Urban sprawl, habitat fragmentation, landsat, land cover, fragstats, gis


The widespread loss and degradation of habitat constitutes the largest threat to biodiversity in North America. While regulatory programs such as the Endangered Species Act of 1973 and wetland permitting under the Clean Water Act have addressed acute assaults on critical habitat, large areas of unprotected uplands have been lost. Urban development, particularly the advent of lower density suburban and rural sprawl, has greatly diminished the extent of contiguous patches of forest habitat and introduced a host of other undesirable effects on ecosystem function. This study sought to evaluate the extent of urban sprawl and its effects on ecological integrity in Florida using Landsat-derived land cover data collected by the Florida Fish and Wildlife Conservation Commission (FWC) circa 1987 and 2003. Chapter 1 described a novel GIS technique for correcting the systematic errors in the FWC 1987 and 2003 land cover data and converting those data to a common classification system so that they could be used in any ad hoc land cover change analysis. Comparison to ground-truth observations demonstrated a significant improvement in the accuracy of the land cover data following the Land Cover Correction Process (LCCP). Change detection between 1987 and 2003 using the correct land cover revealed trends in land cover conversion that were very different from previously published results derived from the original FWC land cover data. Conversion to urban uses in the corrected data was 47,293 ha lower, and conversion to agricultural uses was reduced by 196,773 ha, resulting in 244,067 ha less anthropogenic land conversion than had been previously estimated. Although the corrected land cover data showed that overall land conversion of natural areas was lower compared to the earlier estimate, the corrected data showed proportionally greater habitat losses for four important habitat types: Pinelands (-10.08% in the corrected land cover as compared to -5.90% in the original FWC data); upland forest (-9.46% versus 6.37%); sandhill (-13.90% versus 11.18%); and scrub (-15.52% versus -9.83%). Given the relatively small areal extent of some of these habitats, the larger percent loss estimates over the study period revealed by the corrected land cover data are cause for even greater concern by conservation planners and policymakers. Now that its utility has been demonstrated, the LCCP technique can be applied to any pair of roughly similar land cover mapping datasets provided that their original classification systems can be composed by a cross-walk into a single scheme, and that one or more ancillary data sets are available to serve in the tie-breaker role performed here by the land use data from Florida's Water Management Districts. The Soil Survey Geographic (SSURGO) and State Soil Geographic (STATSGO) soils data of the National Resource Conservation Service, the National Land Cover Dataset (NLCD) or the statewide habitat mapping of the USGS GAP Analysis Program could be adapted to provide the ancillary tie-breaker data required by the LCCP to conduct change detection between disparate land cover data sources heretofore considered too incompatible for that purpose. In Chapter 2, measures of urban sprawl, habitat loss and fragmentation in Florida were estimated using the corrected land cover data for 1987 and 2003. The Northwest and North regions of the state exhibited significantly higher indices of urban sprawl, habitat loss and habitat fragmentation via application of the Moran's I statistic. Reducing urban sprawl and habitat fragmentation spatial metrics to simple ordination variables through the use of non-metric multidimensional scaling produced new measures of urban sprawl and habitat fragmentation that correlated strongly with the original FRAGSTATS metrics, but could be more easily mapped and interpreted. Urban and Habitat ordination metrics were each spatially autocorrelated (Local Moran's I and K-means grouping analyses) but not correlated to each other using the Procrustes analysis PROTEST statistic (m2 = 0.952, p = 0.061). In contrast, individual urban sprawl metrics (CA, NP, LPI, ED, SHAPE_AM and DCAD) correlated with habitat fragmentation. NP and DCAD appeared to be particularly useful in predicting fragmentation, and county governments should take measures to reduce establishment of new urban patches to minimize NP and DCAD. Chapter 3 explored the relationship between environmental outcomes in habitat loss and fragmentation and the quality of county local government comprehensive plans. The use of NMS analysis provided a powerful technique for capturing the intrinsic variability of the Local Government Comprehensive Plan (LGCP) plan scoring systems of Brody (2003) and Pannozzo (2013) into a pair of variables each that could be used to explore associations with metrics of urban sprawl, habitat fragmentation and other county characteristics that influence urban growth and development. The geographic distribution of LGCP plan quality favored coastal counties with higher quality plans over inland counties, and there was some evidence that plans in Central and South regions of Peninsular Florida were superior to those in the North and Northwest Panhandle regions. Key factors in plan quality, specifically Coordination and Management, were strongly associated with urban sprawl or habitat fragmentation outcomes. The resources available to counties in the form of tax revenues, whether the county possessed a rural or urban economy, and the county's political makeup also appeared related to LGCP plan quality, urban sprawl or habitat fragmentation outcomes. More research will be needed to elucidate the specific causal mechanisms behind the implementation of local government planning that resulted in the observed environmental outcomes.


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Graduation Date





Weishampel, John


Doctor of Philosophy (Ph.D.)


College of Sciences



Degree Program

Conservation Biology; Applied Conservation Biology








Release Date

December 2014

Length of Campus-only Access


Access Status

Doctoral Dissertation (Open Access)


Dissertations, Academic -- Sciences; Sciences -- Dissertations, Academic

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Biology Commons