EASE-DGGS: a hybrid discrete global grid system for Earth sciences

References

• Adams, B. (2017). Wāhi, a discrete global grid gazetteer built using linked open data. International Journal of Digital Earth, 10(5), 490–503.
   Web of Science ®Google Scholar
• Al Bitar, A., Mialon, A., Kerr, Y. H., Cabot, F., Richaume, P., Jacquette, E., & Wigneron, J.-P. (2017). The global SMOS Level 3 daily soil moisture and brightness temperature maps. Earth System Science Data, 9(1), 293–315.
   Web of Science ®Google Scholar
• Alderson, T. (2020). Digital earth platforms. In H. Guo, M. F. Goodchild, A. Annoni et al., (Eds.), Manual of digital earth (pp. 25–54). Singapore: Springer Singapore. doi:10.1007/978-981-32-9915-3_2
   Google Scholar
• Anscombe, F. J. (1973). Graphs in statistical analysis. The American Statistician, 27(1), 17–21.
   Web of Science ®Google Scholar
• Barnes, R., & Sahr, K. (2018). dggridR: Discrete global grids for R. Retrieved from https://github.com/r-barnes/dggridR/
   Google Scholar
• Bondaruk, B., Roberts, S. A., & Robertson, C. (2020). Assessing the state of the art in discrete global grid systems: OGC criteria and present functionality. Geomatica, 74(1), 9–30.
   Google Scholar
• Bowater, D., & Stefanakis, E. (2018). The rHEALPix discrete global grid system: Considerations for Canada. Geomatica, 72(1), 27–37.
   Google Scholar
• Brodzik, M. J., & Armstrong, R. (2013). Northern hemisphere EASE-Grid weekly snow cover and sea ice extent Version 4 (Version Number: 4 Published: National Snow and Ice Data Center). Boulder, CO. doi: 10.5067/P7O0HGJLYUQU.
   Google Scholar
• Brodzik, M. J., Billingsley, B., Haran, T., Raup, B., & Savoie, M. H. (2012). EASE-Grid 2.0: Incremental but significant improvements for Earth-Gridded data sets. ISPRS International Journal of Geo-Information, 1(1), 32–45.
   Web of Science ®Google Scholar
• Brodzik, M. J., & Knowles, K. (2002). EASE-Grid:A versatile set of equal-area projections and grids. In M. F. Goodchild & A. J. Kimmerling (Eds.), Discrete global grids: A Web Book. Retrieved from https://escholarship.org/uc/item/9492q6sm#%5B%7B%22num%22%3A2002%2C%22gen%22%3A0%7D%2C%7B%22name%22%3A%22XYZ%22%7D%2C70%2C720%2C0%5D
   Google Scholar
• Brodzik, M. J., Long, D. G., & Hardman, M. A. (2019). SMAP radiometer twice–daily rSIR–enhanced EASE-Grid 2.0 Brightness temperatures, Version 1. 0 (Version Number: 1.0 Published: NASA National Snow and Ice Data Center DAAC). Boulder, CO. doi: 10.5067/QZ3WJNOUZLFK.
   Google Scholar
• Brodzik, M. J., Long, D. G., & Hardman, M. A. (2021). SMAP radiometer twice–daily rSIR–enhanced EASE-Grid 2.0 brightness temperatures, Version 2. 0 (Version Number: 2.0 Published: NASA National Snow and Ice Data Center DAAC). Boulder, CO. doi: 10.5067/YAMX52BXFL10.
   Google Scholar
• Brodzik, M. J., Long, D. G., Hardman, M. A., Paget, A., & Armstrong, R. L. (2016). MEaSUREs calibrated enhanced-resolution passive microwave daily EASE-Grid 2.0 brightness temperature ESDR, Version 1 (Version Number: 1 Published: National Snow and Ice Data Center). Boulder, CO. doi: 10.5067/MEASURES/CRYOSPHERE/NSIDC-0630.001.
   Google Scholar
• Brodzik, M., Billingsley, B., Haran, T., Raup, B., & Savoie, M. (2014). Correction: Brodzik, M.J., et al. EASE-Grid 2.0: Incremental but significant improvements for earth-gridded data sets. ISPRS international journal of geo-information 2012, 1, 32–45. ISPRS International Journal of Geo-Information, 3(3), 1154–1156.
