Another piece of ESRI history from Dr. Armando Guevara, President and CEO of Visual Intelligence (and former ESRI employee).
The Urban and Regional Information Systems Association (URISA) is accepting applications for its Exemplary Systems in Government (ESIG) Awards through April 11, 2014. The awards recognize exceptional achievements in the application of geospatial information technology that have improved the delivery and quality of government services. The award competition is open to all public agencies at the federal, state/provincial, regional and local levels.
Applications may be submitted in two categories, Single Process and Enterprise Systems:
- SINGLE PROCESS SYSTEMS – Systems in this category are outstanding and working examples of applying information system technology to automate a specific SINGLE process or operation involving one department or sub-unit of an agency. The system application results in extended and/or improved government services that are more efficient and/or save money.
- ENTERPRISE SYSTEMS – Systems in this category are outstanding and working examples of using information systems technology in a multi-department environment as part of an integrated process. These systems exemplify effective use of technology yielding widespread improvements in the process(es) and/or service(s) involved and/or cost savings to the organization.
Applications must be submitted by April 11, 2014. Winners in each category will be recognized during GIS-Pro 2014: URISA’s 52nd Annual Conference, September 8-11, 2014 in New Orleans, Louisiana.
For more information or to review submissions from previous winning systems, visit http://www.urisa.org/awards/exemplary-systems-in-government/.
[Source: URISA news release]
BMC Public Health, 2014 (14:11), Published 08 January 2014
By Ta-Chien Chan, Jing-Shiang Hwang, Rung-Hung Chen, Chwan-Chuen King, and Po-Huang Chiang
Severe epidemics of enterovirus have occurred frequently in Malaysia, Singapore, Taiwan, Cambodia, and China, involving cases of pulmonary edema, hemorrhage and encephalitis, and an effective vaccine has not been available. The specific aim of this study was to understand the epidemiological characteristics of mild and severe enterovirus cases through integrated surveillance data.
All enterovirus cases in Taiwan over almost ten years from three main databases, including national notifiable diseases surveillance, sentinel physician surveillance and laboratory surveillance programs from July 1, 1999 to December 31, 2008 were analyzed. The Pearson’s correlation coefficient was applied for measuring the consistency of the trends in the cases between different surveillance systems. Cross correlation analysis in a time series model was applied for examining the capability to predict severe enterovirus infections. Poisson temporal, spatial and space-time scan statistics were used for identifying the most likely clusters of severe enterovirus outbreaks. The directional distribution method with two standard deviations of ellipse was applied to measure the size and the movement of the epidemic.
The secular trend showed that the number of severe EV cases peaked in 2008, and the number of mild EV cases was significantly correlated with that of severe ones occurring in the same week [r = 0.553, p < 0.01]. These severe EV cases showed significantly higher association with the weekly positive isolation rates of EV-71 than the mild cases [severe: 0.498, p < 0.01 vs. mild: 0.278, p < 0.01]. In a time series model, the increase of mild EV cases was the significant predictor for the occurrence of severe EV cases. The directional distribution showed that both the mild and severe EV cases spread extensively during the peak. Before the detected spatio-temporal clusters in June 2008, the mild cases had begun to rise since May 2008, and the outbreak spread from south to north.
Local public health professionals can monitor the temporal and spatial trends plus spatio-temporal clusters and isolation rate of EV-71 in mild and severe EV cases in a community when virus transmission is high, to provide early warning signals and to prevent subsequent severe epidemics.
- Read the paper [PDF]
Spatial Distribution of Soil Organic Carbon and Total Nitrogen Based on GIS and Geostatistics in a Small Watershed in a Hilly Area of Northern China
PLOS One, Published Online 31 December 2013
By Gao Peng, Wang Bing, Geng Guangpo, and Zhang Guangcan
“The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0–20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km2) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging.
“The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed.”
Proceedings of the Royal Society B | Biological Sciences, published 06 November 2013
By L. M. Wedding, A. M. Friedlander, J. N. Kittinger, L. Watling, S. D. Gaines, M. Bennett, S. M. Hardy, and C. R. Smith
“Increases in the demand and price for industrial metals, combined with advances in technological capabilities have now made deep-sea mining more feasible and economically viable. In order to balance economic interests with the conservation of abyssal plain ecosystems, it is becoming increasingly important to develop a systematic approach to spatial management and zoning of the deep sea. Here, we describe an expert-driven systematic conservation planning process applied to inform science-based recommendations to the International Seabed Authority for a system of deep-sea marine protected areas (MPAs) to safeguard biodiversity and ecosystem function in an abyssal Pacific region targeted for nodule mining (e.g. the Clarion–Clipperton fracture zone, CCZ). Our use of geospatial analysis and expert opinion in forming the recommendations allowed us to stratify the proposed network by biophysical gradients, maximize the number of biologically unique seamounts within each subregion, and minimize socioeconomic impacts.
