Geographic Analysis Offers New Insight into Coral Disease Spread

University of FloridaIn the last 30 years, more than 90 percent of the reef-building coral responsible for maintaining major marine habitats and providing a natural barrier against hurricanes in the Caribbean has disappeared because of a disease of unknown origin.

Now a University of Florida geographer and his colleagues applied Geographic Information Systems, known as GIS — as well as software previously used to examine human illness — to show where clusters of diseased coral exist. Their findings, published this month in the journal PLoS One, may help scientists derive better hypotheses to determine what contributes to coral disintegration.

Read the paper: Evaluating Patterns of a White-Band Disease (WBD) Outbreak in Acropora palmata Using Spatial Analysis: A Comparison of Transect and Colony Clustering

“What you’ll find is that spatial techniques have been used relatively little in the coral research community,” said paper co-author Jason Blackburn, a UF professor of geography and member of UF’s Emerging Pathogens Institute. “With these methods, we gain a better understanding of the disease’s distribution across the reef.”

Comparing the difference between analyzing the coral dataset at the transect (A) verses colony-level (B) using DMAP. The following spatial parameters were used for both analyses: a 50 m2 grid cell resolution; and a 342.55 m filter radius, calculated using the Optimized Bandwidth (hopt) estimation method. The prevalence of white-band disease (WBD) clustering are shown in green, with darker shades indicating increased prevalence. Areas with statistically significant clustering rates (p ≤ 0.05), based on 1000 Monte Carlo simulations, are outlined in red. The numbers placed beside each significant clustering were used solely for identification purposes, and have no empirical value.

Microbiologists and toxicologists often run laboratory tests on small samples of Acropora species of coral to determine the factors that contribute to white-band disease, known as WBD. It’s visually identified as a white band moving from the base of the coral up, killing the coral tissue as it goes, leaving only the exposed coral skeleton behind.

Laboratory results spur a range of theories of causation — anything from opportunistic pathogens to specific bacterial infections. Other scientists suggest that WBD is not the result of an outside agent, such as bacteria, but rather a stress response from the coral in reaction to changes in the marine environment, such as ocean pollution and rising ocean temperatures due to climate change.

Yet the cause remains unclear. The goal of this current study was to use GIS and spatial analysis to search for patterns in a WBD outbreak that might point to a mode of transmission or cause, Blackburn said.

“What we wanted to test is how much data scientists should gather to get the full picture of disease,” he said. “What we found was that colony-level sampling, where individual Acropora colonies are counted and checked for disease, can show a far different picture of white-band disease than where only presence/absence of coral and disease are mapped.”

The researchers used data gathered in 2004 from scientists stationed at Buck Island National Monument in the U.S. Virgin Islands. Rather than determining only whether coral was affected by WBD, samplers at the station counted the individual number of healthy and non-healthy coral colonies. University researchers were then able to use this information in the Disease Mapping and Analysis Program, known as DMAP. The free software, designed by theUniversity of Iowa initially to study Sudden-Infant Death Syndrome, was used to create maps of WBD prevalence and to locate areas with significant disease clustering.

“While the focus of our study was on a specific white-band disease outbreak, our methods could be used to determine if there’s a spatial component to just about any type of situation that might be present in an underlying population,” said Jennifer Lentz, a Louisiana State University graduate student who is lead author on the paper. “For example, you could use these same techniques to determine whether people with cancer are clustered in a given geographical area, and if so is there something about those locations that might be contributing to the increased prevalence of cancer.”

The researchers determined that 3 percent of the Acropora coral around Buck Island had WBD. They also found the locations of significant disease clusters, information scientists can then use to narrow where they should take samples for further laboratory tests. This is the first of several studies established by the researchers exploring which types of spatial analysis are the most appropriate for various types of coral data from the Caribbean.

For thousands of years, Acropora was the predominant coral in the Caribbean, but more than three decades of disease have destroyed the species ability to survive, forcing marine life out of their coral habitats, which exposes them to attack by predators.

“When these structures are gone, certain fish species have nowhere to go,” said Lentz. “Whole marine communities start to collapse.”

[Source: University of Florida press release]

New Book Discusses Spatial Analysis of Census Data

Urban Policy and the Census

Urban Policy and the Census details how to interpret census data for use in GIS applications.

Urban Policy and the Census, the latest book from Esri Press, helps researchers and policy analysts gain a comprehensive understanding of census data and how it can be most effectively used for population research, policy planning, and decision-making.

Written by Heather MacDonald and Alan Peters, the book details a methodology for the spatial analysis of decennial census and American Community Survey data in areas including

  • Demographics
  • Economics
  • Housing
  • Transportation

“GIS analysis offers useful ways to interpret and communicate meaningful information, but to do so analysts need to consider the broader context of how that information is produced and the technical limitations of that information,” says MacDonald.

