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  Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset

  Xiaohui Xu, Hui Hu, Sandie Ha, Daikwon Han

  23-11-2016

  https://doi.org/10.4081/gh.2016.482

  2936

  PDF: 1050

  HTML: 818

• Evaluation of the positional difference between two common geocoding methods

  Dustin T. Duncan, Marcia C. Castro, Jeffrey C. Blossom, Gary G. Bennett, Steven L. Gortmaker

  265-273

  01-05-2011

  https://doi.org/10.4081/gh.2011.179

  2758

  PDF: 1919
• 

  An analysis of the process and results of manual geocode correction

  Yolanda J. McDonald, Michael Schwind, Daniel W. Goldberg, Amanda Lampley, Cosette M. Wheeler

  11-05-2017

  https://doi.org/10.4081/gh.2017.526

  2494

  PDF: 1045

  HTML: 986
• 

  Ecological characterization of a cutaneous leishmaniasis outbreak through remotely sensed land cover changes

  Verónica Andreo, Juan Rosa, Karina Ramos, O. Daniel Salomón

  06-05-2022

  https://doi.org/10.4081/gh.2022.1033

  1878

  PDF: 978

  Appendix: 179

  HTML: 41
• 

  Comparison of GPS imputation methods in environmental health research

  Sungsoon Hwang, Kashica Webber-Ritchey, Elizabeth Moxley

  29-08-2022

  https://doi.org/10.4081/gh.2022.1081

  2381

  PDF: 1117

  HTML: 40
• 

  Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach

  Alexander Domnich, Lucia Arata, Daniela Amicizia, Alessio Signori, Roberto Gasparini, Donatella Panatto

  16-11-2016

  https://doi.org/10.4081/gh.2016.457

  3496

  PDF: 1858

  HTML: 1332

• Response to Geocoding-protected health information using online services may compromise patient privacy - Comments on Evaluation of the positional difference between two common geocoding methods by Duncan et al.

  Dustin T. Duncan, Marcia C. Castro, Jeffrey C. Blossom

  158-159

  01-05-2012

  https://doi.org/10.4081/gh.2012.133

  1100

  PDF: 914

• Geocoding-protected health information using online services may compromise patient privacy - Comments on Evaluation of the positional difference between two common geocoding methods by Duncan et al.

  Sunny Mak

  157

  01-05-2012

  https://doi.org/10.4081/gh.2012.132

  1374

  PDF: 1038
• 

  Geocoding precision of birth records from 2008 to 2017 in Kentucky, USA

  Courtney J. Walker, Steven R. Browning, Jeffrey E. Levy, W. Jay Christian

  06-05-2022

  https://doi.org/10.4081/gh.2022.1020

  1543

  PDF: 785

  HTML: 17
• 

  Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany

  Renke Lühken, Jörn Martin Gethmann, Petra Kranz, Pia Steffenhagen, Christoph Staubach, Franz J. Conraths, Ellen Kiel

  31-05-2016

  https://doi.org/10.4081/gh.2016.405

  3423

  PDF: 1127

  HTML: 1464
• 

  Understanding needs and barriers to using geospatial tools for public health policymaking in China

  Dohyeong Kim, Yingyuan Zhang, Chang Kil Lee

  07-05-2018

  https://doi.org/10.4081/gh.2018.594

  2029

  PDF: 992

  HTML: 355
• 

  A topological multilayer model of the human body

  Antonio Barbeito, Marco Painho, Pedro Cabral, João O'Neill

  04-11-2015

  https://doi.org/10.4081/gh.2015.375

  3267

  PDF: 1285

  HTML: 1580
• 

  Integration of accelerometers, global positioning systems (GPS) and geographical information systems (GIS) for measuring physical activity

  Lucian Bezuidenhout, Warren Miller, Conran Joseph, David Moulaee Conradsson

  21-10-2025

  https://doi.org/10.4081/gh.2025.1382

  872

  PDF: 448

  HTML: 33
• 

  Perceived spatial stigma, body mass index and blood pressure: a global positioning system study among low-income housing residents in New York City

  Dustin T. Duncan, Ryan R. Ruff, Basile Chaix, Seann D. Regan, James H. Williams, Joseph Ravenell, Marie A. Bragg, Gbenga Ogedegbe, Brian Elbel

  31-05-2016

  https://doi.org/10.4081/gh.2016.399

  4244

  PDF: 2009

  HTML: 1504