Showing papers by "David Wong published in 2004"
01 Jan 2004
TL;DR: The modifiable areal unit problem (MAUP) as discussed by the authors ) is a problem where the boundaries of many geographical units are often demarcated artificially, and thus can be changed.
Abstract: Even though Gehlke and Biehl (1934) discovered certain aspects of the modifiable areal unit problem (MAUP), the term MAUP was not coined formally until Openshaw and Taylor (1979) evaluated systematically the variability of correlation values when different boundaries systems were used in the analysis. The problem is called “the modifiable areal unit” because the boundaries of many geographical units are often demarcated artificially, and thus can be changed. For example, administrative boundaries, political districts, and census enumeration units are all subject to be redrawn. When data are gathered according to different boundary definitions, different data sets are generated. Analyzing these data sets will likely provide inconsistent results. This is the essence of the MAUP.
670 citations
TL;DR: An effort using EPA's AIRS monitoring data to estimate ozone and PM10 levels at census block groups to make the project more manageable and apply four different interpolation methods to the monitoringData to derive air concentration levels.
Abstract: We recognized that many health outcomes are associated with air pollution, but in this project launched by the US EPA, the intent was to assess the role of exposure to ambient air pollutants as risk factors only for respiratory effects in children. The NHANES-III database is a valuable resource for assessing children's respiratory health and certain risk factors, but lacks monitoring data to estimate subjects' exposures to ambient air pollutants. Since the 1970s, EPA has regularly monitored levels of several ambient air pollutants across the country and these data may be used to estimate NHANES subject's exposure to ambient air pollutants. The first stage of the project eventually evolved into assessing different estimation methods before adopting the estimates to evaluate respiratory health. Specifically, this paper describes an effort using EPA's AIRS monitoring data to estimate ozone and PM10 levels at census block groups. We limited those block groups to counties visited by NHANES-III to make the project more manageable and apply four different interpolation methods to the monitoring data to derive air concentration levels. Then we examine method-specific differences in concentration levels and determine conditions under which different methods produce significantly different concentration values. We find that different interpolation methods do not produce dramatically different estimations in most parts of the US where monitor density was relatively low. However, in areas where monitor density was relatively high (i.e., California), we find substantial differences in exposure estimates across the interpolation methods. Our results offer some insights into terms of using the EPA monitoring data for the chosen spatial interpolation methods.
315 citations
Patent•
17 Nov 2004
TL;DR: Disclosed is a geographic information system which comprises a multithreading client and a multathreading server cluster that includes at least one user interface, at least two client coordinator, map data, and at least three server-side spatial managers.
Abstract: Disclosed is a geographic information system which comprises a multithreading client and a multithreading server cluster. The multithreading client includes at least one user interface, at least one client coordinator, map data, at least one map manager, at least one client-side spatial analyzer, at least one cache manager, at least one data requester, and at least one information communicator. The multithreading server cluster includes: at least one servlet, at least one image accessor, at least one map configuration mechanism; at least one data storage access mechanism, at least one data source manager, and at least one server-side spatial manager.
288 citations
TL;DR: In this article, the authors used the 1990 Census data of 30 selected U.S. metropolitan areas and found that these spatial measures, similar to the aspatial measure, report higher levels of segregation when smaller areal units are used in the analysis.
Abstract: Measuring the level of segregation often encounters two methodological issues: measures are sensitive to changes in the geographical scale of the data and the effectiveness of the measure in reflecting spatial segregation. Several spatial measures have been suggested to measure spatial segregation, but whether they are more or less sensitive to changes in spatial scale has not been investigated, while some spatial measures are relatively scale-insensitive. Using the 1990 Census data of 30 selected U.S. metropolitan areas, this paper demonstrates that these spatial measures, similar to the aspatial measure, report higher levels of segregation when smaller areal units are used in the analysis. Some spatial measures are even more sensitive to scale changes than aspatial measures. Certain patterns of the scale sensitivity were identified, but no general rules can be formulated. A preliminary explanation of the scale effect on spatial segregation measures is offered.
123 citations
TL;DR: In this article, a collection of thirteen papers with a very strong British representation is presented, and the general theme of this book is quite similar to Quattrochi and Goodchild (1997).
Abstract: This book is a collection of thirteen papers with a very strong British representation. The general theme of this book is quite similar to Quattrochi and Goodchild (1997). They do have some minor o...