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...
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doaj-70f552382a7148be823b471423b01ad62020-11-25T03:32:33ZengPAGEPress PublicationsGeospatial Health1827-19871970-70962016-11-0111310.4081/gh.2016.482399Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records datasetXiaohui Xu0Hui Hu1Sandie Ha2Daikwon Han3Department of Epidemiology and Biostatistics, Texas A&M University, College Station, TXDepartment of Epidemiology, University of Florida, Gainesville, FLDepartment of Epidemiology, University of Florida, Gainesville, FLDepartment of Epidemiology and Biostatistics, Texas A&M University, College Station, TXIt 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 smartphoneassisted 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.http://www.geospatialhealth.net/index.php/gh/article/view/482Positional accuracyGeocodeVital statisticsBiasEnvironmental epidemiology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaohui Xu Hui Hu Sandie Ha Daikwon Han |
spellingShingle |
Xiaohui Xu Hui Hu Sandie Ha Daikwon Han Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset Geospatial Health Positional accuracy Geocode Vital statistics Bias Environmental epidemiology |
author_facet |
Xiaohui Xu Hui Hu Sandie Ha Daikwon Han |
author_sort |
Xiaohui Xu |
title |
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_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_sort |
smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset |
publisher |
PAGEPress Publications |
series |
Geospatial Health |
issn |
1827-1987 1970-7096 |
publishDate |
2016-11-01 |
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 smartphoneassisted 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. |
topic |
Positional accuracy Geocode Vital statistics Bias Environmental epidemiology |
url |
http://www.geospatialhealth.net/index.php/gh/article/view/482 |
work_keys_str_mv |
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