Jarlath O’Neil-Dunne

Characterization of Households and its Implications for the Vegetation of Urban Ecosystems

Our understanding of the dynamics of urban ecosystems can be enhanced by examining the multidimensional social characteristics of households. To this end, we investigated the relative significance of three social theories of household structure—population, lifestyle behavior, and social stratification—to the distribution of vegetation cover in Baltimore, Maryland, USA. Our ability to assess the relative significance of these theories depended on fine-scale social and biophysical data. We distinguished among vegetation in three areas hypothesized to be differentially linked to these social theories: riparian areas, private lands, and public rights-of-way (PROWs). Using a multimodel inferential approach, we found that variation of vegetation cover in riparian areas was not explained by any of the three theories and that lifestyle behavior was the best predictor of vegetation cover on private lands. Surprisingly, lifestyle behavior was also the best predictor of vegetation cover in PROWs. The inclusion of a quadratic term for housing age significantly improved the models. Based on these research results, we question the exclusive use of income and education as the standard variables to explain variations in vegetation cover in urban ecological systems. We further suggest that the management of urban vegetation can be improved by developing environmental marketing strategies that address the underlying household motivations for and participation in local land management.

Trees grow on money: Urban tree canopy cover and environmental justice

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman’s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.

High-resolution tree canopy mapping for New York City using LIDAR and object-based image analysis

Abstract. Urban tree canopy is widely believed to have myriad environmental, social, and human-health benefits, but a lack of precise canopy estimates has hindered quantification of these benefits in many municipalities. This problem was addressed for New York City using object-based image analysis (OBIA) to develop a comprehensive land-cover map, including tree canopy to the scale of individual trees. Mapping was performed using a rule-based expert system that relied primarily on high-resolution LIDAR, specifically its capacity for evaluating the height and texture of aboveground features. Multispectral imagery was also used, but shadowing and varying temporal conditions limited its utility. Contextual analysis was a key part of classification, distinguishing trees according to their physical and spectral properties as well as their relationships to adjacent, nonvegetated features. The automated product was extensively reviewed and edited via manual interpretation, and overall per-pixel accuracy of the final map was 96%. Although manual editing had only a marginal effect on accuracy despite requiring a majority of project effort, it maximized aesthetic quality and ensured the capture of small, isolated trees. Converting high-resolution LIDAR and imagery into usable information is a nontrivial exercise, requiring significant processing time and labor, but an expert system–based combination of OBIA and manual review was an effective method for fine-scale canopy mapping in a complex urban environment.

Urban Tree Canopy and Asthma, Wheeze, Rhinitis, and Allergic Sensitization to Tree Pollen in a New York City Birth Cohort

Background: Urban landscape elements, particularly trees, have the potential to affect airflow, air quality, and production of aeroallergens. Several large-scale urban tree planting projects have sought to promote respiratory health, yet evidence linking tree cover to human health is limited. Objectives: We sought to investigate the association of tree canopy cover with subsequent development of childhood asthma, wheeze, rhinitis, and allergic sensitization. Methods: Birth cohort study data were linked to detailed geographic information systems data characterizing 2001 tree canopy coverage based on LiDAR (light detection and ranging) and multispectral imagery within 0.25 km of the prenatal address. A total of 549 Dominican or African-American children born in 1998–2006 had outcome data assessed by validated questionnaire or based on IgE antibody response to specific allergens, including a tree pollen mix. Results: Tree canopy coverage did not significantly predict outcomes at 5 years of age, but was positively associated with asthma and allergic sensitization at 7 years. Adjusted risk ratios (RRs) per standard deviation of tree canopy coverage were 1.17 for asthma (95% CI: 1.02, 1.33), 1.20 for any specific allergic sensitization (95% CI: 1.05, 1.37), and 1.43 for tree pollen allergic sensitization (95% CI: 1.19, 1.72). Conclusions: Results did not support the hypothesized protective association of urban tree canopy coverage with asthma or allergy-related outcomes. Tree canopy cover near the prenatal address was associated with higher prevalence of allergic sensitization to tree pollen. Information was not available on sensitization to specific tree species or individual pollen exposures, and results may not be generalizable to other populations or geographic areas.

An Ecology of Prestige in New York City: Examining the Relationships Among Population Density, Socio-economic Status, Group Identity, and Residential Canopy Cover

Several social theories have been proposed to explain the uneven distribution of vegetation in urban residential areas: population density, social stratification, luxury effect, and ecology of prestige. We evaluate these theories using a combination of demographic and socio-economic predictors of vegetative cover on all residential lands in New York City. We use diverse data sources including the City’s property database, time-series demographic and socio-economic data from the US Census, and land cover data from the University of Vermont’s Spatial Analysis Lab (SAL). These data are analyzed using a multi-model inferential, spatial econometrics approach. We also examine the distribution of vegetation within distinct market categories using Claritas’ Potential Rating Index for Zipcode Markets (PRIZM™) database. These categories can be disaggregated, corresponding to the four social theories. We compare the econometric and categorical results for validation. Models associated with ecology of prestige theory are more effective for predicting the distribution of vegetation. This suggests that private, residential patterns of vegetation, reflecting the consumption of environmentally relevant goods and services, are associated with different lifestyles and lifestages. Further, our spatial and temporal analyses suggest that there are significant spatial and temporal dependencies that have theoretical and methodological implications for understanding urban ecological systems. These findings may have policy implications. Decision makers may need to consider how to most effectively reach different social groups in terms of messages and messengers in order to advance land management practices and achieve urban sustainability.