MacDonald, a former associate professor in the urban and regional planning program at the University of Iowa. He is a senior lecturer and course director of planning in the School of the Built Environment at the University of Technology in Sydney, Australia.

Peters previously held the positions of professor and chair of urban and regional planning at the University of Iowa, and is now a professor in the faculty of the built environment at the University of New South Whales. Peters and MacDonald also wrote Unlocking the Census with GIS (Esri Press, 2004).

Urban Policy and the Census (ISBN: 978-1-58948-222-7, 200 pages, $49.95 USD) is available at online retailers worldwide, at, or by calling 1-800-447-9778.  Outside the United States, visit for complete ordering options, or visit to contact your local Esri distributor. Interested retailers can contact Esri Press book distributor Ingram Publisher Services.

[Source: Esri press release]

Spatial Cloud Computing: How Can the Geospatial Sciences Use and Help Shape Cloud Computing?

International Journal of Digital EarthInternational Journal of Digital Earth, Volume 4, Issue 4, 2011

Chaowei Yang, Michael Goodchild, Qunying Huang, Doug Nebert, Robert Raskin, Yan Xu, Myra Bambacus, and Daniel Fay

“The geospatial sciences face grand information technology (IT) challenges in the twenty-first century: data intensity, computing intensity, concurrent access intensity and spatiotemporal intensity. These challenges require the readiness of a computing infrastructure that can: (1) better support discovery, access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries; (2) provide real-time IT resources to enable real-time applications, such as emergency response; (3) deal with access spikes; and (4) provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge. The emergence of cloud computing provides a potential solution with an elastic, on-demand computing platform to integrate – observation systems, parameter extracting algorithms, phenomena simulations, analytical visualization and decision support, and to provide social impact and user feedback – the essential elements of the geospatial sciences.

System of systems solution includes Earth observation, parameter extraction, model simulations, decision support, social impact and feedback.

System of systems solution includes Earth observation, parameter extraction, model simulations, decision support, social impact and feedback.

“We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles, the kernel of the geospatial sciences, could be utilized to ensure the benefits of cloud computing. Four research examples are presented to analyze how to: (1) search, access and utilize geospatial data; (2) configure computing infrastructure to enable the computability of intensive simulation models; (3) disseminate and utilize research results for massive numbers of concurrent users; and (4) adopt spatiotemporal principles to support spatiotemporal intensive applications. The paper concludes with a discussion of opportunities and challenges for spatial cloud computing (SCC).”

MCDA-GIS Integrated Approach for Optimized Landfill Site Selection for Growing Urban Regions: An Application of Neighborhood-proximity Analysis

Annals of GIS, Volume 17, Issue 1, 01 March 2011

Yashon O. Ouma; Emmanuel C. Kipkorir; Ryutaro Tateishi

“The exponential rise in urban population and the resulting urban waste generation in developing countries over the past few decades, and the resulting accelerated urbanization phenomenon has brought to the fore the necessity to engineer environmentally sustainable and efficient urban waste disposal and management systems. Intelligent and integrated landfill siting is a difficult, complex, tedious, and protracted process requiring evaluation of many different criteria. Optimized siting decisions have gained considerable importance in ensuring minimum damage to the various environmental sub-components as well as reducing the stigma associated with the residents living in its vicinity. This article addresses the siting of a new landfill using a multi-criteria decision analysis integrated with overlay analysis within a geographical information system. The integrated multi-criteria decision analysis-geographical information system employs a two-stage analysis, synergistically, to form a spatial decision support system for landfill siting in fast-growing urban centers. Several correlated factors are considered in the siting process including transportation systems, water resources, land use, sensitive sites, and air quality. Weightings were assigned to each criterion depending upon their relative significance and ratings in accordance with the relative magnitude of impact. The results, analyzed using neighborhood-proximity analysis, show the effectiveness of the system in the site-selection process for Eldoret Municipality (Kenya), in the short- and long-term solid waste disposal siting options.”

A Semi-automated GIS Model for Extracting Geological Structural Information from a Spaceborne Thematic Image

GIScience & Remote SensingGIScience & Remote Sensing, Volume 48, Number 2 / April-June 2011

A. Dadon, A. Peeters, E. Ben-Dor, and A. Karnieli

“This paper presents a semi-automated GIS model for extracting structural information from a spaceborne imaging spectroscopy classification of sedimentary rocks by combining the IS classification with a digital terrain model. The output consists of a database with structural attributes, specifically the dip and strike, of the geological layers. The model was evaluated statistically for its accuracy with promising results, which demonstrate its potential to support field surveys, for geological mapping, for 3D modeling of the subsurface, and for geological spatial analysis.”