Geographic information. Quality principles

2003 ◽  
Keyword(s):  
Information Quality ◽  
Geographic Information ◽  
Quality Principles

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

2016 ◽  
Vol 11 (3) ◽  
Author(s):  
Xiaohui Xu ◽  
Hui Hu ◽  
Sandie Ha ◽  
Daikwon Han
Keyword(s):  
Pilot Study ◽  
Data Collection ◽  
Spatial Data ◽  
Information Quality ◽  
Reference Method ◽  
Application Programming Interface ◽  
Geographic Information ◽  
Aerial Image ◽  
Positional Accuracy ◽  
Birth Records

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.

scholarly journals A review of volunteered geographic information quality assessment methods

2016 ◽  
Vol 31 (1) ◽  
pp. 139-167 ◽  
Author(s):  
Hansi Senaratne ◽  
Amin Mobasheri ◽  
Ahmed Loai Ali ◽  
Cristina Capineri ◽  
Mordechai (Muki) Haklay
Keyword(s):  
Quality Assessment ◽  
Information Quality ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Assessment Methods
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