TL;DR: Diverse single-variable and composite area-based socioeconomic measures at the census tract, block group, and zip code level for Massachusetts and Rhode Island indicated that block group and tract socioeconomic measures performed comparably within and across both states, but zip code measures for several outcomes detected no gradients or gradients contrary to those observed with tract and block group measures.
Abstract: Despite the promise of geocoding and use of area-based socioeconomic measures to overcome the paucity of socioeconomic data in US public health surveillance systems, no consensus exists as to which measures should be used or at which level of geography. The authors generated diverse single-variable and composite area-based socioeconomic measures at the census tract, block group, and zip code level for Massachusetts (1990 population: 6,016,425) and Rhode Island (1990 population: 1,003,464) to investigate their associations with mortality rates (1989-1991: 156,366 resident deaths in Massachusetts and 27,291 in Rhode Island) and incidence of primary invasive cancer (1988-1992: 140,610 resident cases in Massachusetts; 1989-1992: 19,808 resident cases in Rhode Island). Analyses of all-cause and cause-specific mortality rates and all-cause and site-specific cancer incidence rates indicated that: 1) block group and tract socioeconomic measures performed comparably within and across both states, but zip code measures for several outcomes detected no gradients or gradients contrary to those observed with tract and block group measures; 2) similar gradients were detected with categories generated by quintiles and by a priori categorical cutpoints; and 3) measures including data on economic poverty were most robust and detected gradients that were unobserved using measures of only education and wealth.
TL;DR: This paper presents a meta-modelling architecture suitable for GIS models and Modeling of vector data models, and some examples show how this architecture can be modified for distributed systems.
Abstract: 1 Introduction2 Coordinate Systems3 Georelational Vector Data Model4 Object-Based Vector Data Model5 Raster Data Model6 Data Input7 Geometric Transformation8 Spatial Data Editing9 Attribute Data Input and Management10 Data Display and Cartography11 Data Exploration12 Vector Data Analysis13 Raster Data Analysis14 Terrain Mapping and Analysis15 Viewsheds and Watersheds16 Spatial Interpolation17 Geocoding and Dynamic Segmentation18 Path Analysis and Network Applications19 GIS Models and Modeling
TL;DR: In this article, a task description is stored in a database accessible by a mobile computer system and the database is indexed based on the positioning information when the information indicates that the mobile computer is in a geographic location that facilitates completion of a task associated with the task description.
Abstract: A task description is stored in a database accessible by a mobile computer system The mobile computer system receives positioning information corresponding to its geographic location and indexes the database based on the positioning information when the information indicates that the mobile computer system is in a geographic location that facilitates completion of a task associated with the task description The database may be resident in the mobile computer system or accessible in other ways, for example, via the Internet The task description preferably includes a geocode which corresponds to the geographic location at which completion of the task may be facilitated The task description may also include textual, voice or other message which can be displayed and/or played back to a user The positioning information may be obtained from a GPS satellite, a GLONASS satellite or a pseudolite The mobile computer system may be a portable unit, such as a PDA, or integrated within a vehicle
TL;DR: In this article, the authors introduce Geographic Information Systems (GIS), an introduction to Geographic Information System (GeIS) and Geocarto International: Vol. 6, No. 1, pp. 46-46.
Abstract: (1991). Geographic information systems: An introduction. Geocarto International: Vol. 6, No. 1, pp. 46-46.
TL;DR: In this article, a method and an apparatus operates to associate a geographic location associated with a network address, where the retrieved information is processed to identify a plurality of geographic locations potentially associated with the network address.
Abstract: A method and an apparatus operates to associate a geographic location associated with a network address. At least one data collection operation is performed to obtain information pertaining to a network address. The retrieved information is processed to identify a plurality of geographic locations potentially associated with the network address, and to attach a confidence factor to each of the plurality of geographic locations. An estimated geographic location is selected from the plurality of geographic locations as being a best estimate of a true geographic location of the network address, where the selection of the estimated geographic location is based upon a degree of confidence-factor weighted agreement within the plurality of geographic locations.