5. OPERATIONAL1ZATION OF EARTH OBSERVATION
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motivation since the source of data from which to derive information is
of marginal or no concern, so long as the information provided is
accurate and suitable to the task at hand.
2. To understand how to satisfy an information requirement using remotely
sensed data sources requires knowledge of the physics of the sensing
process and the technology which supports it. This knowledge, in
general, only exists on the technology side of the gap and when one
couples this with the differences in motivation on the two sides of the
gap, one is soon led to the conclusion that the initiative to bridge the gap
must come from the technology side.
In the following sections we explore a process by which the knowledge gap
may be bridged.
4.1
The data to information knowledge base
There are two major activities involved in expanding the knowledge base
supporting data to information conversion methodologies:
1. Understanding requirements for information. It has already been stated
that these requirements differ depending on the use to which the
information is to be put. Additionally, the ways in which information
consumers express their requirements differs between disciplines and
have no explicit relationships with remote sensing technologies. Thus, at
this stage of the process, one’s technological expertise and knowledge are
of little use. One must “get inside the head” of the consumer and
understand in the way he/she does, what the information requirements are
and how they relate to the task(s) at hand. This is a major undertaking
and its difficulty should not be minimized;
2. Having understood an information requirement, one must then determine
whether and how this requirement can be satisfied using Earth
Observation data sources, the costs of doing so and the quality of the
information produced relative to that derived from alternative sources. It
is here that technological expertise and knowledge are critical.
Each of these activities is a substantial undertaking. The first involves
getting answers to the generic question “When you do your job, what
information do you need?” If the field is forestry, for example, the answers
will be expressed in terms of such things as biomass, plant nutrition, erosion
factors, crown closure, species mix, road access, forest diseases, regrowth
rates and the like. Furthermore, information delivered by the system must
also be expressed in these terms. Images of forestlands from space are, in
general, of passing interest only.
The second task involves applying one’s knowledge of the physics of
measuring physical quantities from space, the processing of raw data into
43
motivation since the source of data from which to derive information is
of marginal or no concern, so long as the information provided is
accurate and suitable to the task at hand.
2. To understand how to satisfy an information requirement using remotely
sensed data sources requires knowledge of the physics of the sensing
process and the technology which supports it. This knowledge, in
general, only exists on the technology side of the gap and when one
couples this with the differences in motivation on the two sides of the
gap, one is soon led to the conclusion that the initiative to bridge the gap
must come from the technology side.
In the following sections we explore a process by which the knowledge gap
may be bridged.
4.1
The data to information knowledge base
There are two major activities involved in expanding the knowledge base
supporting data to information conversion methodologies:
1. Understanding requirements for information. It has already been stated
that these requirements differ depending on the use to which the
information is to be put. Additionally, the ways in which information
consumers express their requirements differs between disciplines and
have no explicit relationships with remote sensing technologies. Thus, at
this stage of the process, one’s technological expertise and knowledge are
of little use. One must “get inside the head” of the consumer and
understand in the way he/she does, what the information requirements are
and how they relate to the task(s) at hand. This is a major undertaking
and its difficulty should not be minimized;
2. Having understood an information requirement, one must then determine
whether and how this requirement can be satisfied using Earth
Observation data sources, the costs of doing so and the quality of the
information produced relative to that derived from alternative sources. It
is here that technological expertise and knowledge are critical.
Each of these activities is a substantial undertaking. The first involves
getting answers to the generic question “When you do your job, what
information do you need?” If the field is forestry, for example, the answers
will be expressed in terms of such things as biomass, plant nutrition, erosion
factors, crown closure, species mix, road access, forest diseases, regrowth
rates and the like. Furthermore, information delivered by the system must
also be expressed in these terms. Images of forestlands from space are, in
general, of passing interest only.
The second task involves applying one’s knowledge of the physics of
measuring physical quantities from space, the processing of raw data into