15.2.4 Balancing Costs and Product Quality
Managers often accept maps at face value without any recognition of the underlying methods used and associated product quality. Additionally, many maps are,
in fact, far more complex than required by the management needs of the users,
which can be as basic as simply guiding selection of monitoring sites. A recent
study by Roelfsema and Phinn (2008) found that three main items affected user
selection of a suitable mapping approach: (1) variation in coral reef environments;
(2) purpose of the habitat map; and (3) resource management requirements. The
study evaluated the accuracy, cost, and relevance of eight commonly used benthic
cover mapping approaches applied in three different coral reef environments in
Fiji. The mapping approaches differed from each other by: image type; level of
image correction; detail of calibration and validation field data; and/or classification method (e.g., manual digitizing, supervised classification). Each approach
and resulting output map was assessed quantitatively, by calculating map accuracy, production time and cost, and qualitatively, by subjective evaluation by users
from local marine monitoring agencies in Fiji. In this case study, analysis of results
for a 14 km
2 fringing reef showed that users: (1) perceived that maps showing the
highest detail best represented the reef study area, even though they were sometimes more detailed than required for their mapping purposes; (2) rated most maps
evenly when provided with the associated cost and time to create maps, without
receiving information on map accuracy; and (3) favored detail and higher accuracy
above cost and production when all information was provided (Fig. 15.3).
It is important to note, however, that there is no unique answer to which mapping
methods and techniques will be most appropriate and cost-effective for each study
area and application. The time and cost involved in mapping and monitoring coral
reefs can vary between mapping approaches, study questions, and the environmental characteristics of the study area, such as extent, heterogeneity, water depth
variations, water clarity range, and remoteness (Mumby et al. 1999; Roelfsema and
Phinn 2008). Time and cost, therefore, need to be considered across three main
components: (1) project planning; (2) field work; and (3) processing, analysis and
reporting. In addition, cost calculations must include personnel, image and
equipment requirements, as well as skill and experience levels needed. Given that
coral reef management agencies often operate on a limited budget, in such cases
consideration should also be given to collaborations with research centers or other
government agencies within and external to their countries, which may have greater
technical capacity and resources to produce higher quality map products.
15.3 Example Applications
The sections below describe several examples of how remote sensing data are
actively being used for coral reef management and monitoring applications. In
each case, we describe the context of the application, the types of data that are
412
S. Jupiter et al.
Managers often accept maps at face value without any recognition of the underlying methods used and associated product quality. Additionally, many maps are,
in fact, far more complex than required by the management needs of the users,
which can be as basic as simply guiding selection of monitoring sites. A recent
study by Roelfsema and Phinn (2008) found that three main items affected user
selection of a suitable mapping approach: (1) variation in coral reef environments;
(2) purpose of the habitat map; and (3) resource management requirements. The
study evaluated the accuracy, cost, and relevance of eight commonly used benthic
cover mapping approaches applied in three different coral reef environments in
Fiji. The mapping approaches differed from each other by: image type; level of
image correction; detail of calibration and validation field data; and/or classification method (e.g., manual digitizing, supervised classification). Each approach
and resulting output map was assessed quantitatively, by calculating map accuracy, production time and cost, and qualitatively, by subjective evaluation by users
from local marine monitoring agencies in Fiji. In this case study, analysis of results
for a 14 km
2 fringing reef showed that users: (1) perceived that maps showing the
highest detail best represented the reef study area, even though they were sometimes more detailed than required for their mapping purposes; (2) rated most maps
evenly when provided with the associated cost and time to create maps, without
receiving information on map accuracy; and (3) favored detail and higher accuracy
above cost and production when all information was provided (Fig. 15.3).
It is important to note, however, that there is no unique answer to which mapping
methods and techniques will be most appropriate and cost-effective for each study
area and application. The time and cost involved in mapping and monitoring coral
reefs can vary between mapping approaches, study questions, and the environmental characteristics of the study area, such as extent, heterogeneity, water depth
variations, water clarity range, and remoteness (Mumby et al. 1999; Roelfsema and
Phinn 2008). Time and cost, therefore, need to be considered across three main
components: (1) project planning; (2) field work; and (3) processing, analysis and
reporting. In addition, cost calculations must include personnel, image and
equipment requirements, as well as skill and experience levels needed. Given that
coral reef management agencies often operate on a limited budget, in such cases
consideration should also be given to collaborations with research centers or other
government agencies within and external to their countries, which may have greater
technical capacity and resources to produce higher quality map products.
15.3 Example Applications
The sections below describe several examples of how remote sensing data are
actively being used for coral reef management and monitoring applications. In
each case, we describe the context of the application, the types of data that are
412
S. Jupiter et al.