Urban, M.C., Alberti, M., De Meester, L. et al. Interactions between climate change and urbanization will shape the future of biodiversity. Nat. Clim. Chang. (2024). https://doi.org/10.1038/s41558-024-01996-2
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Abstract
Climate change and urbanization are two of the most prominent global drivers of biodiversity and ecosystem change. Fully understanding, predicting and mitigating the biological impacts of climate change and urbanization are not possible in isolation, especially given their growing importance in shaping human society. Here we develop an integrated framework for understanding and predicting the joint effects of climate change and urbanization on ecology, evolution and their eco-evolutionary interactions. We review five examples of interactions and then present five hypotheses that offer opportunities for predicting biodiversity and its interaction with human social and cultural systems under future scenarios. We also discuss research opportunities and ways to design resilient landscapes that address both biological and societal concerns.
Wang, Z., Ito, K., & Biljecki, F. (2024). Assessing the equity and evolution of urban visual perceptual quality with time series street view imagery. Cities, 145, 104704-. https://doi.org/10.1016/j.cities.2023.104704
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Abstract
The well-being of residents is considerably influenced by the quality of their environment. However, due to the lack of large-scale quantitative and longitudinal evaluation methods, it has been challenging to assess residents' satisfaction and achieve social inclusion goals in neighborhoods. We develop a novel cost-effective method that utilizes time series street view imagery for evaluating and monitoring visual environmental quality in neighborhoods. Unlike most research that relies on site visits or surveys, this study trains a deep learning model with a large-scale dataset to analyze six perception indicators' scores in neighborhoods in different geographies and does so longitudinally thanks to imagery taken over a period of a decade, a novelty in the body of knowledge. Implementing the approach, we examine public housing neighborhoods in Singapore and New York City as case studies. The results demonstrated that temporal imagery can effectively assess spatial equity and monitor the visual environmental qualities of neighborhoods over time, providing a new, comprehensive, and scalable workflow. It can help governments improve policies and make informed decisions on enhancing the design and living standards of urban residential areas, including public housing communities, which may be affected by social stigmatization, and monitor the effectiveness of their policies and actions.
Keywords
Residential quality; Public housing; Environmental quality; Spatial equity; Street view imagery; Visual environment
Tzu-Hsin Karen Chen, Mark E. Kincey, Nick J. Rosser, Karen C. Seto, Identifying recurrent and persistent landslides using satellite imagery and deep learning: A 30-year analysis of the Himalaya, Science of The Total Environment, Volume 922, 2024, 171161, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2024.171161.
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Abstract
This paper presents a remote sensing-based method to efficiently generate multi-temporal landslide inventories and identify recurrent and persistent landslides. We used free data from Landsat, nighttime lights, digital elevation models, and a convolutional neural network model to develop the first multi-decadal inventory of landslides across the Himalaya, spanning from 1992 to 2021. The model successfully delineated >265,000 landslides, accurately identifying 83 % of manually mapped landslide areas and 94 % of reported landslide events in the region. Surprisingly, only 14 % of landslide areas each year were first occurrences, 55–83 % of landslide areas were persistent and 3–24 % had reactivated. On average, a landslide-affected pixel persisted for 4.7 years before recovery, a duration shorter than findings from small-scale studies following a major earthquake event. Among the recovered areas, 50 % of them experienced recurrent landslides after an average of five years. In fact, 22 % of landslide areas in the Himalaya experienced at least three episodes of landslides within 30 years. Disparities in landslide persistence across the Himalaya were pronounced, with an average recovery time of 6 years for Western India and Nepal, compared to 3 years for Bhutan and Eastern India. Slope and elevation emerged as significant controls of persistent and recurrent landslides. Road construction, afforestation policies, and seismic and monsoon activities were related to changes in landslide patterns in the Himalaya.
Keywords
Landslide inventory; Landslide evolution; Vegetation recovery; Multi-temporalSpatiotemporal analysis; Machine learning
Ashayeri, M., & Abbasabadi, N. (2024). Unraveling energy justice in NYC urban buildings through social media sentiment analysis and transformer deep learning. Energy and Buildings, 306, 113914-. https://doi.org/10.1016/j.enbuild.2024.113914
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Abstract
This study explores the intricate relationship between human sentiment on social media data, herein tweet posts on X platform, urban building characteristics, and the socio-spatial dynamics of New York City (NYC) boroughs. Leveraging Natural Language Processing (NLP) techniques, particularly sentiment analysis, augmented by the capabilities of transformer deep learning models, RoBERTa, the study places particular emphasis on the term ‘Stay-at-Home’ to encapsulate the pronounced shift in building occupancy during the pandemic's inaugural year. This focus intertwines with pivotal terms like ‘Energy Bill’ and ‘HVAC’, shedding light on their interconnected implications. The sentiment analysis leverages data from New York City's PLUTO and the Department of Energy's LEAD databases to emotional disparities connected to urban building characteristics as well as demographic and socioeconomic factors. This analytical approach unravels prevailing public emotions and extends the discussion to include energy justice concerns, viewing them through the lens of the city's built infrastructure. The research uncovers profound disparities in the built environment and the allocation of resources in NYC, highlighting the critical need to embrace a spatial justice framework for a sustainable future. This research can aid designers, planners, and policymakers in their efforts to promote equitable and inclusive urban development.
