Using Spatial Analysis to Improve Health Care Services and Delivery at Baystate Health

Journal of Map & Geography LibrariesJournal of Map & Geography Libraries, Volume 7, Issue 3, 2011

Jane L. Garb and Richard B. Wait

“Baystate Health has been recognized by the industry for its innovative and wide-ranging use of geographic information systems (GISs) to address problems in health. Spatial analysis is a key component in the effective use of GISs in health care for data exploration, hypothesis testing, and modeling. This paper describes GIS applications by the Health Geographics Program at Baystate Health.

Flow of youth violence and police sectors in Springfield, MA. Arrow width indicates volume of flow.

Flow of youth violence and police sectors in Springfield, MA. Arrow width indicates volume of flow.

“These applications include direct patient care, epidemiologic research, disease prevention and intervention, strategic planning, and marketing. We directed particular attention to the spatial analytic methods used in these applications. Finally, the challenges faced in obtaining and using health data for our analysis are discussed.”

Spatial Dynamics of Human-Origin H1 Influenza A Virus in North American Swine

PLoS PathogensPLoS Pathogens, June 2011

Martha I. Nelson, Philippe Lemey, Yi Tan, Amy Vincent, Tommy Tsan-Yuk La, Susan Detmer5, Cécile Viboud, Marc A. Suchard, Andrew Rambaut, Edward C. Holmes, and Marie Gramer

“The emergence and rapid global spread of the swine-origin H1N1/09 pandemic influenza A virus in humans underscores the importance of swine populations as reservoirs for genetically diverse influenza viruses with the potential to infect humans. However, despite their significance for animal and human health, relatively little is known about the phylogeography of swine influenza viruses in the United States. This study utilizes an expansive data set of hemagglutinin (HA1) sequences (n = 1516) from swine influenza viruses collected in North America during the period 2003–2010. With these data we investigate the spatial dissemination of a novel influenza virus of the H1 subtype that was introduced into the North American swine population via two separate human-to-swine transmission events around 2003.

Evolutionary origins of H1 swine influenza viruses in North America

Evolutionary origins of H1 swine influenza viruses in North America

“Bayesian phylogeographic analysis reveals that the spatial dissemination of this influenza virus in the US swine population follows long-distance swine movements from the Southern US to the Midwest, a corn-rich commercial center that imports millions of swine annually. Hence, multiple genetically diverse influenza viruses are introduced and co-circulate in the Midwest, providing the opportunity for genomic reassortment. Overall, the Midwest serves primarily as an ecological sink for swine influenza in the US, with sources of virus genetic diversity instead located in the Southeast (mainly North Carolina) and South-central (mainly Oklahoma) regions. Understanding the importance of long-distance pig transportation in the evolution and spatial dissemination of the influenza virus in swine may inform future strategies for the surveillance and control of influenza, and perhaps other swine pathogens.”

Highly Anticipated Events Scheduled For GIS-Pro 2011 in Indianapolis

GIS-Pro 2011: URISA’s 49th Annual ConferenceA number of events will be featured at GIS-Pro 2011: URISA’s 49th Annual Conference taking place November 1-4, 2011 in Indianapolis. An “All Things Geospatial” evening Ignite session, Lightning Talks, an OpenStreetMap Lab, Esri Technical Workshops and User Group Meeting, and a DevMeetUp are all on the program this year.  In addition to full-day URISA Certified Workshops, peer presentations and invited speakers and panelists, URISA is also hosting a working group during the conference to develop the final tier of the Geospatial Technology Competency Model for the U.S. Department of Labor (DOL). This tier will establish the competencies needed for GIS managers.

Conference Chair, Geney Terry, GISP noted that the educational content of the conference will “cover professional development, tools to measure the success of GIS like ROI and maturity models, state of the art technologies, geospatial industry trends, sharing of leadership experience, and cross-jurisdictional collaboration.  Several sessions will be conducted more like a training class and you will have information in your hands that you can take back to work and implement immediately. One area of the GIS profession that the conference has not focused on extensively in the past is the developer community, both application and web.  That’s changing this year.  We’ve included several sessions, both daytime breakout sessions and evening events, that will provide opportunities for developers to learn, collaborate, and network.  These sessions cover industry standard software and open source applications.”