   Web of Science ®Google Scholar
• Clarke, K. C. (2000). Criteria and measures for the comparison of global geocoding systems. Santa Barbara, California, 18.
   Google Scholar
• Dhu, T., Dunn, B., Lewis, B., Lymburner, L., Mueller, N., Telfer, E., … Phillips, C. (2017). Digital earth Australia – Unlocking new value from earth observation data. Big Earth Data, 1(1), 64–74.
   Google Scholar
• Dwyer, J., Roy, D. P., Sauer, B., Jenkerson, C. B., Zhang, H. K., & Lymburner, L. (2018). Analysis ready data: enabling analysis of the landsat archive. preprint. Earth Sciences. doi:10.20944/preprints201808.0029.v1.
   Google Scholar
• Entekhabi, D., Das, N., Njoku, E. G., Johnson, J. T., & Shi, J. (2016). SMAP L3 radar/radiometer global daily 9 km EASE- Grid soil moisture, Version 3 (Version Number: 3 Published: NASA National Snow and Ice Data Center DAAC). Boulder, CO. doi: 10.5067/7KKNQ5UURM2W.
   Google Scholar
• Gibb, R. G. (2016, Apr). The rHEALPix discrete global grid system. IOP Conferenc E Series: Earth and Environmental Science, 34, 012012.
   Google Scholar
• Goodchild, M. F. (2018). Reimagining the history of GIS. Annals of GIS, 24(1), 1–8.
   Web of Science ®Google Scholar
• International Standards Organization. (2021). Geographic information — Discrete global grid systems specifications — Part 1: Core reference system and operations, and equal area earth reference system (ISO 19170-1:2021). Retrieved from https://www.iso.org/standard/32588.html
   Google Scholar
• Kim, S., Van Zyl, J., Dunbar, R. S., Njoku, E. G., Johnson, J. T., Moghaddam, M., & Tsang, L. (2016). SMAP L3 radar global daily 3 km EASE-Grid soil moisture, Version 3 (Version Number: 3 Published: NASA National Snow and Ice Data Center DAAC). Boulder, CO. doi: 10.5067/IGQNPB6183ZX.
   Google Scholar
• Kim, Y., Kimball, J. S., Glassy, J., & Du, J. (2017a). An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing. Earth System Science Data, 9(1), 133–147.
   Web of Science ®Google Scholar
• Kim, Y., Kimball, J. S., & McDonald, K. C. (2017b). MEaSUREs global record of daily landscape freeze/thaw status, Version 4 (Version Number: 4 Published: NASA National Snow and Ice Data Center DAAC). Boulder, CO. doi: 10.5067/MEASURES/CRYOSPHERE/nsidc-0477.004.
   Google Scholar
• Lewis, A., Oliver, S., Lymburner, L., Evans, B., Wyborn, L., Mueller, N., & Wang, L.-W. (2017). The Australian geoscience data cube - Foundations and lessons learned. Remote Sensing of Environment, 202, 276–292.
   Web of Science ®Google Scholar
• Ltd., Riskaware. (2017). OpenEAGGR (Open Equal Area Global GRid). Retreievd from https://github.com/riskaware-ltd/open-eaggr
   Google Scholar
• Lynnes, C., Baynes, K., & McInerney, M. (2016). Big Data in the Earth observing system data and information system. Retreievd from https://ntrs.nasa.gov/citations/20160008918
   Google Scholar
• Mahdavi Amiri, A., Alderson, T., & Samavati, F. (2019). Geospatial data organization methods with emphasis on aperture-3 hexagonal discrete global grid systems. Cartographica: The International Journal for Geographic Information and Geovisualization, 54(1), 30–50.
   Google Scholar
• Mahdavi Amiri, A., Samavati, F., & Peterson, P. (2021). rHEALPix DGGS in python. Retreievd from https://github.com/manaakiwhenua/rhealpixdggs-py
   Google Scholar
• Martínez, J., Gabarró, C., & Turiel, A. (2019). Arctic sea surface salinity L3 maps (V.3.0). Published: CSIC - Instituto de Ciencias del Mar (ICM). doi:10.20350/digitalCSIC/9065
   Google Scholar
• Miller, H. J., & Goodchild, M. F. (2015). Data-driven geography. GeoJournal, 80(4), 449–461.
