A geographically-aware multilevel analysis on the association between atmospheric temperature and the “Emergency and transitional shelter population”
Understanding the geographical distribution and correlates of special segments of the population has the potential for offering insight into human behavior. Our study examines the Emergency and Transitional Shelter Population (ETSP)—which includes what are commonly referred to as “homeless” people....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Bucharest
2014-11-01
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| Series: | Human Geographies: Journal of Studies and Research in Human Geography |
| Subjects: | |
| Online Access: | http://humangeographies.org.ro/articles/82/a_82_1_siordia.pdf |
| _version_ | 1818880400494166016 |
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| author | Carlos Siordia Curtis Smith Ernesto Castañeda-Tinoco |
| author_facet | Carlos Siordia Curtis Smith Ernesto Castañeda-Tinoco |
| author_sort | Carlos Siordia |
| collection | DOAJ |
| description | Understanding the geographical distribution and correlates of special segments of the population has the potential for offering insight into human behavior. Our study examines the Emergency and Transitional Shelter Population (ETSP)—which includes what are commonly referred to as “homeless” people. We use 2010 data from two sources: United States (US) Census Bureau county-level ETSP estimates; and North America Land Data Assimilation System Phase 2 (NLDAS-2). We investigate the ecological correlates of ETSP concentration by using a geographically-aware multilevel linear model. The specific aim is to investigate if an how atmospheric temperature is related with ETSP concentration by county—after accounting for population density and percent non-Hispanic-White. We use ArcGIS® 10.1 to create a spatial weight matrix of the ten most proximal counties and use SAS® 9.3 to create an algorithm that estimates County Cluster Dyadic Averages (CCDAs). By nesting the 31,090 CCDAs over the 3,109 counties in the continental US, we find a positive and statistically significant relationship between ETSP density and atmospheric temperature. Ecological studies should continue to explore the spatial heterogeneity of the ETSP. |
| first_indexed | 2024-12-19T14:45:22Z |
| format | Article |
| id | doaj.art-6252d35e96dc4079b2292ade78ccb209 |
| institution | Directory Open Access Journal |
| issn | 1843-6587 2067-2284 |
| language | English |
| last_indexed | 2024-12-19T14:45:22Z |
| publishDate | 2014-11-01 |
| publisher | University of Bucharest |
| record_format | Article |
| series | Human Geographies: Journal of Studies and Research in Human Geography |
| spelling | doaj.art-6252d35e96dc4079b2292ade78ccb2092022-12-21T20:16:59ZengUniversity of BucharestHuman Geographies: Journal of Studies and Research in Human Geography1843-65872067-22842014-11-018251510.5719/hgeo.2014.82.5A geographically-aware multilevel analysis on the association between atmospheric temperature and the “Emergency and transitional shelter population”Carlos Siordia0 Curtis Smith1Ernesto Castañeda-Tinoco2a University of Pittsburghb University of Texas at El Pasob University of Texas at El PasoUnderstanding the geographical distribution and correlates of special segments of the population has the potential for offering insight into human behavior. Our study examines the Emergency and Transitional Shelter Population (ETSP)—which includes what are commonly referred to as “homeless” people. We use 2010 data from two sources: United States (US) Census Bureau county-level ETSP estimates; and North America Land Data Assimilation System Phase 2 (NLDAS-2). We investigate the ecological correlates of ETSP concentration by using a geographically-aware multilevel linear model. The specific aim is to investigate if an how atmospheric temperature is related with ETSP concentration by county—after accounting for population density and percent non-Hispanic-White. We use ArcGIS® 10.1 to create a spatial weight matrix of the ten most proximal counties and use SAS® 9.3 to create an algorithm that estimates County Cluster Dyadic Averages (CCDAs). By nesting the 31,090 CCDAs over the 3,109 counties in the continental US, we find a positive and statistically significant relationship between ETSP density and atmospheric temperature. Ecological studies should continue to explore the spatial heterogeneity of the ETSP.http://humangeographies.org.ro/articles/82/a_82_1_siordia.pdfecologicalETSPhomelessmobile populations.multilevelspatialweather |
| spellingShingle | Carlos Siordia Curtis Smith Ernesto Castañeda-Tinoco A geographically-aware multilevel analysis on the association between atmospheric temperature and the “Emergency and transitional shelter population” Human Geographies: Journal of Studies and Research in Human Geography ecological ETSP homeless mobile populations. multilevel spatial weather |
| title | A geographically-aware multilevel analysis on the association between atmospheric temperature and the “Emergency and transitional shelter population” |
| title_full | A geographically-aware multilevel analysis on the association between atmospheric temperature and the “Emergency and transitional shelter population” |
| title_fullStr | A geographically-aware multilevel analysis on the association between atmospheric temperature and the “Emergency and transitional shelter population” |
| title_full_unstemmed | A geographically-aware multilevel analysis on the association between atmospheric temperature and the “Emergency and transitional shelter population” |
| title_short | A geographically-aware multilevel analysis on the association between atmospheric temperature and the “Emergency and transitional shelter population” |
| title_sort | geographically aware multilevel analysis on the association between atmospheric temperature and the emergency and transitional shelter population |
| topic | ecological ETSP homeless mobile populations. multilevel spatial weather |
| url | http://humangeographies.org.ro/articles/82/a_82_1_siordia.pdf |
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