URISA Certified Workshops, this year offered at no additional cost with your conference registration, will be presented on November 1. Attendees may choose one workshop to attend (note that some of the workshops are already nearing capacity):

  • Business Intelligence and Data Integration for the GIS Professional
  • Cartography and Map Design
  • 3D Geospatial: Project Implementation Methods and Best Practices
  • Open Source GIS
  • GIS Strategic Planning
  • Public Data, Public Access, Privacy and Security

Featured Sessions include:

One Government and Data Sharing – Vincent Hoong, Executive Director of the Singapore Land Authority will discuss in the Opening Keynote how they use a ‘one government’ approach to motivate agencies to work together and how they’ve developed a policy framework to successfully guide data sharing.

Thought Leaders Panel – Executives from a variety of national and international corporations that use GIS to solve their own problems will tell you why they decided to use GIS, and how they convinced their organizations to invest in geospatial data and technology.

Geospatially Enabling Decision-making – Find out how the Kansas Legislature is integrating geospatial data and location into the process of making laws.  You’ll gain ideas about how to geospatially enable your own state or provincial legislatures, county commissions, municipal councils, tribal councils, or any deliberative body.

Recognize the 2011 GIS Hall of Fame inductees, Exemplary Systems in Government and URISA Service Award winners during the Awards Breakfast; network at the GISP and Young Professional receptions; and expand your professional community at the various social events during the conference. Sponsors/Exhibitors are a focus for the conference, with the general sessions and meals taking place in the same ballroom as the exhibition.

GIS-Pro 2011 will take place at the new JW Marriott Indianapolis which has already garnered customer satisfaction awards since opening in February. Discounted rooms are being offered for only $139 (including internet access), but the offer is only valid until October 7.

Visit the conference website at for complete program and registration details and follow the conference on twitter (#gispro2011).

[Source: URISA press release]

A Multiscale Geographic Object-based Image Analysis to Estimate Lidar-measured Forest Canopy Height using Quickbird Imagery

International Journal of Geographical Information Science International Journal of Geographical Information Science, Volume 25, Issue 6, 2011

Gang Chen, Geoffrey J. Hay, Guillermo Castilla, Benoît St-Onge, and Ryan Powers

“Lidar (light detection and ranging) has demonstrated the ability to provide highly accurate information on forest vertical structure; however, lidar data collection and processing are still expensive. Very high spatial resolution optical remotely sensed data have also shown promising results to delineate various forest biophysical properties. In this study, our main objective is to examine the potential of Quickbird (QB) imagery to accurately estimate forest canopy heights measured from small-footprint lidar data. To achieve this, we have developed multiscale geographic object-based image analysis (GEOBIA) models from QB data for both deciduous and conifer stands. In addition to the spectral information, these models also included (1) image-texture [i.e., an internal-object variability measure and a new dynamic geographic object-based texture (GEOTEX) measure that quantifies forest variability within neighboring objects] and (2) a canopy shadow fraction measure that acts as a proxy of vertical forest structure. A novel object area-weighted error calculation approach was used to evaluate model performance by considering the importance of object size.

(a) A sample area in the study site, and the SCRM-derived segmentation boundaries overlaid on the corresponding area with the mean object size (MOS) of (b) 0.04 ha, (c) 0.36 ha, (d) 1.00 ha, (e) 4.00 ha, and (f) 6.00 ha.

