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erage of communication networks. The number of such
satellites could double in the new decade. With electronic
networks of ground-receiving stations world-wide, the
systems provide global digital coverage data in both spa-
tial and temporal domains for scientific communities,
operational users and decision-makers. Socialising infor-
mation technology, including the digital Earth observation
data, could change the way of living and revolutionalise
planning and decision-making processes at all levels.
The digital Earth is to create a strong impact on society,
contributing to socialising spatial information. On the one
hand, pertinent data and decision support tools will be
accessible on a timely basis to scientific communities for
studying global issues, such as monitoring carbon, water
cycles, climate changes; on the other hand, value-added
information will become more easily accessible to all inter-
ested stakeholders, including planners and decision-mak-
ers at various levels, local communities and even individuals
for monitoring physical, chemical and biological conditions
of the eco-systems. Local farmers, for example, by mod-
ernising response farming towards precision farming, will
improve their tactical decision-making based on the quanti-
tative observation of local environmental factors, such as
physical parameters of soil, nutrients, water stress and crop
diseases. Real time monitoring and modelling of crops will
enable decisions by farmers on optimum farming practices
relating to irrigation, pesticide and harvesting, using cen-
trally stored reference data, automatically collected weather
data and rainfall estimation from satellite images, in combi-
nation with some key data of social and economic con-
straints. Precision farming will contribute to sustainable agri-
culture development by trade-off between productivity and
pollution and efficient use of resources.
The new technologies- satellite-based positioning systems,
satellite remote sensing and geographical information sys-
tems - viewed as an important part of the digital Earth infra-
structure, will facilitate much of the work related to detecting
and measuring variables of landuse and land cover, soil,
cropland, rangeland, forests and trees and fisheries
resources, and monitoring and predicting environmental
changes and sustainability. By "implanting" smart sensors in
strategically selected vulnerable locations/objects, it will
. enable real-time detecting for early warning natural disasters
such as landslides, forest fires and spreads of hazardous
materials, or perhaps reporting the loss of critical biodiversi-
ties that are put under close surveillance. The information
can be disseminated through world-wide digital Earth net-
works ready for on-line processing, analysis and utilisation.
2. Integrated Global Observing Strategy
Identifying missions for the vision of the digital Earth will be
a continual process. An Integrated Global Observing Strat-
egy (IGOS) could be a prototype for such a mission. Sev-
eral international research and development programmes,
such as the International Programme on Geosphere and
Biosphere (IGBP) and the World Climate Research Pro-
gramme (WCRP) are other examples contributing to the
missions of digital Earth. The objective of IGOS is to unite
the major satellite and surface-based systems for global
environmental observations of the atmosphere, oceans
and land. As a strategic planning process, IGOS links
research, long-term monitoring and operational pro-
grammes, as well as data producers and users, in a frame-
work that delivers maximum benefit and effectiveness in
addressing information needs in decision-making for sus-
tainable development.
The strategy of IGOS covers all forms of data collection
concerning the physical, chemical and biological environ-
ments of the Earth, as well as data on the human environ-
ment, on human pressures on the natural environment,
and on environmental impacts on human well-being. It
Terrestrial Validation Synergism
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(Source: GTOS Secretariat)
International Archives of Photogrammerty and Remote Sensing. Vol. XXXIII, Part A. A