Jung, M. C., Yost, M. G., Dannenberg, A. L., Dyson, K., & Alberti, M. (2024). Legacies of redlining lead to unequal cooling effects of urban tree canopy. Landscape and Urban Planning, 246. https://doi.org/10.1016/j.landurbplan.2024.105028
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Abstract
Redlining—a racially discriminatory policy of systematic disinvestment established by the Home Owners’ Loan Corporation (HOLC) in the 1930s and continued until the late 1960s—still influences the contemporary landscape of cities in the US. While the heterogeneous distribution of land surface temperature and tree canopy cover between neighborhoods with different HOLC grades have been recently examined, the development of long-term and city-specific heat management strategies is still limited. Here, we explored the effect of redlining in Portland, Oregon, and Philadelphia, Pennsylvania, to assess its contemporary impact on climate equity. We performed a change analysis of land surface temperature and tree canopy area over the past and introduced mixed-effects models to test the intra- and inter-city differences in canopy cooling effects between the different HOLC grades. We found that (1) persistent temporal patterns of lower land surface temperatures and larger tree canopy areas are observed in higher HOLC grades, (2) greater green equity was achieved through contrasting temporal changes in tree canopy areas across HOLC grades in Portland and Philadelphia, and (3) opposite patterns exist between these cities, with stronger canopy cooling effects in neighborhoods with a Low HOLC grade in Portland and those with a High HOLC grade in Philadelphia. Differences in tree canopy change between the two cities over the past decade highlight potential influences of city-specific tree planting practices. Local planners should back tree planting initiatives to equitably mitigate urban heat exposure, considering historical redlining contexts and contemporary landscape features.
Keywords
Redlining; HOLC grade; Tree canopy; Land surface temperature; Tree equity
CBE Researchers developed a report “Finding Common Ground: Best Practices for Policies Supporting Transit-Oriented Development,” with the Mobility Innovation Center and led by the Washington Center for Real Estate Research. Project Team: Mason Virant, Associate Director, Washington Center for Real Estate Research Christian Phillips, Urban Design and Planning PhD Program Steven C. Bourassa, PhD Director, Washington Center for Real Estate Research Arthur Acolin, Associate Professor, Runstad Department of Real Estate Visit the project page here.
Ko, W. H., Schiavon, S., Altomonte, S., Andersen, M., Batool, A., Browning, W., Burrell, G., Chamilothori, K., Chan, Y.-C., Chinazzo, G., Christoffersen, J., Clanton, N., Connock, C., Dogan, T., Faircloth, B., Fernandes, L., Heschong, L., Houser, K. W., Inanici, M., … Kent, M. (2022). Window View Quality: Why It Matters and What We Should Do. Leukos, 18(3), 259–267. https://doi.org/10.1080/15502724.2022.2055428
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Research Interests: Regional econ. development (tech innovation, human capital, regional industry), Transportation planning/policy (travel behavior, mobility, sustainable transportation), intersection between planning (or transportation), population/public health, and climate change, and urban form
Chen, T.-H. K., Horsdal, H. T., Samuelsson, K., Closter, A. M., Davies, M., Barthel, S., Pedersen, C. B., Prishchepov, A. V., & Sabel, C. E. (2023). Higher depression risks in medium- than in high-density urban form across Denmark. Science Advances, 9(21), eadf3760–eadf3760. https://doi.org/10.1126/sciadv.adf3760
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Abstract
Urban areas are associated with higher depression risks than rural areas. However, less is known about how different types of urban environments relate to depression risk. Here, we use satellite imagery and machine learning to quantify three-dimensional (3D) urban form (i.e., building density and height) over time. Combining satellite-derived urban form data and individual-level residential addresses, health, and socioeconomic registers, we conduct a case-control study (n = 75,650 cases and 756,500 controls) to examine the association between 3D urban form and depression in the Danish population. We find that living in dense inner-city areas did not carry the highest depression risks. Rather, after adjusting for socioeconomic factors, the highest risk was among sprawling suburbs, and the lowest was among multistory buildings with open space in the vicinity. The finding suggests that spatial land-use planning should prioritize securing access to open space in densely built areas to mitigate depression risks.
Walter, R. J., Tillyer, M. S., Ramiller, A., & Acolin, A. (2023). Scaling Down from the Neighborhood in Urban Planning Research and Practice: The Potential Benefits of a Micro-Scale Focus. Journal of Planning Education and Research. https://doi.org/10.1177/0739456X231175593
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Abstract
The neighborhood has been the dominant spatial unit in urban planning since the early 20th century. Criticisms of the neighborhood unit include disagreements about defining boundaries, methodological challenges in capturing neighborhood effects, and negative impacts on communities. With advancements in data management, and public data available at smaller units (street block or property), quantitative analyses are possible at the micro-scale. This commentary draws on crime research and prevention to illustrate the benefits of micro-scale approaches to quantitative analyses in the field of urban planning, arguing that the devolution to smaller scales may be a vehicle for efficient resource allocation.