“The resulting proposal for an MPA network (nine replicate 400 × 400 km MPAs) covers 24% (1 440 000 km2) of the total CCZ planning region and serves as example of swift and pre-emptive conservation planning across an unprecedented area in the deep sea. As pressure from resource extraction increases in the future, the scientific guiding principles outlined in this research can serve as a basis for collaborative international approaches to ocean management.”
GIScience Research Track
Esri International User Conference
14-18 July, 2014
San Diego, California
Call for Papers, Transactions in GIS special issue
GI Science researchers are invited to present original manuscripts for a peer-reviewed journal and presentation in the GIScience Research Track of the 2014 Esri International User Conference.
Papers in this special track must focus on cutting-edge research in GIScience and need not be Esri software related. Full papers will be included in a special issue of the journal Transactions in GIS to be distributed at the 2014 Conference. Abstracts (500 words) must be submitted to Dr. John Wilson, University of Southern California, by 15th December, 2013.
The Transactions in GIS editorial team will review abstracts based on their GIScience content and select a maximum of nine abstracts to become full papers. Notice of acceptance will occur by end of December, 2013. Full papers (maximum 6,000 words plus figures, tables, and references in appropriate format for publication) must be submitted to Dr. Wilson for independent review by 15th February, 2014. Reviewed papers will be returned to authors by 15th March, 2014 and final manuscripts must be returned by 8th April, 2014, to be included in the special issue of Transactions in GIS.
A listing of the 2013 accepted papers can be found at the journal website: http://onlinelibrary.wiley.com/doi/10.1111/tgis.2013.17.issue-3/issuetoc
For questions or guidelines on this GIScience Research Track, please contact Michael Gould at firstname.lastname@example.org.
Abstracts should be submitted via email with a subject line “Esri GIScience Abstract, Authors Last Name” no later than 15th December, 2013 to:
Dr. John Wilson, email@example.com
Spatial Distribution and Conservation of Speckled Hind and Warsaw Grouper in the Atlantic Ocean off the Southeastern U.S.
PLOS ONE, 19 November 2013
By Nicholas A. Farmer and Mandy Karnauskas
“There is broad interest in the development of efficient marine protected areas (MPAs) to reduce bycatch and end overfishing of speckled hind (Epinephelus drummondhayi) and warsaw grouper (Hyporthodus nigritus) in the Atlantic Ocean off the southeastern U.S. We assimilated decades of data from many fishery-dependent, fishery-independent, and anecdotal sources to describe the spatial distribution of these data limited stocks. A spatial classification model was developed to categorize depth-grids based on the distribution of speckled hind and warsaw grouper point observations and identified benthic habitats. Logistic regression analysis was used to develop a quantitative model to predict the spatial distribution of speckled hind and warsaw grouper as a function of depth, latitude, and habitat.
“Models, controlling for sampling gear effects, were selected based on AIC and 10-fold cross validation. The best-fitting model for warsaw grouper included latitude and depth to explain 10.8% of the variability in probability of detection, with a false prediction rate of 28–33%. The best-fitting model for speckled hind, per cross-validation, included latitude and depth to explain 36.8% of the variability in probability of detection, with a false prediction rate of 25–27%. The best-fitting speckled hind model, per AIC, also included habitat, but had false prediction rates up to 36%. Speckled hind and warsaw grouper habitats followed a shelf-edge hardbottom ridge from North Carolina to southeast Florida, with speckled hind more common to the north and warsaw grouper more common to the south. The proportion of habitat classifications and model-estimated stock contained within established and proposed MPAs was computed. Existing MPAs covered 10% of probable shelf-edge habitats for speckled hind and warsaw grouper, protecting 3–8% of speckled hind and 8% of warsaw grouper stocks. Proposed MPAs could add 24% more probable shelf-edge habitat, and protect an additional 14–29% of speckled hind and 20% of warsaw grouper stocks.”