Abstract: The 3G iPhone was the first consumer device to provide a seamless integration of three positioning technologies: Assisted GPS (A-GPS), WiFi positioning and cellular network positioning. This study presents an evaluation of the accuracy of locations obtained using these three positioning modes on the 3G iPhone. A-GPS locations were validated using surveyed benchmarks and compared to a traditional low-cost GPS receiver running simultaneously. WiFi and cellular positions for indoor locations were validated using high resolution orthophotography. Results indicate that A-GPS locations obtained using the 3G iPhone are much less accurate than those from regular autonomous GPS units (average median error of 8 m for ten 20-minute field tests) but appear sufficient for most Location Based Services (LBS). WiFi locations using the 3G iPhone are much less accurate (median error of 74 m for 58 observations) and fail to meet the published accuracy specifications. Positional errors in WiFi also reveal erratic spatial patterns resulting from the design of the calibration effort underlying the WiFi positioning system. Cellular positioning using the 3G iPhone is the least accurate positioning method (median error of 600 m for 64 observations), consistent with previous studies. Pros 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.
By Sven Fuhrmann, Oleg Komogortsev, Dan Tamir
Abstract: It is often assumed that three-dimensional topographic maps provide more effective route planning, navigation, orientation, and way-finding results than traditional two-dimensional representations. The research reported here investigates whether three-dimensional spatial mappings provide better support for route planning than two-dimensional representations. In a set of experiments performed as part of this research, human subjects were randomly shown either a two- or three-dimensional hologram of San Francisco and were asked to plan a bicycling route between an origin and a destination point. In a second task, participants used these holograms to identify the highest elevation point in the displayed area. The eye-movements of the participants, throughout the process of looking at the geospatial holograms and executing the tasks, were recorded. The eye-tracking metrics analysis indicates with a high statistical level of confidence that three-dimensional holographic maps enable more efficient route planning. In addition, the research group is developing a new algorithm to analyze the differences between participant-selected routes and a set of “good routes.” The algorithm employs techniques used to represent the boundary of objects and methods for assessing the difference between objects in modern digital image recognition, image registration, and image alignment applications. The overall goal is to create a theoretical framework for investigating and quantifying route planning effectiveness.
Abstract: Text documents frequently contain descriptions of different kinds of movements by individual persons, groups, animals, vehicles, or other moving objects. Comprehending and modeling the semantics of movement is an area of interest for geographic information science. In this article, we show how text documents that contain movement verbs can be analyzed for deriving representations of movement or dynamic paths. A conceptual framework is presented that provides the foundations necessary for deriving dynamic paths automatically from natural language descriptions and representing these dynamic paths in an information system, such as a geographic information system. In this research, a linguistic analysis of dynamic paths is presented and linked to a spatiotemporal representation of paths. We show how movement descriptions in text can be mapped to a set of elemental components including source, destination, route, direction, distance, start time, end time, and duration. Together, this set of path components captures the spatiotemporal characteristics of the path of a moving object as described using natural language. A systematic examination of these components builds a foundation for understanding more complex scenarios involving discourse (composed of consecutive sentences). Additional aspects reflecting important semantics about the movement characteristics of objects and discussed here are the shape of the path and granularity of modeling.
“Whereis.com approached Melbourne University’s geomatics department – “the science and technologies of three-dimensional measurement, mapping and visualisation” – about a year ago, asking it to test its theory that the inclusion of landmarks would improve map directions and to help determine the qualities that make a landmark worth using.”
William B. Monahan, Senior GIS Scientist with Audubon California, has written an essay on (published at Grist.org) 0n how data collected by volunteer scientists is helping to build a case for climate action.
“They traipse through forest, grass and wetland, through mud, rain and even snow. They carry binoculars and take careful notes of everything they see.
“These are the folks—thousands of dedicated bird watchers—that for more than 100 years have been taking part in the Audubon Christmas Bird Count, documenting fluctuations in bird populations the old-fashioned way: counting birds one by one, year after year.