“To determine the best object scale [i.e., mean object size (MOS)] for defining the most accurate canopy height estimates, we introduce a new perspective, which considers height variability both between- and within-objects at all scales. To better evaluate the improvements resulting from our GEOBIA models, we compared their performance with a traditional pixel-based approach. Our results show that (1) the addition of image-texture and shadow fraction variables increases the model performance versus using spectral information only, especially for deciduous trees, where the average increase of R 2 is approximately 23% with a further 1.47 m decrease of Root Mean Squared Error (RMSE) at all scales using the GEOBIA approach; (2) the best object scale for our study site corresponds to an MOS of 4.00 ha; (3) at most scales, GEOBIA models achieve more accurate results than pixel-based models; however, we note that inappropriately selected object scales may result in poorer height accuracies than those derived from the applied pixel-based approach.”

Space-time Confounding Adjusted Determinants of Child HIV/TB Mortality for Large Zero-inflated Data in Rural South Africa

Spatial and Spatio-temporal Epidemiology, Available online 18 July 2011

Eustasius Musenge, Penelope Vounatsou, and Kathleen Kahn

“South Africa has the greatest burden of HIV/TB, with a prevalence of 17% and 2.1 million AIDS orphans. We used data from Agincourt located in rural northeast South Africa, collected longitudinally over the years 2000 and 2005. A total of 187 deaths were observed from 16,844 children aged 1-5 years coming from 8,863 households. In this paper we employ two zero inflated models adjusting for household spatiotemporal random effects using Bayesian inference. Bayesian zero inflated spatiotemporal models were able to detect hidden patterns within the data. Our main finding was that maternal orphans were almost thrice at greater risk of HIV/TB death compared to those with living mothers (AHR=2.93, 95% CI[1.29;6.93]). Risk factor analyses which adjusts for person, place and time enables policy makers to use estimates and maps for interventions. We conclude saying child survival is dependent on the mother’s survival and advocate for policies that promote maternal longevity.”

Call for Papers: GIS for Environmental Modelling

6th International Congress on Environmental Modelling and Software The 6th International Congress on Environmental Modelling and Software (01 – 05 July 2012 in Leipzig, Germany) will have a session on Geographic Information Systems and geoprocessing workflows for environmental modeling (Daniel P. Ames, Robert Argent, Susan Cuddy, Nigel W.T. Quinn, and Raul Zurita-Milla).


In September 2000, the 4th International Conference on Integrating GIS and Environmental Modelling (GIS-EM4) was held in Banff, Canada with more than 250 presentations. In the ensuing 12 years no major “GIS for Environmental Modelling” meeting has been held in spite of:

  • significant advances in both GIS software and hardware computational capabilities
  • advent of a veritable  tidal wave of accessible geospatial data sets
  • the introduction of an entirely new breed of GIS software (characterized by Google Earth and Google Maps) and the accompanying rise of the so-called “neogeographer”
  • the establishment of major geospatial data sharing standards through OGC and related bodies (e.g. WFS, KML) and
  • the introduction of a several highly functional free and open source GIS software tools and libraries (e.g. as sponsored by OSGeo).

This session of iEMSs 2012 recognizes all of these advances as well as the natural role of iEMSs in encouraging, promoting, and facilitating continued advancements in the application of GIS software and tools to environmental Modelling. While any novel and interesting studies in the arena of GIS for environmental modelling will be considered for presentation in this session, we are particularly interested in the development and application of geoprocessing workflows, use of free and open source GIS, web-based GIS applications, tightly coupled GIS-based environmental models, GIS-based environmental decision support systems, geospatial data services, geoprocessing semantics, GIS integration technologies, and related topics.

Paper Submissions

The first step is submitting an abstract (300 words max.) before the 1st of November 2011 In case of approval you will be invited to prepare a six page long full paper, which has to be submitted until 15 February, 2012.

More Information

The call for papers:

The GIS sessions (D6):

ESRI Software R&D Team, circa 1985

Courtesy of Armando Guevara comes this gem:

“ESRI Software R&D Team Circa 1985 –these guys wrote the first operational components of Arc Info – which later evolved into Arc GIS. I personally took this picture and then pasted myself on it.”

