, 185, 142, 10.1016/j.rse.2016.02.016

Fikes

Ghemawat, 2003, The Google file system, Proc. SOSP, 29, 10.1145/945445.945450

Global Forest Watch

Gonzalez, 2015

Gonzalez, 2010, Google fusion tables: web-centered data management and collaboration, ACM SIGMOD, 1061

Hansen, 2013, High-resolution global maps of 21st-century forest cover change, Science, 342, 850, 10.1126/science.1244693

Hughes, 2015, GeoMesa: a distributed architecture for spatio-temporal fusion

Joshi, 2016, Tracking changes and preventing loss in critical tiger habitat, Sci. Adv., 2, 10.1126/sciadv.1501675

Lobell, 2015, A scalable satellite-based crop yield mapper, Remote Sens. Environ., 164, 324, 10.1016/j.rse.2015.04.021

Loveland, 2012, Landsat: Building a strong future, Remote Sens. Environ., 122, 22, 10.1016/j.rse.2011.09.022

Map of Life

Masek, 2006, A Landsat surface reflectance dataset for North America, 1990–2000, Geosci. Remote Sensing Lett. IEEE, 3, 68, 10.1109/LGRS.2005.857030

Nemani, 2011, Collaborative supercomputing for global change science, EOS Trans. Am. Geophys. Union, 92, 109, 10.1029/2011EO130001

Patel, 2015, Multitemporal settlement and population mapping from Landsat using google earth engine, Int. J. Appl. Earth Obs. Geoinf., 35, 199, 10.1016/j.jag.2014.09.005

Pekel, 2016, High-resolution mapping of global surface water and its long-term changes, Nature, 10.1038/nature20584

Soulard, 2016, Continuous 1985–2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California, Remote Sens., 8, 371, 10.3390/rs8050371

Sturrock, 2014, Fine-scale malaria risk mapping from routine aggregated case data, Malar. J., 13, 1, 10.1186/1475-2875-13-421

Tigani, 2014

Verma, 2015

Whitman, 2014, 73

Woodcock, 2008, Free access to Landsat imagery, Science, 320, 1011, 10.1126/science.320.5879.1011a

Yu, 2015, Geospark: a cluster computing framework for processing large-scale spatial data

Zhang, 2015, Building a better urban picture: combining day and night remote sensing imagery, Remote Sens., 7, 11887, 10.3390/rs70911887