scispace - formally typeset
P

Paul A. Zandbergen

Researcher at University of New Mexico

Publications -  49
Citations -  4243

Paul A. Zandbergen is an academic researcher from University of New Mexico. The author has contributed to research in topics: Geocoding & Spatial analysis. The author has an hindex of 30, co-authored 49 publications receiving 3883 citations. Previous affiliations of Paul A. Zandbergen include Vancouver Island University & University of British Columbia.

Papers
More filters
Journal ArticleDOI

Ecologically Sustainable Organizations: An Institutional Approach

TL;DR: In this article, institutional theory is used to understand how consensus is built around the meaning of sustainability, and how concepts or practices associated with sustainability are developed and diffused among organizations.
Journal ArticleDOI

Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning

TL;DR: Props and cons of the three positioning technologies are presented in terms of coverage, accuracy and reliability, followed by a discussion of the implications for LBS using the 3G iPhone and similar mobile devices.
Journal ArticleDOI

Positional Accuracy of Assisted GPS Data from High-Sensitivity GPS-enabled Mobile Phones

TL;DR: The current study has confirmed the reliability of A-GPS on mobiles phones as a source of location information for a range of different LBS applications with relatively consistent availability of valid GPS position fixes under varying conditions.
Journal ArticleDOI

A comparison of address point, parcel and street geocoding techniques

TL;DR: Variability in geocoding match rates between address databases and between geographic areas is substantial, reinforcing the need to strengthen the development of standards for address reference data and improved address data entry validation procedures.
Journal ArticleDOI

Kernel density estimation and hotspot mapping: examining the influence of interpolation method, grid cell size, and bandwidth on crime forecasting

TL;DR: Examination of the effects of user-defined parameters settings on the predictive accuracy of crime hotspot maps produced from kernel density estimation (KDE) shows that interpolation method has a considerable effect on predictive accuracy, grid cell size has little to no effect, and bandwidth as some effect.