To make Google's high-resolution imagery as useful as possible, it is necessary to more fully characterize the temporal, spectral, and spatial properties of the archive. Users also have a number of additional resources to rely upon, including: detailed digital elevation models which allow three-dimensional viewing of the imagery, more than five million geo-referenced photos from services such as Panoramio, and a rapidly expanding set of vector and image-based overlays from a wide range of commercial geospatial services companies, scientific and government organizations, and millions of individual members of the GE community. GE high-resolution imagery does not contain an infrared band and sometimes has a slightly coarser spatial resolution than the native images provided directly from the sensor operators, yet a user of the GE environment is often able to readily discern land cover type, disturbance events, and other relevant attributes based solely on the imagery. This cost landscape changed in 2005, when Google began hosting high-resolution commercial imagery at reduced spectral and spatial resolution on its cost-free Google Earth and Google Maps applications. Improvements in algorithm design and computational power have steadily reduced the analytic obstacles for leveraging this imagery, yet the cost of commercial imagery remains prohibitive for many science applications.
#STREAING SPONGEBOB SEASON 3 EPISODE 4 3 ARCHIVE#
Some scientists have recently begun using this rapidly expanding, cost-free imagery source, but the GE high-resolution imagery archive remains a largely unexploited resource for the scientific analysis and description of the Earth's land surface.Īlthough high-resolution imagery has long played a role in scientific inquiry, the 19 launches (respectively) of the commercial imaging satellites IKONOS and QuickBird, have generated increased interest in methods that facilitate the efficient extraction of scientifically relevant information from high-resolution imagery.
Imagery at these resolutions allows human observers to readily discriminate between major natural land cover classes and to discern components of the human built environment, including: individual houses, industrial facilities, and roads. GE now hosts high-resolution (< 2.5 meter) imagery from 2000-2008 that spans more than twenty percent of the Earth's land surface, and more than a third of the human population.
Yet the imagery which underlies GE has potential applications that extend beyond visualization the archive could contribute directly to land-cover and land-use change science (LCLUC). With more than 200 million users since its release in June 2005, Google Earth (GE) has recently been recognized for its potential to significantly improve the visualization and dissemination of scientific data. These findings indicate that Google Earth high-resolution imagery has a horizontal positional accuracy that is sufficient for assessing moderate-resolution remote sensing products across most of the world's peri-urban areas. The accuracy of control points in more-developed countries is 24.1 meters RMSE, which is significantly more accurate than the control points in developing countries (44.4 meters RMSE t-test p-value < 0.01). The control points derived from satellite imagery have an accuracy of 22.8 meters RMSE, which is significantly more accurate than the 48 control-points based on aerial photography (41.3 meters RMSE t-test p-value < 0.01). Relative to Landsat GeoCover, the 436 Google Earth control points have a positional accuracy of 39.7 meters RMSE (error magnitudes range from 0.4 to 171.6 meters). Landsat GeoCover is an orthorectified product with known absolute positional accuracy of less than 50 meters root-mean-squared error (RMSE). To increase the scientific utility of this archive, we address horizontal positional accuracy (georegistration) by comparing Google Earth with Landsat GeoCover scenes over a global sample of 436 control points located in 109 cities worldwide. This contemporary high-resolution archive represents a significant, rapidly expanding, cost-free and largely unexploited resource for scientific inquiry. Google Earth now hosts high-resolution imagery that spans twenty percent of the Earth's landmass and more than a third of the human population.
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