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Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset
It is well known that the conventional, automated geocoding method based on self-reported residential addresses has many issues. We developed a smartphone-assisted aerial image-based method, which uses the Google Maps application programming interface as a spatial data collection tool during the bir...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5800510/ https://www.ncbi.nlm.nih.gov/pubmed/27903063 http://dx.doi.org/10.4081/gh.2016.482 |
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author | Xu, Xiaohui Hu, Hui Ha, Sandie Han, Daikwon |
author_facet | Xu, Xiaohui Hu, Hui Ha, Sandie Han, Daikwon |
author_sort | Xu, Xiaohui |
collection | PubMed |
description | It is well known that the conventional, automated geocoding method based on self-reported residential addresses has many issues. We developed a smartphone-assisted aerial image-based method, which uses the Google Maps application programming interface as a spatial data collection tool during the birth registration process. In this pilot study, we have tested whether the smartphone-assisted method provides more accurate geographic information than the automated geocoding method in the scenario when both methods can get the address geocodes. We randomly selected 100 well-geocoded addresses among women who gave birth in Alachua county, Florida in 2012. We compared geocodes generated from three geocoding methods: i) the smartphone-assisted aerial image-based method; ii) the conventional, automated geocoding method; and iii) the global positioning system (GPS). We used the GPS data as the reference method. The automated geocoding method yielded positional errors larger than 100 m among 29.3% of addresses, while all addresses geocoded by the smartphone-assisted method had errors less than 100 m. The positional errors of the automated geocoding method were greater for apartment/condominiums compared with other dwellings and also for rural addresses compared with urban ones. We conclude that the smartphone-assisted method is a promising method for perspective spatial data collection by improving positional accuracy. |
format | Online Article Text |
id | pubmed-5800510 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
record_format | MEDLINE/PubMed |
spelling | pubmed-58005102018-02-06 Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset Xu, Xiaohui Hu, Hui Ha, Sandie Han, Daikwon Geospat Health Article It is well known that the conventional, automated geocoding method based on self-reported residential addresses has many issues. We developed a smartphone-assisted aerial image-based method, which uses the Google Maps application programming interface as a spatial data collection tool during the birth registration process. In this pilot study, we have tested whether the smartphone-assisted method provides more accurate geographic information than the automated geocoding method in the scenario when both methods can get the address geocodes. We randomly selected 100 well-geocoded addresses among women who gave birth in Alachua county, Florida in 2012. We compared geocodes generated from three geocoding methods: i) the smartphone-assisted aerial image-based method; ii) the conventional, automated geocoding method; and iii) the global positioning system (GPS). We used the GPS data as the reference method. The automated geocoding method yielded positional errors larger than 100 m among 29.3% of addresses, while all addresses geocoded by the smartphone-assisted method had errors less than 100 m. The positional errors of the automated geocoding method were greater for apartment/condominiums compared with other dwellings and also for rural addresses compared with urban ones. We conclude that the smartphone-assisted method is a promising method for perspective spatial data collection by improving positional accuracy. 2016-11-23 /pmc/articles/PMC5800510/ /pubmed/27903063 http://dx.doi.org/10.4081/gh.2016.482 Text en http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License (CC BY-NC 4.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Article Xu, Xiaohui Hu, Hui Ha, Sandie Han, Daikwon Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset |
title | Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset |
title_full | Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset |
title_fullStr | Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset |
title_full_unstemmed | Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset |
title_short | Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset |
title_sort | smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5800510/ https://www.ncbi.nlm.nih.gov/pubmed/27903063 http://dx.doi.org/10.4081/gh.2016.482 |
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