ESRI Software R&D Team, circa 1985

  1. Dave Bishop [PIOS and AutoMap]
  2. Mark Oliver [DG to UNIX porting]
  3. Glenn Huibregtse [Prime to UNIX porting]
  4. Peter Aronson [INFO; Database stuff]
  5. Scott Morehouse [Chief Software Engineer]
  6. Tony Lupien [Adddress matching; geocoding]
  7. Bill Moreland [Arcplot; ArcEdit]
  8. Armando Guevara [Geometric and Topologic processors (clean, build, clip, etc.); TIN; GRID]

LiveROMS: A Virtual Environment for Ocean Numerical Simulations

Environmental Modelling & SoftwareEnvironmental Modelling & Software, Available online 21 June 2011

H.H. Sepulveda, O.E. Artal, and C. Torregrosa

“LiveROMS is a bootable DVD that contains an Linux-based computer operating system which has a complete, functioning version of the ROMS ocean circulation model and an Octave version of ROMSTOOLS. It allows students and scientists to experiment with this ocean numerical model, with just a basic knowledge of Linux.”

ROMS Ocean Model.  Photo credit: Pacific Islands Ocean Observing System.

ROMS Ocean Model. Photo credit: Pacific Islands Ocean Observing System.

Exploratory Spatial Analysis of Illegal Oil Discharges Detected off Canada’s Pacific Coast

Lecture Notes in Computer ScienceLecture Notes in Computer Science, 2008, Volume 5072/2008, pp81-95

Norma Serra-Sogas, Patrick O’Hara, Rosaline Canessa, Stefania Bertazzon, and Marina Gavrilova

“In order to identify a model that best predicts spatial patterns it is necessary to first explore the spatial properties of the data that will be included in a predictive model. Exploratory analyses help determine whether or not important statistical assumptions are met, and potentially lead to the definition of spatial patterns that might exist in the data. Here, we present results from exploratory analyses based on detected illegal oil spills by the National Aerial Surveillance Program (NASP) in Canada’s Pacific Region, and marine vessel traffic, the possible source of these oil discharges.

LISA cluster map of surveillance flight counts.

LISA cluster map of surveillance flight counts.

“We identify and describe spatial properties of the oil spills, surveillance flights and marine traffic, to ultimately identify to most suitable predictive model to map areas where these events are more likely to occur.”

Synergy of Very High Resolution Optical and Radar Data for Object-based Olive Grove Mapping

International Journal of Geographical Information Science International Journal of Geographical Information Science, Volume 25, Issue 6, 2011

Jan Peters, Frieke Van Coillie, Toon Westra, and Robert De Wulf

“This study investigates the potential of very high resolution (VHR) optical and radar data for olive grove landscape mapping. VHR data were fed into a four-step processing chain performing an object-based land-use classification. The four steps included (i) image segmentation, (ii) object feature calculation, (iii) object-based classification and (iv) land-use map evaluation. First, the optical (ADS40) and radar (RAMSES SAR and TerraSAR-X) data were applied to the processing chain separately. As supported by two segmentation evaluation measures, the stand purity index (PI) and the potential mapping accuracy (PMA), the optical data thereby led to a significantly better segmentation and a more accurate olive cover map (Kruskal–Wallis test, ). Second, synergy models were developed combining data from the different sensors at different stages of the object-based classification process, namely, (1) during the segmentation step, (2) during the feature calculation step and (3) after the object classification step.

Soft classification (a) and hard classification (b) based on the synergy model at feature level. The soft classification expresses the probability of occurrence of olive grove (Po). The ADS40 false colour composite image of the study site is shown for comparison (c).

“The combined use of features from the different sensors resulted in a considerable improvement in mapping accuracy, with correctly classified objects supported by high probabilities. The assessment of feature importance revealed that optical data were most important for successful object-based olive grove mapping; however, features related to object shape and texture of the radar imagery added to its success. Comparison of the object-based synergy model with a pixel-based synergy model indicated a limited classification improvement. This research showed that the integrated use of VHR optical and radar data is appropriate in an object-based classification framework, leading towards more accurate olive grove landscape mapping.”