About the Author    Introduction    Methods and Procedures    Analysis and Results    Discussion    Conclusion    Bibliography

Bibliography

Grotzinger, J., Jordan, T. H., Press, F., Siever, R. (2007). Understanding Earth Fifth Edition. New York, NY: W.H. Freeman and
        Company.

Combs, D. L., Parrish, R. G., McNabb, S. J. N., Davis, J. H. (1996) “Deaths Related to Hurricane Andrew in Florida and Louisiana,
        1992.” International Journal of Epidemiology Vol. 25, No. 3, 537 – 544.

Wikipedia Web Site (2008) Moran’s I. Last Accessed April 19th 2008, from the World Wide Web:
        http://en.wikipedia.org/wiki/Moran%27s_I

State Of Florida: The Unofficial Public Resource of the American Safety Council for Florida Residents & Visitors (2008)
        Florida Quick Facts Last Accessed April 20th 2008, from the World Wide Web:
        http://www.stateofflorida.com/Portal/DesktopDefault.aspx?tabid=95

Klinkenberg, B. (2008, Jan. 28). “Understanding Landcape Metrics: Patterns and Processes” Geography 471 lecture presented at the         University of British Columbia.

Data Links

  Geodata.gov: U.S. Maps & Data

  Center For Hazards and Risk Research at Columbia University

  Census 2000 Boundary Files, U.S. Census Bureau

  Florida Coastal Evergaldes Long Term Ecological Research

Pictures Sources

Detailed Layer Information

        Global Cyclone Mortality Risks and Distribution (gdcycmrt) is a 2.5 minute grid of global cyclone mortality risks. Gridded Population of the World, Version 3 (GPWv3) data provide a baseline estimation of population per grid cell from which to estimate potential mortality loss. Mortality loss estimates per hazard event are calculated using regional, hazard-specific mortality records of the Emergency Events Database (EM-DAT) that span the 20 years between 1981 and 2000. Data regarding the frequency and distribution of cyclone hazard are obtained from the Global Cyclone Hazard Frequency and Distribution dataset. In order to more accurately reflect the confidence associated with the data and procedures, the potential mortality estimate range is classified into deciles, 10 classes of an approximately equal number of grid cells, providing a relative estimate of cyclone-based mortality risks. This dataset is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN). The purpose is to provide a means of assessing global cyclone mortality risks and distribution. The data are available from the Socioeconomic Data and Applications Center (SEDAC) in American Standard Code for Information Interchange (ASCII) and dBASE (DBF) formats via FTP at ftp://ftp.ciesin.columbia.edu/pub/hotspots/.

        Global Cyclone Proportional Economic Loss Risk Deciles (gdcycpro) is a 2.5 minute grid of cyclone hazard economic loss as proportions of Gross Domestic Product (GDP) per analytical unit. Estimates of GDP at risk are based on regional economic loss rates derived from historical records of the Emergency Events Database (EM-DAT). Loss rates are weighted by the hazard's frequency and distribution. The methodology of Sachs et al. (2003) is followed to determine baseline estimates of GDP per grid cell. To better reflect the confidence surrounding the data and procedures, the range of proportionalities is classified into deciles, 10 class of an approximately equal number of grid cells of increasing risk. This dataset is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN). The purpose is to provide a spatial surface of the proportional economic impacts of global cyclone hazard. The data are available from the Socioeconomic Data and Applications Center (SEDAC) in Ameard Code for Information Interchange (ASCII) format via FTP at ftp://ftp.ciesin.columbia.edu/pub/hotspots/.

        Tropical storm intensity zone global coverage. This dataset was derived from the Munich Reinsurance Company's (Munich Re) World Map of Natural Hazards. This data layer shows tropical storm intensity zones based on the five different wind speeds of the Saffir-Simpson Hurricane Scale. The Saffir-Simpson Scale is used by the National Weather Service to give public safety officials an assessment of a tropical storm's potential for wind and storm surge damage. The scale indicates probable property damage for each of the following five wind speed categories: 1) 118-153 km/h, 2) 154-177 km/h, 3) 178-209 km/h, 4) 210-249 km/h, 5) 250+ km/h. The Storm Intensity Zone layer shows that there is a 10% probability of a storm of this intensity striking in the next 10 years (which is equivalent to a return period of 100 years). Purpose:A general-purpose global tropical storm intensity zone data layer designed to support Geographic Information Systems applications.

         Surface Elevation_24. This dataset was created to represent the land surface elevation at 1:24,000 scale for Florida. The elevation contour lines representing the land surface elevation were digitized from United States Geological survey 1:24,000 (7.5 minute) quadrangles and were compiled by South Florida, South West Florida, St. Johns River and Suwannee River Water Management Districts and FDEP. QA and corrections to the data were supplied by the Florida Department of Environmental Protection's Florida Geological Survey and the Division of Water Resource Management. This data, representing over 1,000 USGS topographic maps, spans a variety of contour intervals including 1 and 2 meter and 5 and 10 foot. The elevation values have been normalized to feet in the final data layer. Attributes for closed topographic depressions were also captured where closed (hautchered) features were identified and the lowest elevation determined using the closest contour line minus one-half the contour interval. This data was derived from the USGS 1:24,000 topographic map series. The data is more than 20 years old and is likely out-of-date in areas of high human activity. Purpose:This dataset was created to represent the land surface elevation at 1:24,000 scale for Florida.

Special Thanks