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15 results on '"geographic unit"'

2. How to Capture Neighborhood Change in Small Cities.

Author

Kaida, Lisa, Ramos, Howard, Singh, Diana, and McLay, Rachel

Subjects
SMALL cities, NEIGHBORHOOD change, CENSUS districts
Abstract

Copyright of Canadian Studies in Population is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2020
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3. Nuevas perspectivas sobre el Problema de la Unidad Espacial Modificable (PUEM) en relación con la representación cartográfica de enfermedades raras.

Author

Sánchez-Díaz, Germán, Alonso-Ferreira, Verónica, Posada de la Paz, Manuel, and Escobar, Francisco

Subjects
*PHYSIOGRAPHIC provinces, *MEDICAL geography, *RARE diseases, *NEIGHBORHOODS, *VISUALIZATION
Abstract

This study analyses the effect of the modifiable areal unit problem (MAUP) comparing mortality data of a specific rare disease (Huntington) in three levels of spatial aggregation in Spain. The objective is to compare mortality indicators and cartographic visualisations in order to soundly advise on the optimal aggregation level according to population, covered area, and number of cases. We designed an adjacency ratio to observe the effect of neighbourhood relationships among three geographic units: province; district (comarca); municipality. For each level of aggregation, we performed epidemiological indicators of mortality as well as local indicators of spatial association. Maps were plotted with user-defined intervals to compare visual and statistical differences. MAUP-related effects are particularly noticeable in relatively infrequent events such as rare diseases. We found that district displayed the highest indicator for stability in the adjacency ratio and showed optimal characteristics for spatial resolution and the amount of information revealed through plotting. This helps in the choice of the working scale that can be used with other diseases or the levels of aggregation as a first step for more advanced epidemiological analyses. [ABSTRACT FROM AUTHOR]

Published
2020
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4. Geospatial Information Diffusion Technology Supporting by Background Data

Author

Chongfu Huang

Subjects
geographic unit, background data, information diffusion, normal diffusion, self-learning discrete regression, Engineering (General). Civil engineering (General), TA1-2040, Risk in industry. Risk management, HD61
Abstract

In this paper, we express the initial concept of geospatial information diffusion supporting by background data, which plays a role as a bridge to diffuse the information carried by the observations, obtained from observed units, to gap units. The self-learning discrete regression, based on the multivariate normal diffusion, is suggested to supplement incomplete geospatial data to be complete. The suggested method has obvious advantages over the geographic weighted regression and the artificial neural network for inferring the observations in gap units

Published
2019
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8. Design of Dissimilarity Measures: A New Dissimilarity Between Species Distribution Areas

Author

Hennig, Christian, Hausdorf, Bernhard, Bock, H. -H., editor, Gaul, W., editor, Vichi, M., editor, Arabie, Ph., editor, Baier, D., editor, Critchley, F., editor, Decker, R., editor, Diday, E., editor, Greenacre, M., editor, Lauro, C., editor, Meulman, J., editor, Monari, P., editor, Nishisato, S., editor, Ohsumi, N., editor, Opitz, O., editor, Ritter, G., editor, Schader, M., editor, Weihs, C., editor, Batagelj, Vladimir, editor, Bock, Hans-Hermann, editor, Ferligoj, Anuška, editor, and Žiberna, Aleš, editor

Published
2006
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13. How to Capture Neighborhood Change in Small Cities

Author

Lisa Kaida, Howard Ramos, Rachel McLay, Diana Singh, and Sociology

Subjects
History, Small city, 05 social sciences, 0211 other engineering and technologies, 0507 social and economic geography, 021107 urban & regional planning, 02 engineering and technology, Census, geographic unit, small cities, Boundary (real estate), Geography, Neighborhood change, Census Tracts, Dissemination Area, Aggregated Dissemination Areas, Regional science, 050703 geography, Charlottetown, Demography
Abstract

