Horizontal positional accuracy of google earth's high-resolution imagery archive

Sensors

Volumn 8, Issue 12, 2008, Pages 7973-7981

  Potere, David ^a  

^a PRINCETON UNIVERSITY   (United States)

Author keywords

Google earth; High resolution imagery; Horizontal positional accuracy; Land cover validation; Optical remote sensing

Indexed keywords

GOOGLE EARTHS; HIGH RESOLUTION IMAGERY; LAND COVER; OPTICAL REMOTE SENSING; POSITIONAL ACCURACY;

AERIAL PHOTOGRAPHY; DEVELOPING COUNTRIES; SATELLITE IMAGERY;

REMOTE SENSING;

EID: 58149185306     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s8127973     Document Type: Article

References (18)

1. Google, Inc. Press Release: Introducing Google Earth Outreach, Mountain View, California, USA, 26 June, 2007. (www.google.copm/press/pressrel/outreach- 20070625.html).
2. Butler, D. The web-wide world. Nature 2006, 439, 776-779.
3. Compieta, P.; Di Martino, S.; Bertolotto, M.; Ferrucci, F.; Kechadi, T. Exploring spatio-temporal data mining and visualization. J. Visual Lang. Comput. 2007, 18, 255-279.
4. Guralnick, R.P.; Hill, A.W.; Lane, M. Towards a collaborative, global infrastructure for biodiversity assessment. Ecol. Lett. 2007, 10, 663-672.
5. Google, Inc. Press Release: Google Announces Major Imagery Update for Google Earth, New Tools and Innovations in Mapping, Mountain View, California, USA, 12 June, 2006, (www.google.copm/press/pressrel/geoday.html).
6. Imagery Resolution Assessment and Reporting Standards Committee. Civil National Imagery Interpretability Rating Scale (NIIRS) Reference Guide, 1996. (www.fas.org/irp/imint/niirs-c/index.html).
7. Leachtenauer, J.C.; Daniel, K; Vogl, T.P. Digitizing Corona imagery: Quality vs. cost. In Corona: Between the Sun & the Earth, The first NRO reconnaissance eye in space; R.A. McDonald (ed.); American Society Photogrammetry and Remote Sensing: Washington, D.C., USA, 1997; pp. 189-203.
8. Cha, S.; Park, C. The utilization of Google Earth images as reference data for the multitemporal land cover classification with MODIS data of North Korea, Korean J. Remote Sens. 2007, 23, 483-491.
9. Thenkabail, P.S.; Biradar, M.; Noojipady, P.; Cai, X.; Dheeravath, V.; Li, Y.; Velpuri, M.; Gumma, M.; Pandey, S. Sub-pixel area calculation methods for estimating irrigated areas. Sensors 2007, 7, 2519-2538.
10. Zhang, B.; NanShan, A.; Huang, Z.; Yi, C.; Qin, F. Meanders of the Jialing River in China: Morphology and formation, Chinese Science Bulletin 2008, 5, 267-281.
11. Constantine, J.A.; Dunne, T. Meander cutoff and the controls on the production of oxbow lakes. Geology 2008, 36, 23-26.
12. Panoramio, Press Release: One million registered users and five million photos uploaded, 2007. (www.panoramio.com/blog/1-million-registered-users-and-5- million-photos-uploaded/)
13. DigitalGlobe, Sensor Description, 2008 (www.digitalglobe.com/index.php/ 85/QuickBird).
14. Tucker, C.J.; Grant, D.M.; Dykstra, J.D. NASA's Global Orthorectified Landsat Data Set. Photogramm. Eng. Remote Sens. 2004, 70, 313-322.
15. Masek, J.; Honzak, M.; Goward, S.N.; Liu, P.; Pak, E. Landsat-7 ETM+ as an observatory for land cover: Initial radiometric and geometric comparisons with Landsat-5 Thematic Mapper, Remote Sensing of the Environment 2001, 78, 118-130.
16. Angel, S.; Sheppard, S.C.; Civco, D.L. The Dynamics of Global Urban Expansion. The World Bank: Washington, D.C., USA, 2005. (www.williams.edu/ Economics/UrbanGrowth/WorkingPapers.htm).
17. Global Land Cover Change Facility (GLCF), University of Maryland, 2007 (www.landcover.org).
18. Sahr, K.; White, D.; Kimerling, A. Geodesic Discrete Global Grid Systems. Cartography Geogr. Inf. Sci. 2003, 30, 121-134.