five

Measuring urban tree loss dynamics across residential landscapes

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Mendeley Data2024-06-05 更新2024-06-27 收录
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https://catalog.data.gov/dataset/be36c187-8447-4aa2-8bb7-9c26a75ffc33
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The spatial arrangement of urban vegetation depends on urban morphology and socio-economic settings. Urban vegetation changes over time because of human management. Urban trees are removed due to hazard prevention or aesthetic preferences. Previous research attributed tree loss to decreases in canopy cover. However, this provides little information about location and structural characteristics of trees lost, as well as environmental and social factors affecting tree loss dynamics. This is particularly relevant in residential landscapes where access to residential parcels for field surveys is limited. We tested whether multi-temporal airborne LiDAR and multi-spectral imagery collected at a 5-year interval can be used to investigate urban tree loss dynamics across residential landscapes in Denver, CO and Milwaukee, WI, covering 400,705 residential parcels in 444 census tracts. Position and stem height of trees lost were extracted from canopy height models calculated as the difference between final (year 5) and initial (year 0) vegetation height derived from LiDAR. Multivariate regression models were used to predict number and height of tree stems lost in residential parcels in each census tract based on urban morphological and socio-economic variables. A total of 28,427 stems were lost from residential parcels in Denver and Milwaukee over 5 years. Overall, 7% of residential parcels lost one stem, averaging 90.87 stems per km2. Average stem height was 10.16 m, though trees lost in Denver were taller compared to Milwaukee. The number of stems lost was higher in neighborhoods with higher canopy cover and developed before the 1970s. However, socio-economic characteristics had little effect on tree loss dynamics. The study provides a robust method for measuring urban tree loss dynamics within and across entire cities, and represents a first step towards high resolution assessments of the three-dimensional change of urban vegetation at large spatial scales.
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2023-06-28
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