Vegetation Structure and Distribution Across Scales in a Large Metropolitan Area: Case Study of Austin MSA, Texas, USA
The spatial distribution of vegetation across metropolitan areas is important for wildlife habitat, air quality, heat mitigation, recreation, and other ecosystem services. This study investigated relationships between vegetation patterns and parcel characteristics at multiple scales of the Austin Me...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Geographies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-7086/5/1/11 |
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| Summary: | The spatial distribution of vegetation across metropolitan areas is important for wildlife habitat, air quality, heat mitigation, recreation, and other ecosystem services. This study investigated relationships between vegetation patterns and parcel characteristics at multiple scales of the Austin Metropolitan Statistical Area (MSA), a rapidly growing region in central Texas characterized by diverse biophysical and socioeconomic landscapes. We used LiDAR data to map vegetation types and distributions across a 6000 km<sup>2</sup> study area. Principal component analysis (PCA) and regression models were employed to explore tree, shrub, and grass cover across parcels, cities, and the MSA, considering home value, age, size, and distance to the city center. At the MSA scale, tree and shrub cover were higher in the Edwards Plateau than in the Blackland Prairie ecoregion. Tree cover increased with parcel size and home value, especially in suburban areas. Older parcels had more mature trees, though less so in the grass-dominated Blackland Prairie. Shrub cover was higher on larger parcels in the Edwards Plateau, while the Blackland Prairie showed the opposite trend. PCA explained 60% of the variance, highlighting links between vegetation and urban development. Our findings reveal how biophysical and socioeconomic factors interact to shape vegetation, offering considerations for land use, housing, and green infrastructure planning. |
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| ISSN: | 2673-7086 |