Abstract
Degradation of estuarine ecosystems caused by human‐induced stressors justifies finding efficient ways to manage and protect these environments. This study demonstrates the utilities of satellite remote sensing, landscape metrics and multivariate statistical analysis for quantifying landscape pattern and its change in a highly sensitive estuarine watershed. The objective of this study was to identify the appropriate method for landscape pattern characterization in the Pensacola estuarine drainage area (PEDA) as part of an interdisciplinary effort to develop environmental indicators for integrated estuarine ecosystem assessment in the Gulf of Mexico. The study has several components. First, two land‐use and land‐cover maps were produced from satellite imagery by using hierarchical classification and spatial reclassification techniques. Then, 56 metrics of landscape composition or configuration were computed from the two maps for different spatial observational units, including the PEDA, four sub‐watersheds, and three predefined buffer areas. Because some of the landscape metrics may be correlated with each other, landscape ecology principles, principal component analysis and Spearman's rank correlation analysis were used to eliminate redundant metrics. This resulted in a parsimonious set of core metrics which were not redundant but spanned the important dimensions of landscape structure and pattern. These core metrics were finally used to quantify landscape pattern for different spatial observational units at the two different years. Landscape structure has been found to be more fragmented in the Pensacola Bay watershed, around the city centres and along the coastlines, where urbanization and human economic activities are more concentrated. Over time, the landscape mosaics became more heterogeneous while the classes of patches tended to be more fragmented. Results of this study should help coastal managers in the PEDA target those areas in need of conservation and protection.
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