“Old fashioned as it is, this data has proven invaluable for researchers through several generations. Now, we at Audubon California have found a way to use the work of these volunteers to shed new light on climate change, one of the most challenging issues for bird conservation today.”
…from the International Journal of Health Geographics 2009, 8:36…
“Spatio-temporal cluster analysis of county-based human West Nile virus incidence in the continental United States”
By Ramanathan Sugumaran, Scott R Larson, and John P DeGroote
“Background: West Nile virus (WNV) is a vector-borne illness that can severely affect human health. After introduction on the East Coast in 1999, the virus quickly spread and became established across the continental United States. However, there have been significant variations in levels of human WNV incidence spatially and temporally. In order to quantify these variations, we used Kulldorff’s spatial scan statistic and Anselin’s Local Moran’s I statistic to uncover spatial clustering of human WNV incidence at the county level in the continental United States from 2002-2008. These two methods were applied with varying analysis thresholds in order to evaluate sensitivity of clusters identified.
“Results: The spatial scan and Local Moran’s I statistics revealed several consistent, important clusters or hot-spots with significant year-to-year variation. In 2002, before the pathogen had spread throughout the country, there were significant regional clusters in the upper Midwest and in Louisiana and Mississippi. The largest and most consistent area of clustering throughout the study period was in the Northern Great Plains region including large portions of Nebraska, South Dakota, and North Dakota, and significant sections of Colorado, Wyoming, and Montana. In 2006, a very strong cluster centered in southwest Idaho was prominent. Both the spatial scan statistic and the Local Moran’s I statistic were sensitive to the choice of input parameters.
“Conclusions: Significant spatial clustering of human WNV incidence has been demonstrated in the continental United States from 2002-2008. The two techniques were not always consistent in the location and size of clusters identified. Although there was significant inter-annual variation, consistent areas of clustering, with the most persistent and evident being in the Northern Great Plains, were demonstrated. Given the wide variety of mosquito species responsible and the environmental conditions they require, further spatio-temporal clustering analyses on a regional level is warranted.”
…from the International Journal of Health Geographics 2009, 8:36…
“Exploring Spatial Patterns and Hotspots of Diarrhea in Chiang Mai, Thailand”
By Nakarin Chaikaew, Nitin Tripathi, and Marc Souris
“Diarrhea is a major public health problem in Thailand. The Ministry of Public Health, Thailand, has been trying to monitor and control this disease for many years.
“The methodology and the results from this study could be useful for public health officers to develop a system to monitor and prevent diarrhea outbreaks.
“Methods: The objective of this study was to analyse the epidemic outbreak patterns of diarrhea in Chiang Mai province, Northern Thailand, in terms of their geographical distributions and hotspot identification. The data of patients with diarrhea at village level and the 2001-2006 population censuses were collected to achieve the objective.
“Spatial analysis, using geographic information systems (GIS) and other methods, was used to uncover the hidden phenomena from the data. In the data analysis section, spatial statistics such as quadrant analysis (QA), nearest neighbour analysis (NNA), and spatial autocorrelation analysis (SAA), were used to identify the spatial patterns of diarrhea inChiang Mai province.
“In addition, local indicators of spatial association (LISA) and kernel density (KD) estimation were used to detect diarrhea hotspots using data at village level.
“Results: The hotspot maps produced by the LISA and KD techniques showed spatial trend patterns of diarrhea diffusion. Villages in the middle and northern regions revealed higher incidences.
“Also, the spatial patterns of diarrhea during the years 2001 and 2006 were found to represent spatially clustered patterns, both at global and local scales.
“Conclusion: Spatial analysis methods in GIS revealed the spatial patterns and hotspots of diarrhea in Chiang Mai province from the year 2001 to 2006. To implement specific and geographically appropriate public health risk-reduction programs, the use of such spatial analysis tools may become an integral component in the epidemiologic description, analysis, and risk assessment of diarrhea.”