Keywords: spatial autocorrelation, coral reef monitoring, multispectral discrimination

Abstract
Rather than attempt to remotely identify specific benthic habitats with similar optical properties, a more appropriate use of available satellite technology may be to examine benthic homogeneity of a coral reef ecosystem with the hypothesis that a healthy reef will display great heterogeneity, but a dead algae-covered reef will be relatively homogeneous. Such an approach to ecosystem analysis could prove to be efficient with respect to time, human resources, and data storage, and would produce results that could be directly applied to a realistic management scheme with "minimal regrets". A measure of spatial autocorrelation, the Getis Statistic, used in a case study of SPOT imagery shows potential in evaluating the well-being of a coral reef ecosystem.

Introduction
Over the past decade, there have been increased efforts to establish better management and conservation measures to protect the diversity of the biologically rich areas of coral reefs and related benthic habitats. Remote sensing can be used as a management tool to map and monitor the geographic extent of coral reefs to a limited degree given the available satellite imagery, but perhaps its true value is in its ability to identify areas of change over time. Analysis of hyperspectral data has produced encouraging results in the discrimination of common and optically similar coral reef substrates such as healthy corals, bleached corals, sea grass, and algae-covered surfaces (Holden and LeDrew, 1998, 1999, 2000; Hardy et al., 1992; Myers et al., 1999; Clark et al., 2000), but at the present time, such high spectral resolution data is unavailable from a satellite platform. While currently available satellite sensors have global mapping and monitoring capabilities, the accuracy and precision attainable when applied to reef ecosystems is relatively low due to the large pixel size and broad spect ral bandwidths of these sensors. Because of the deteriorating global state of coral reef and related benthic ecosystems , however, waiting for the ideal technology for accurate and precise imaging of submerged benthic habitats is not realistic. Instead, there is a need to utilize the available imaging technology, assess the accuracy and acknowledge the limitations. SPOT HRV, Landsat TM and possibly SeaWiFS data are viable options since they provide moderate spatial resolution (20m, 30m, and 100m respectively) and spectral resolution (2, 6, and 6 useful optical broadbands, respectively) in the visible wavelengths while covering large geographic areas at regular time intervals (revisit times of approximately 26, 16, and 1 day, respectively). The spectral resolution of these sensors is limiting if optically similar substrates, such as healthy coral and algae-covered surfaces, need to be discriminated due to the small number of broad wavebands, however little conclusive research has been conducted to examine the optimal spectral resolution requirements for bottom type detection (See Hardy et al., 1992; Myers et al., 1999; Holden and LeDrew, 1998 and 1999; Clark et al., 2000; Holden and LeDrew, 2000). Additionally, the spatial characteristics are limiting if small features, such as discrete coral heads, need to be definitively located since the pixel sizes are relatively large compared to the size of common coral reef features (techniques such as sub pixel feature identification could minimize this limitation). Similarly, satellite technology may not be appropriate if a high temporal resolution data set is required to examine rapid changes because of infrequent revisit times and cloud-cover issues. The alternative is to conduct (often prohibitively) expensive and logistically complex airborne surveys at a higher spatial, spectral and temporal resolution, which may not be operationally feasible in the developing regions in which coral reefs are found.

An appropriate approach to using available satellite imagery to monitor coral reef ecosystems is the use of benthic homogeneity as indicated by spatial autocorrelation to evaluate the ecosystem (LeDrew et al, 2000). Spatial autocorrelation is defined as the situation where one variable (reflectance value of a pixel in this case) is related to another variable located nearby (surrounding pixels). Spatial autocorrelation is useful since it not only considers the value of the pixel (magnitude of reflectance), but also the relationship between that pixel and its surrounding pixels. Our hypothesis is that a healthy coral reef ecosystem will be heterogeneous, but a dead, algae-dominated coral reef will be relatively spatially homogeneous. This approach does not necessarily facilitate direct identification of substrate type, but it does allow for fast assessment of changes in ecosystem composition over a large geographic area if a time series of imagery is available. The results of such an approach utilizing currently available satellite technology may contribute to more effective management of coral reef resources.

The specific objective of this paper is to perform a case study using a local indicator of spatial autocorrelation (the Getis Statistic) based on SPOT imagery of Bunaken National Marine Park, North Sulawesi, Indonesia. This case study is performed to examine the feasibility of using measures of spatial homogeneity to evaluate changes in benthic habitat over time. The accuracy of the Getis Statistic approach is estimated based on familiarity with the study site and field data collection during time of satellite image acquisition (1997and 2000).