Satellite remote sensing has been
used to varying degrees around the
world for over three decades. Over that
time the degree to which the technology
has been applied has varied greatly
from country to country – from being
broadly embraced to being used hardly
at all. Simply stated, where remotely
sensed data and related geospatial data
are used in a limited fashion the full
economic and social value of the data
for resource evaluation, sustainable
resource management, and environmental
protection is not realized. This paper
examines the key factors that appear to
be associated with varying use of the data
and consequent derivation of benefits.
At one time it was thought that this use
was related to the economic situation
within a country or the quality of
training and education. While these
factors are of course important, this work isolates other factors as being
equally if not more important. These
factors include data policy, approaches to
commercialization, the level of applied
research and links to “real” users. This
paper explores the importance of these
other factors with special reference to
data policy in Thailand and Canada.
Background
In the examination of why some remote
sensing programs in less developed
countries were more successful than others
Ryerson and Quiroga (2000) suggested
that a number of factors come into play.
In a review of over 200 projects around
the world it was found that successful
projects seem to share the operational
characteristics outlined in Table 1.
Experience has also shown that if
tangible results are expected it is critical
to involve the potential community
of end users through self-sustaining
institutions very early in the design stage.
While this work seemed to explain the
level of success at the project level, and
while it helped explain some of the level
of success at the national level, there were
situations at the national level that did
not appear to be explainable solely on
the basis of these factors. The remainder
of this paper addresses these factors.
The importance of data policy
We have been involved in detailed studies
of geospatial and remote sensing data
policy in general and specifically in the
USA, Europe, Australia, Canada and
Thailand. In a land mark comparative study of data policy in Canada, the USA,
and Australia, our team found (Sears
2001) that cost recovery policies adversely
affected the level of use of geospatial
data. Furthermore, we found an inverse
relationship between the levels of cost
recovery fees charged and the growth
of the geospatial industry. While this
study has resulted in a reduction in cost
recovery for base-layers of geospatial map
information in Canada (and in Australia),
it has had limited or no impact on the high
cost of remote sensing data in Canada
where the study was done. Canada seems
to have adopted a low-volume high-cost
model for remote sensing data and by so
doing has had an impact on several areas,
including data use, development of valueadded
industry, and the derivation of
benefits from widespread data use. With
our findings a data policy framework was
developed (Ryerson 2005). The essential
elements of that policy believed to be
relevant to data use are summarized
in the early paper by Ryerson, and
are available from the author.
The framework was subsequently applied
and modified somewhat for Thailand
in a September 2006 Workshop held in
Bangkok hosted by the GeoInformatics
and Space Technology Development
Agency (Public Organization)
(GISTDA) of Thailand and Kim
Geomatics Corporation of Canada.
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