What does Google Earth Mean for the Social Sciences? - Geographic Visualization: Concepts, Tools and Applications - page 14

Figure 2.1 Dutton's Quaternary Triangular Mesh, a discrete global grid based on recursive subdivi-
sion of the faces of an octahedron

by a single numerical string of variable length, rather than the pairs of strings of latitude
and longitude, and spatial resolution is always explicit.

2.2.2 Massive volumes of data

The Earth's surface has approximately 500 million square kilometres. To picture the surface
at a spatial resolution of 1 km requires 500 million data elements, and at a spatial resolution
of 1 m there are approximately 500

10 12 data elements. Feeding such volumes of data
from the Google Earth server to a personal computer creates truly daunting problems. For
example, assuming that each data element consists of a single byte (allowing 256 possible
values), it would take 69.4 working years to send the whole Earth at 1 m resolution over a
T1 line, the communication speed that is typical of many offices but generally faster than
home broadband connections. Over a 56 kbit phone modem the same task would take
12 400 years.
Google Earth manages to create images at these resolutions using a number of clever
tricks and strategies. First, there is never any point in downloading data at a resolu-
tion finer than that of the computer's screen, which means that only on the order of
1 million data elements at the appropriate spatial resolution need to be present at any
time. Second, by requiring the user to download software rather than using a standard
browser, Google Earth is able to store data locally, and download only data that are newly
needed. Finally, level-of-detail management allows lower levels of spatial resolution in the
periphery of the field of view and during rapid panning. As a result, it is possible using
a fairly modest Internet communication speed to create real-time flights over the Earth's
surface.

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