2000). In projects with restricted budgets or limited access to the region, archived data
may be selected as the primary data for analysis. Regardless of whether archived or
ordered images are selected, operators target images that possess minimal cloud cover
and best represent the feature of interest in both spatial, spectral, and temporal
dimensions (Green et al., 2000). If images that include the desired information are
unavailable and/or if data for a particular event or season is required, then a scheduled
flyover is planned, taking into consideration costs and image processing turn-around
time. In situ field data may be collected simultaneously with image capture to evaluate
the accuracy of the image and to enhance the information interpretation (Green et al.,
2000). Once both field and image data are gathered, corrections and integration of data
sets begins, and a final image is produced with a defined specified level of accuracy and
information content (Lillesand and Kiefer, 1994).
During these preliminary steps, local communities can be involved. However, such
involvement may introduce complexity and slow the process of image construction
(Veitayaki, 1998). Nevertheless, local community involvement in the ‘construction
stage’ considerably improves the relevance and practicality of research projects. When
the objectives of a remote sensing study are being defined, for example, local
community members should identify their own research needs (Johannes, 1998). Often
these needs are in conflict with those of the technically trained who often wish to
(1) address purely scientific questions concerning variables that have remained largely
unexamined and/or (2) tackle specific organizational directives from the funding
agency. Although scientists cannot be blamed for the direction of academic research,
managers would welcome almost any scientific information and would benefit from
opportunities to define their own agendas (Hof, 2002).
Once local communities are involved in the beginning stages of the project, ongoing dialogues during subsequent stages of image construction can continue and
increase the appropriateness of the final product. Local communities will benefit from
the process by increasing their knowledge of environmental variables and linkages, and
by better understanding how substrate features are identified, all the while appreciating
the amount of time and effort required to achieve various levels of image accuracy.
Although involving local communities creates complexity, it is essential to the planning
and implementation of appropriate resource management strategies (Cooke, 1994).
There are considerable issues to face when bringing together remotely sensed
information and local knowledge, but incorporating a series of guidelines (Newman and
LeDrew, 2005) may enhance the success of the integration process and bring about
greater utilization of remotely sensed information.
4.3.1 Building an Image with Local Input
Communicating environmental information using satellite imagery, or an imagebased map, is not a universal strategy (Johannes, 1981). For example, on several
islands within Indonesia, it is typical for the local managers to learn about spatial and
temporal changes to coral reef features without the aid of visual devices. Avoiding a
spatial context, stakeholders describe features in the form of lists emphasizing type and
abundance (World, 1994; Cesar et al., 1997; Fearnside, 1997; Pet-Soede et al., 1999).
When viewing or working with geographic maps or images, different people obtain
different amounts and kinds of information. This difference is the result not of the
subjectivity of the information but rather of the different degrees of the viewers’ ability
to extract information. There are differences between the interpreter’s image of reality,
parts of reality that have been mapped, and what actually exists (Salichtchev, 1977).
Therefore, remote sensing operators are challenged to illustrate complex environmental
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Mapping and Management of Coral
may be selected as the primary data for analysis. Regardless of whether archived or
ordered images are selected, operators target images that possess minimal cloud cover
and best represent the feature of interest in both spatial, spectral, and temporal
dimensions (Green et al., 2000). If images that include the desired information are
unavailable and/or if data for a particular event or season is required, then a scheduled
flyover is planned, taking into consideration costs and image processing turn-around
time. In situ field data may be collected simultaneously with image capture to evaluate
the accuracy of the image and to enhance the information interpretation (Green et al.,
2000). Once both field and image data are gathered, corrections and integration of data
sets begins, and a final image is produced with a defined specified level of accuracy and
information content (Lillesand and Kiefer, 1994).
During these preliminary steps, local communities can be involved. However, such
involvement may introduce complexity and slow the process of image construction
(Veitayaki, 1998). Nevertheless, local community involvement in the ‘construction
stage’ considerably improves the relevance and practicality of research projects. When
the objectives of a remote sensing study are being defined, for example, local
community members should identify their own research needs (Johannes, 1998). Often
these needs are in conflict with those of the technically trained who often wish to
(1) address purely scientific questions concerning variables that have remained largely
unexamined and/or (2) tackle specific organizational directives from the funding
agency. Although scientists cannot be blamed for the direction of academic research,
managers would welcome almost any scientific information and would benefit from
opportunities to define their own agendas (Hof, 2002).
Once local communities are involved in the beginning stages of the project, ongoing dialogues during subsequent stages of image construction can continue and
increase the appropriateness of the final product. Local communities will benefit from
the process by increasing their knowledge of environmental variables and linkages, and
by better understanding how substrate features are identified, all the while appreciating
the amount of time and effort required to achieve various levels of image accuracy.
Although involving local communities creates complexity, it is essential to the planning
and implementation of appropriate resource management strategies (Cooke, 1994).
There are considerable issues to face when bringing together remotely sensed
information and local knowledge, but incorporating a series of guidelines (Newman and
LeDrew, 2005) may enhance the success of the integration process and bring about
greater utilization of remotely sensed information.
4.3.1 Building an Image with Local Input
Communicating environmental information using satellite imagery, or an imagebased map, is not a universal strategy (Johannes, 1981). For example, on several
islands within Indonesia, it is typical for the local managers to learn about spatial and
temporal changes to coral reef features without the aid of visual devices. Avoiding a
spatial context, stakeholders describe features in the form of lists emphasizing type and
abundance (World, 1994; Cesar et al., 1997; Fearnside, 1997; Pet-Soede et al., 1999).
When viewing or working with geographic maps or images, different people obtain
different amounts and kinds of information. This difference is the result not of the
subjectivity of the information but rather of the different degrees of the viewers’ ability
to extract information. There are differences between the interpreter’s image of reality,
parts of reality that have been mapped, and what actually exists (Salichtchev, 1977).
Therefore, remote sensing operators are challenged to illustrate complex environmental
271
Mapping and Management of Coral