Small cities across North America are experiencing rapid changes, but methodological obstacles hamper researchers’ ability to analyze them. This research note explores some of the methodological challenges faced by researchers and offers solutions. Using Charlottetown, Prince Edward Island, as a case study, we show that a major challenge lies in choosing meaningful geographic units for small city neighborhoods, and we evaluate the benefits and drawbacks of several geographical options. Another major challenge is that the boundaries of existing units change between census years, demanding an approach to reconstructing them to allow for temporal analysis. We propose two feasible solutions for re-creating neighborhood geographic units over time: ‘moving forward’ and ‘going backward.’ Both involve selecting units from a particular census year to serve as a fixed point of reference for the re-creation of boundaries across multiple census years. We conclude by cautioning that studying changes in small cities over longer time periods in Canada is not feasible because of the extensive and complex boundary changes that have occurred between census years. We offer an approach for looking at shorter time periods. SSHRC Insight Grant

Published
2020

14. New insights around the Modifiable Areal Unit Problem (MAUP) in its relation to cartographic representation of rare diseases

Author

Germán Sánchez-Díaz, Manuel Posada de la Paz, Francisco Escobar, Verónica Alonso-Ferreira, and Instituto de Salud Carlos III

Subjects
Cartography, PUEM, Aggregated data, Epidemiology, Geography, Planning and Development, Geographic unit, lcsh:G1-922, Geografía médica, Diseases, Enfermedades, MAUP, Medical geography, Datos agregados, Unidad geográfica, General Earth and Planetary Sciences, Epidemiología, Cartografía, lcsh:Geography (General)
Abstract

[ES] En el marco del análisis espacio-temporal de la Enfermedades Raras (ER) en España, los efectos derivados del Problema de la Unidad Espacial Modificable (PUEM) condicionan la interpretación de los resultados. Este estudio tiene como objetivo comparar indicadores de mortalidad y visualización cartográfica para recomendar la unidad geográfica de trabajo óptima según población, área cubierta y el número de casos de la enfermedad. Se estudiaron los fallecimientos debidos a una ER (Huntington) en tres niveles de agregación espacial; el municipio, la comarca y la provincia. Se diseñó una ratio de adyacencia para observar el efecto de las relaciones de vecindad entre las tres unidades administrativas tratadas. Se calcularon indicadores epidemiológicos de mortalidad, así como indicadores locales de asociación espacial en cada nivel de agregación. Los resultados se representaron cartográficamente utilizando intervalos definidos por el usuario para comparar de forma visual las diferencias estadísticas y cartográficas. El PUEM fue particularmente visible trabajando con datos agregados de ER. Las comarcas representaron el mayor nivel de estabilidad en la ratio de adyacencia así como la unidad geográfica óptima en términos de resolución espacial y variabilidad de la información representada cartográficamente. Este proceso de ayuda en la elección de la escala de trabajo puede ser extrapolado a otras enfermedades o niveles de agregación, como paso previo a análisis epidemiológicos más avanzados. [EN] This study analyses the effect of the modifiable areal unit problem (MAUP) comparing mortality data of a specific rare disease (Huntington) in three levels of spatial aggregation in Spain. The objective is to compare mortality indicators and cartographic visualisations in order to soundly advise on the optimal aggregation level according to population, covered area, and number of cases. We designed an adjacency ratio to observe the effect of neighbourhood relationships among three geographic units: province; district (comarca); municipality. For each level of aggregation, we performed epidemiological indicators of mortality as well as local indicators of spatial association. Maps were plotted with user-defined intervals to compare visual and statistical differences. MAUP-related effects are particularly noticeable in relatively infrequent events such as rare diseases. We found that district displayed the highest indicator for stability in the adjacency ratio and showed optimal characteristics for spatial resolution and the amount of information revealed through plotting. This helps in the choice of the working scale that can be used with other diseases or the levels of aggregation as a first step for more advanced epidemiological analyses. Este artículo se enmarca dentro del proyecto de investigación financiado por la Acción Estratégica en Salud Intramural del Instituto de Salud Carlos III. Referencia del proyecto: TPY1238/15. Sí

Published
2020

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