A Spatial Analysis of the Relationship between Vegetation and Poverty
The goal of this paper was to investigate poverty and inequities that are associated with vegetation. First, we performed a pixel-level linear regression on time-series and Normalized Difference Vegetation Index (NDVI) for 72 United States (U.S.) cities with a population ≥250,000 for 16 years (1990,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-03-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | http://www.mdpi.com/2220-9964/7/3/83 |
| _version_ | 1811277205799436288 |
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| author | Teddy Dawson J.S. Onésimo Sandoval Vasit Sagan Thomas Crawford |
| author_facet | Teddy Dawson J.S. Onésimo Sandoval Vasit Sagan Thomas Crawford |
| author_sort | Teddy Dawson |
| collection | DOAJ |
| description | The goal of this paper was to investigate poverty and inequities that are associated with vegetation. First, we performed a pixel-level linear regression on time-series and Normalized Difference Vegetation Index (NDVI) for 72 United States (U.S.) cities with a population ≥250,000 for 16 years (1990, 1991, 1995, 1996, 1997, 1998, and 2001 to 2010) using Advanced Very High Resolution Radiometer 1-kilometer (1-km). Second, from the pixel-level regression, we selected five U.S. cities (Shrinking: Chicago, Detroit, Philadelphia, and Growing: Dallas and Tucson) that were one standard deviation above the overall r-squared mean and one standard deviation below the overall r-squared mean to show cities that were different from the typical cities. Finally, we used spatial statistics to investigate the relationship between census tract level data (i.e., poverty, population, and race) and vegetation for 2010, based on the 1-km grid cells using Ordinary Least Squares Regression and Geographically Weighted Regression. Our results revealed poverty related areas were significantly correlated with positive high and/or negative high vegetation in both shrinking and growing cities. This paper makes a contribution to the academic body of knowledge on U.S. urban shrinking and growing cities by using a comparative analysis with global and local spatial statistics to understand the relationship between vegetation and socioeconomic inequality. |
| first_indexed | 2024-04-13T00:11:29Z |
| format | Article |
| id | doaj.art-8953142d8c0d460d98e503c481cfdb4b |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-04-13T00:11:29Z |
| publishDate | 2018-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-8953142d8c0d460d98e503c481cfdb4b2022-12-22T03:11:04ZengMDPI AGISPRS International Journal of Geo-Information2220-99642018-03-01738310.3390/ijgi7030083ijgi7030083A Spatial Analysis of the Relationship between Vegetation and PovertyTeddy Dawson0J.S. Onésimo Sandoval1Vasit Sagan2Thomas Crawford3Department of Sociology and Anthropology, Saint Louis University, St. Louis, MO 63108, USADepartment of Sociology and Anthropology, Saint Louis University, St. Louis, MO 63108, USADepartment of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO 63108, USADepartment of Geography, Virginia Tech, 220 Stanger Street, Blacksburg, VA 24061; USAThe goal of this paper was to investigate poverty and inequities that are associated with vegetation. First, we performed a pixel-level linear regression on time-series and Normalized Difference Vegetation Index (NDVI) for 72 United States (U.S.) cities with a population ≥250,000 for 16 years (1990, 1991, 1995, 1996, 1997, 1998, and 2001 to 2010) using Advanced Very High Resolution Radiometer 1-kilometer (1-km). Second, from the pixel-level regression, we selected five U.S. cities (Shrinking: Chicago, Detroit, Philadelphia, and Growing: Dallas and Tucson) that were one standard deviation above the overall r-squared mean and one standard deviation below the overall r-squared mean to show cities that were different from the typical cities. Finally, we used spatial statistics to investigate the relationship between census tract level data (i.e., poverty, population, and race) and vegetation for 2010, based on the 1-km grid cells using Ordinary Least Squares Regression and Geographically Weighted Regression. Our results revealed poverty related areas were significantly correlated with positive high and/or negative high vegetation in both shrinking and growing cities. This paper makes a contribution to the academic body of knowledge on U.S. urban shrinking and growing cities by using a comparative analysis with global and local spatial statistics to understand the relationship between vegetation and socioeconomic inequality.http://www.mdpi.com/2220-9964/7/3/83geographically weighted regressionNormalized Difference Vegetation Indexpovertyspatial statisticscities |
| spellingShingle | Teddy Dawson J.S. Onésimo Sandoval Vasit Sagan Thomas Crawford A Spatial Analysis of the Relationship between Vegetation and Poverty ISPRS International Journal of Geo-Information geographically weighted regression Normalized Difference Vegetation Index poverty spatial statistics cities |
| title | A Spatial Analysis of the Relationship between Vegetation and Poverty |
| title_full | A Spatial Analysis of the Relationship between Vegetation and Poverty |
| title_fullStr | A Spatial Analysis of the Relationship between Vegetation and Poverty |
| title_full_unstemmed | A Spatial Analysis of the Relationship between Vegetation and Poverty |
| title_short | A Spatial Analysis of the Relationship between Vegetation and Poverty |
| title_sort | spatial analysis of the relationship between vegetation and poverty |
| topic | geographically weighted regression Normalized Difference Vegetation Index poverty spatial statistics cities |
| url | http://www.mdpi.com/2220-9964/7/3/83 |
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