Spatio-Temporal Analysis of Droughts in Semi-Arid Regions by Using Meteorological Drought Indices

Atmosphere 2013, 4, 94-112

Alireza Shahabfar and Josef Eitzinger

“Six meteorological drought indices including percent of normal (PN), standardized precipitation index (SPI), China-Z index (CZI), modified CZI (MCZI), Z-Score (Z), the aridity index of E. de Martonne (I) are compared and evaluated for assessing spatio-temporal dynamics of droughts in six climatic regions in Iran.

Spatial distribution of monthly drought indices with the best correlation to standardized precipitation index (SPI) for January, February, March and April.

Spatial distribution of monthly drought indices with the best correlation to standardized precipitation index (SPI) for January, February, March and April.

“Results indicated that by consideration of the advantages and disadvantages of the mentioned drought predictors in Iran, the Z-Score, CZI and MCZI could be used as a good meteorological drought predictor. Depending on the month, the length of drought and climatic conditions of the region, they are an alternative to the SPI that has limitations both because of only a few available long term data series in Iran and its complex structure.”

Mapping Spatial Variations of Health Insurance Coverage in the Coastal Bend, Texas

Journal of MapsJournal of Maps, Volume 8, Issue 4, December 2012, pages 349-353

Yuxia Huang & Pamela Meyer

“A 2010 Health Needs Assessment for 15 counties of the Coastal Bend in the state of Texas indicates limited access to health care services and health insurance coverage is a main potential barrier to health care for some segments of the Coastal Bend population. The purpose of this paper is to obtain geographical sight of the health insurance coverage. The hypothesis is that the health insurance coverage by racial and ethnic groups would vary spatially. Data came from the local hospital systems and included 145,669 patient visits from 1 September 2007 through 31 August 2009. A series of maps were produced showing financial class categories for both Hispanics and Whites adults by combining the cross-tabulations of patient data and estimated population both at the zip code level. The maps show that the health insurance coverage disparities vary spatially within zip codes in the Coastal Bend. Moreover, Hispanic and White adult patients do not follow the same pattern of spatial distribution.”

URISA Invites Comments on its GIS Capability Maturity Model

URISAURISA invites experienced GIS professionals of all kinds – particularly those with management experience – to review and comment on a draft GIS Capability Maturity Model (GCMM).

The GIS Capability Maturity Model is intended primarily to define the components of an effective GIS operation, as well as to identify the characteristics of a well-managed and mature GIS. The model was originally developed in 2009 and adopted as a URISA initiative in 2010. In 2011 and 2012 it was used to inform development of the Geospatial Management Competency Model by URISA. URISA’s GIS Management Institute conducted an internal review/revision process from October 2012 through March 2013. This process resulted in the version of the model now offered for public review.

Links to the draft GCMM and an online questionnaire for reviewers are available at The questionnaire will remain open through May 31, 2013. After the public review period, URISA’s GIS Management Institute will review all comments received, make appropriate changes, and publish a fully authorized peer-reviewed version of the model.

[Source: URISA press release]

URISA’s GIS in Public Health Conference Program Announced

URISA is pleased to announce its Fourth GIS in Public Health Conference. The conference will take place in Miami, Florida, June 17-20, 2013 and is chaired by long-time program committee member, Jason K. Blackburn, PhD, Emerging Pathogens Institute & Department of Geography at the University of Florida. This biennial conference has been previously presented in New Orleans (2007), Providence (2009) and Atlanta (2011) and was established to provide an open and participatory forum for advancing the effective use of spatial information and geographic information system technologies across the domains of public health, healthcare and community health preparedness.The educational program was developed through a peer review of submissions received through a Call for Presentations. The broad conference theme for the 2013 event is: Geospatial tools for understanding health issues related to the environment, human population, and animal populations and the intersections of the three.

Preconference courses will be taught on Monday, June 17:

  • An Overview of Open Source GIS Software
  • Detecting Clusters of Adverse Health Outcomes using SaTScan™
  • Geospatial Data Collection for Micro-Environments and Multiple Time Periods: The Use of Spatial Video
Mei-Po Kwan

Mei-Po Kwan

The conference is honored to welcome Mei-Po Kwan (Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign) as the opening keynote speaker. She will address GIS Methods for Analyzing GPS Data: Applications in Neighborhood and Health Research.