   Web of Science ®Google Scholar
• Mote, T. L. (2014). MEaSUREs Greenland surface melt daily 25km EASE-Grid 2.0, Version 1 (Version Number: 1 Published: National Snow and Ice Data Center). Boulder, CO. doi: 10.5067/MEASURES/CRYOSPHERE/nsidc-0533.001.
   Google Scholar
• Mote, T. L. (2021). Discrete global grid Systems Software Working Group (SWG). Retreievd from https://www.ogc.org/projects/groups/dggsswg
   Google Scholar
• Open Geospatial Consortium. (2017a). Big geospatial data. Retreievd from https://docs.opengeospatial.org/wp/16-131r2/16-131r2.html
   Google Scholar
• Open Geospatial Consortium. (2017b). Discrete Global Grid Systems Domain Working Group (DWG). Retrieved from https://www.ogc.org/projects/groups/dggsdwg
   Google Scholar
• Open Geospatial Consortium. (2017c). Topic 21: Discrete global grid systems abstract specification. Retrieved from http://docs.opengeospatial.org/as/15-104r5/15-104r5.html
   Google Scholar
• Peterson, P. R. (2017). Discrete global grid systems. In D. Richardson et al, (Ed.), International encyclopedia of geography: People, the earth, environment and technology (pp. 1–10). Oxford, UK: John Wiley & Sons, Ltd.
   Google Scholar
• Potapov, P., Hansen, M. C., Kommareddy, I., Kommareddy, A., Turubanova, S., Pickens, A., … Ying, Q. (2020). Landsat analysis ready data for global land cover and land cover change mapping. Remote Sensing, 12(3), 426.
   Web of Science ®Google Scholar
• Purss, M. B. J., Lewis, A., Oliver, S., Ip, A., Sixsmith, J., Evans, B., … Chan, T. (2015). Unlocking the Australian landsat archive – From dark data to high performance data infrastructures. GeoResJ, 6, 135–140.
   Google Scholar
• Purss, M. B. J., Liang, S., Gibb, R., Samavati, F., Peterson, P., Dow, C., … Saeedi, S. (2017). Applying discrete global grid systems to sensor networks and the Internet of Things. 2017 IGARSS. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 5581–5583). Fort Worth, TX: IEEE. doi: 10.1109/IGARSS.2017.8128269.
   Google Scholar
• Purss, M., Oliver, S., Lewis, A., Minchin, S., Wyborn, L., Gibb, R., … Evans, B. (2013). Specification of a global nested grid system for use by Australia and New Zealand. 7th eResearch Australasia Conference, Brisbane, Australia.
   Google Scholar
• Robinson, D. A., & Estilow, T. W., and NOAA Climate Record Program, (2012). NOAA climate data record of Northern Hemisphere (NH) Snow Cover Extent (SCE), Version 1 (Version Number: 1 Published: NOAA National Centers for Environmental Information”, note = “Digital Media”). doi: 10.7289/V5N014G9.
   Google Scholar
• Rosling, H., Rosling, O., & Ronnlund, A. R. (2020). Factfulness: Tens reasons we’re wrong about the world - and why things are better than you think. New York: Flat Iron Books.
   Google Scholar
• Sahr, K. (2003). Geodesic discrete global grid systems. Cartography and Geographic Information Science, 30(2), 121–134.
   Google Scholar
• Snyder, J. P. (1992). An equal-area map projection for polyhedral globes. Cartographica: The International Journal for Geographic Information and Geovisualization, 29(1), 10–21.
   Google Scholar
• Snyder, J. P. (1997). Flattening the Earth: Two thousand years of map projections (pp. 384). Chicago: The University of Chicago Press.
   Google Scholar
• Technologies, Uber. (2018). H3 software repository. Retreievd from https://github.com/uber/h3
   Google Scholar
• Tobler, W., & Chen, Z.-T. (1985). A quadtree for global information storage. Geographical Analysis, 18(4), 360–371.
   Web of Science ®Google Scholar
• Yuan, M. (2020). Relationships between space and time. In J. P. Wilson (Ed.), The geographic information science & technology body of knowledge (3rd Quarter 2020 ed.). doi:10.22224/gistbok/2020.3.7.
   Google Scholar