Ecosystem services in managing residential landscapes: priorities, value dimensions, and cross-regional patterns

Although ecosystem services have been intensively examined in certain domains (e.g., forests and wetlands), little research has assessed ecosystem services for the most dominant landscape type in urban ecosystems—namely, residential yards. In this paper, we report findings of a cross-site survey of homeowners in six U.S. cities to 1) examine how residents subjectively value various ecosystem services, 2) explore distinctive dimensions of those values, and 3) test the urban homogenization hypothesis. This hypothesis posits that urbanization leads to similarities in the social-ecological dynamics across cities in diverse biomes. By extension, the thesis suggests that residents’ ecosystem service priorities for residential landscapes will be similar regardless of whether residents live in the humid East or the arid West, or the warm South or the cold North. Results underscored that cultural services were of utmost importance, particularly anthropocentric values including aesthetics, low-maintenance, and personal enjoyment. Using factor analyses, distinctive dimensions of residents’ values were found to partially align with the Millennium Ecosystem Assessment’s categories (provisioning, regulating, supporting, and cultural). Finally, residents’ ecosystem service priorities exhibited significant homogenization across regions. In particular, the traditional lawn aesthetic (neat, green, weed-free yards) was similarly important across residents of diverse U.S. cities. Only a few exceptions were found across different environmental and social contexts; for example, cooling effects were more important in the warm South, where residents also valued aesthetics more than those in the North, where low-maintenance yards were a greater priority.

Multiple health benefits of urban tree canopy: The mounting evidence for a green prescription.

The purpose of this study was to enhance the understanding of the health-promoting potential of trees in an urbanized region of the United States. This was done using high-resolution LiDAR and imagery data to quantify tree cover within 250m of the residence of 7910 adult participants in the California Health Interview Survey, then testing for main and mediating associations between tree cover and multiple health measures. The results indicated that more neighborhood tree cover, independent from green space access, was related to better overall health, primarily mediated by lower overweight/obesity and better social cohesion, and to a lesser extent by less type 2 diabetes, high blood pressure, and asthma. These findings suggest an important role for trees and nature in improving holistic population health in urban areas.

Characterizing tree canopy loss using multi-source GIS data in Central Massachusetts, USA

Despite numerous ecosystem services provided by urban trees, they are continually threatened by combined natural disturbances, invasive species, development and negligent management practices. This research characterizes the amount and cause of tree loss in Worcester, Massachusetts, in the northeast United States, and neighbouring towns between 2008 and 2010 using multi-source remotely sensed imagery and historical land cover maps (1976–2009). Historical land-change analysis reveals that proportional forest cover loss in the Worcester County study area exceeds that of the state by 0.26% per year, 67% of which was driven by the expansion of low-density residential land use. Between 2008 and 2010, 2% of Worcester County’s tree canopy was lost to high- and low-density urban development (47% of the total loss), United States Department of Agriculture (USDA) tree removal for Asian longhorned beetle (ALB) eradication (25%), timber harvest (15%) and ice storm damage (6%). The use of multi-source geographic information system (GIS) data to characterize tree canopy loss makes it a flexible and replicable method to monitor urban tree health.

Climate Variation Overwhelms Efforts to Reduce Nitrogen Delivery to Coastal Waters

We calculated watershed nitrogen (N) retention (inputs–outputs)/inputs) each year from 1999–2013 for nine sub-watersheds along an urban–rural gradient near Baltimore MD to determine how land use and climate influence watershed N flux. Retention is critical to efforts to control coastal eutrophication through regulatory efforts that mandate reductions in the total maximum daily load (TMDL) of N that specific water bodies can receive. Retention decreased with urbanization as well as with increases in precipitation with retention decreasing from an average of 91% in the forested sub-watershed to 16% in the most urban sub-watershed. Export was 23% higher, and retention was 7% lower in winter (November–April) than during the growing season. Total N delivery to Baltimore Harbor varied almost threefold between wet and dry years, which is significant relative to the total annual export allowed for all non-point sources to the harbor under the TMDL. These results suggest that expectations for TMDLs should consider watershed land use and climate variability, and their potential for change if they are to result in improvements in receiving water quality.

Collaborative imaging of urban forest dynamics: augmenting re-photography to visualize changes over time

The ecological sciences face the challenge of making measurements to detect subtle changes sometimes over large areas across varied temporal scales. The challenge is thus to measure patterns of slow, subtle change occurring along multiple spatial and temporal scales, and then to visualize those changes in a way that makes important variations visceral to the observer. Imaging plays an important role in ecological measurement but existing techniques often rely on approaches that are limited with respect to their spatial resolution, view angle, and/or temporal resolution. Furthermore, integrating imaging acquired through different modalities is often difficult, if not impossible. This research envisions a community-based and participatory approach based around augmented rephotography of ecosystems. We show a case study for the purpose of monitoring the urban tree canopy. The goal is to explore, for a set of urban locations, the integration of ground level rephotography with available LiDAR data, and to create a dynamic view of the urban forest, and its changes across various spatial and temporal scales. This case study gives the opportunity to explore various augments to improve the ground level image capture process, protocols to support 3D inference from the contributed photography, and both in-situ and web based visualizations of the temporal change over time.