Thesis (M. G. I. S.)--University of Hong Kong, 2005. / Title proper from title frame. Also available in printed format.

published_or_final_version / abstract / Geography / Master / Master of Geographic Information System

Many local planning departments have acquired and put into use advanced automated geocoding and Geographic Information Systems (GIS) to store, process, map and analyze geographic data. GIS technological advancements in hardware, software, and geographic databases - specifically, in geocoding methods to reference street address data to geographic locations - enable data to be integrated, mapped, and analyzed more efficiently and effectively. Also, technological advancements depend on organizational and institutional environments. The relationships between technological advancements and technical (data mapping and analysis), organizational, and institutional environments are not clear. The purpose of this study is to explain these relationships to help planning and development directors make better decisions in acquiring and using advanced geocoding and GIS technology. The findings are based on a mail survey of planning and development departments in cities with populations of 50,000 or more in the United States. The study found that planning departments with advanced geocoding and GIS technology are capable of conducting advanced geocoding applications. Data can be tabulated, aggregated, linked, and modeled for mapping and planning. Geocoding to aggregate data to small geographic areas helps by providing required and up-to-date information to solve urban problems. However, the study did not find that advanced geocoding systems enhance data quality as measured by spatial resolution and volume. Further studies are needed to explore this issue. The adoption and implementation of advanced geocoding and GIS technology are influenced by organizational and institutional environments. Large cities have more experience with hardware, software programs, computer professionals, and training programs, but they are dependent on centralized systems from an earlier computer era. Consequently, more recent entrants to using computers for geographic data processing are emerging rapidly. As technology is becoming more advanced, hardware and software costs are declining. Some of the organizational and institutional issues are eliminated while new ones are emerging. As a result, small area cities are adopting advanced geocoding and GIS technology more rapidly than they were previously, and sometimes they surpass large cities. This study improves understanding of automated street address geocoding methods and how these methods are related to advancements in GIS technology. The study also examines how technical, organizational, and institutional environments are interrelated in adopting and using geocoding and GIS technology. The challenge in the 1990s will not be how to fund and acquire a GIS, but how to integrate all of the pieces in order to make the technology work properly.

Indiana University-Purdue University Indianapolis (IUPUI) / Identifying spatial and temporal patterns of disease occurrence by mapping the residential locations of affected people can provide information that informs response by public health practitioners and improves understanding in epidemiological research. A common method of locating patients at the individual level is geocoding residential addresses stored in electronic medical records (EMRs) using address matching procedures in a geographic information system (GIS). While the process of geocoding is becoming more common in public health studies, few researchers take the time to examine the effects of using different address databases on match rate and positional accuracy of the geocoded results. This research examined and compared accuracy and match rate resulting from four commonly-used geocoding databases applied to sample of 59,341 subjects residing in and around Marion County/ Indianapolis, IN. The results are intended to inform researchers on the benefits and downsides to their selection of a database to geocode patient addresses in EMRs.