Dozens of speakers from across the globe will discuss such topics as:

  • Preparing for the Future: Are Caribbean Countries Positioned to Manage the Increase in Non-communicable Illnesses?
    Patricia Boda, PhD, Associate Professor, Middle Tennessee State University, Murfreesboro, TN
  • GIS for Community Air Quality: A Spatial Model of Diesel Exhaust
    Jill Schulte, Research Assistant, University of Washington, Seattle, WA
    Julie Fox, PhD, Senior Fellow, University of Washington, Seattle, WA
  • HealthGIS for Reaching the Unreached Population
    Paban Kumar Ghimire, Deputy Director, Department of Health Services, Nepal
  • Macro Mapping of Dengue Virus Vector
    Lynette Akong, Bsc, Msc, Ministry of Planning and Sustainable Development, Trinidad and Tobago
  • Spatial Modeling of Malaria Parasitemia in Young Children in Tanzania
    Rebecca Stallings, MHS Biostatistics Graduate Student, Missouri State University, Springfield, MO
  • Comparing Primary Care Service Areas to Estimated Drive Times
    Sean Finnegan, MS, Research and GIS Data Manager, American Academy of Family Physicians, Washington, DC
  • Remote Sensing and GIS Techniques for Monitoring Industrial Wastes for Amman City
    Raina Qutieshat, PhD, Lecturer, Balqa Applied University, Jordan
  • Using Geospatial Mapping to Address the Burden of Diabetes in Durham County, NC
    Benjamin Strauss, MS, GIS Analyst, Children’s Environmental Health Initiative, Ann Arbor, MI
    Nicole Sandberg, MURP, GIS Analyst, Children’s Environmental Health Initiative, Ann Arbor, MI
  • Chronic Obstructive Pulmonary Disease (COPD) in India: GIS is The Tool for Epidemiological Studies
    Arun Sharma, MD, Professor, University College of Medical Sciences, India
    Marilyn O’Hara, Clinical Associate Professor, University of Illinois, Urbana, IL
  • Small-Area Geographies of Mental Health in England
    Nick Bearman,  Associate Research Fellow in GIS, European Centre for Environment and Human Health, University of Exeter Medical School, United Kingdom

The poster session is an important feature of the conference, with nearly 30 participants demonstrating their research on such important topics as:

  • Does Place Make a Difference for Texas’ Adolescent and Young Adult Cancer Survival
    Deborah Vollmer Dahlke, MPAff, Director, Texas Life Science Foundation, Austin, TX
  • Spatial Epidemiology of Highly Pathogenic of Avian Influenza A (H5N1) in Central Java & Yogyakarta Provinces, Indonesia
    Triwibowo Ambar Garjito, Health Epidemiologist and Molecular Biologist, Vector and Reservoir Diseases Research Center, Indonesia
  • Bayesian Spatial Analysis of Teenage Pregnancy Rates in a Brazilian State
    Daiane Leite da Roza,  Universidade de São Paulo, BrazilKazakhstan Health Study : The
  • Study of the Determinants of Metabolic Syndrome in Elderly Population
    Leila Utepova, MPH, Researcher, Center for Life Sciences, Nazarbayev University, Astana, Kazakhstan
    Alibek Kossumov, PhD, Senior Researcher, Center for Life Sciences, Nazarbayev University, Astana, Kazakhstan

Dr. Andrew Curtis, Director of the GIS Health and Hazards Lab at Kent State University will provide the closing keynote address on Thursday, June 20.

Early registration discounts are available until May 15 and sponsorship opportunities are plentiful.

For specific conference details and participation options, visit

[Source: URISA press release]

Understanding Forest-derived Biomass Supply with GIS Modelling

jssJournal of Spatial Science, Volume 57, Issue 2, December 2012, pages 213-232

B.K. Hock, L. Blomqvist, P. Hall, M. Jack, B. Möller, and S.J. Wakelin

“In New Zealand, residues from the harvest of plantation forests have been identified as the largest potential source of biomass for energy production to replace fossil fuels. Barriers to the increased use of biomass include uncertainty of supply as local plantations may not have an even age distribution, and the cost of delivery as forests are frequently remote from energy users. A GIS-based model was developed to predict supply curves of forest biomass material for a site or group of sites, both now and in the future. The GIS biomass supply model was used to assist the New Zealand Energy Efficiency and Conservation Authority’s development of a national target for biomass use for industrial heat production, to determine potential forest residue volumes for industrial heat and their delivery costs for 19 processing plants of the dairy company Fonterra, and towards investigating options for electricity generation from local resources for small, remote settlements. The results of these applications are presented and potential further developments to the model are outlined.”

Fusing Remote Sensing with Sparse Demographic Data for Synthetic Population Generation: An Algorithm and Application to Rural Afghanistan

International Journal of Geographical Information ScienceInternational Journal of Geographical Information Science, published online 19 November 2012

Seyed M. Mussavi Rizi, Maciej M. Łatek, and Armando Geller

“We develop a new algorithm for population synthesis that fuses remote-sensing data with partial and sparse demographic surveys. The algorithm addresses non-binding constraints and complex sampling designs by translating population synthesis into a computationally efficient procedure for constrained network growth. As a case, we synthesize the rural population of Afghanistan, validate the algorithm with in-sample and out-of-sample tests, examine the variability of algorithm outputs over k-nearest neighbor manifolds, and show the responsiveness of our algorithm to additional data as a constraint on marginal population counts.”