The University of Washington College of Built Environments (CBE) recognized faculty and staff at the 2023 CBE Graduation Celebration. These awards celebrate CBE faculty and staff for their dedication, service, and many contributions to our community. Congratulations to all our awardees! Lionel Pries Award for Excellence in Teaching: Catherine De Almeida Outstanding Faculty Award: Jeffrey Ochsner Outstanding Part-Time Teaching Award: Marty Curry Distinguished Staff Award: Laura Barrera Read more here.
Department: Urban Design and Planning
Integration of Urban Science and Urban Climate Adaptation Research: Opportunities to Advance Climate Action
Lobo, J., Aggarwal, R. M., Alberti, M., Allen-Dumas, M., Bettencourt, L. M. A., Boone, C., Brelsford, C., Broto, V. C., Eakin, H., Bagchi-Sen, S., Meerow, S., D’Cruz, C., Revi, A., Roberts, D. C., Smith, M. E., York, A., Lin, T., Bai, X., Solecki, W., … Gauthier, N. (2023). Integration of urban science and urban climate adaptation research: opportunities to advance climate action. Npj Urban Sustainability, 3(1), 32–39. https://doi.org/10.1038/s42949-023-00113-0
Abstract
There is a growing recognition that responding to climate change necessitates urban adaptation. We sketch a transdisciplinary research effort, arguing that actionable research on urban adaptation needs to recognize the nature of cities as social networks embedded in physical space. Given the pace, scale and socioeconomic outcomes of urbanization in the Global South, the specificities and history of its cities must be central to the study of how well-known agglomeration effects can facilitate adaptation. The proposed effort calls for the co-creation of knowledge involving scientists and stakeholders, especially those historically excluded from the design and implementation of urban development policies.
Detecting Subpixel Human Settlements in Mountains Using Deep Learning: A Case of the Hindu Kush Himalaya 1990–2020
Chen, T.-H. K., Pandey, B., & Seto, K. C. (2023). Detecting subpixel human settlements in mountains using deep learning: A case of the Hindu Kush Himalaya 1990–2020. Remote Sensing of Environment, 294, 113625–. https://doi.org/10.1016/j.rse.2023.113625
Abstract
The majority of future population growth in mountains will occur in small- and medium-sized cities and towns and affect vulnerable ecosystems. However, mountain settlements are often omitted from global land cover analyses due to the low spatial resolution of satellite images, which cannot resolve the small scale of mountains settlements. This study demonstrates, for the first time, the potential of deep learning to detect human settlements in mountains at the sub-pixel level, based on Landsat satellite imagery. We hypothesized that adding spatial and temporal features could improve the detection of mountain settlements since spectral information alone led to inaccurate results. For spatial features, we compared a U-shaped neural network (U-Net), a deep learning algorithm that automatically learns spatial features, with a simple random forest (RF) algorithm. Then, we assessed whether temporal features would increase accuracy by comparing two input datasets, multispectral imagery and temporal features from the Continuous Change Detection and Classification (CCDC) algorithm. We evaluated each method by calculating the accuracies of (1) the binary settlement footprint, (2) the subpixel estimates of impervious surfaces, and (3) urban growth. We tested the accuracies using visually interpreted datasets from time-series Google Earth images across the Hindu Kush Himalaya that were not used for training to evaluate model transferability. The U-Net successfully improved mountain settlement mapping compared to the random forest, with a substantial discrepancy in small settlements. The time-series results from the U-Net successfully captured long-term urban growth but fewer short-term changes. Contrary to expectations, the CCDC temporal features reduced the accuracy of mountain settlement mapping due to frequent cloud cover in hilly areas. Our subpixel analysis reveals that the built-up area of the Hindu Kush Himalaya has expanded at a rate of 61 km2 per year from 1990 to 2020, which is about twice the estimate of the Global Human Settlement Layer using binary urban/non-urban classifications.
Keywords
Urban land cover; Land cover fraction; Peri-urban; Built-up area; Subpixel mapping; Machine learning; Time-series; Himalaya; CCDC
Urban Infrastructure Lab Report on High-Speed Rail
The Urban Infrastructure Lab researchers have released a report on a Cascadia region high-speed rail project. College of Built Environments faculty Jan Whittington and Qing Shen were authors on the report, along with 3 Interdisciplinary Ph.D. in Urban Design and Planning students (Siman Ning, Haoyu Yue, and Chin-Wei Chen), and a Master of Urban Planning candidate (Richard McMichael). This report examines the successes and lessons learned from existing high-speed rail projects in Europe and Asia, including 50 hours of interviews…
Higher Depression Risks in Medium- Than in High-Density Urban Form Across Denmark
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
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.
Tzu-Hsin Karen Chen
UW Department of Urban Design and Planning in the College of Built Environments.
Urban Design & Planning student selected for 2023 applied research fellow cohort
The Population Health Initiative announced the summer 2023 cohort of applied research fellows. Among the group of 5 students (3 graduate and 2 undergraduate) is Pamela Lim from the College of Built Environments Urban Design & Planning department. These students will spend 10 weeks over the summer working collaboratively with King County’s demographer and Public Health – Seattle & King County’s Assessment, Policy Development and Evaluation Unit with the support of the Population Health Applied Research Fellowship. The team will…
EarthLab 2023-2024 Innovation Grant awardees
EarthLab selected the 2023-2024 Innovation Grant Awardees in April 2023. One of the projects chosen includes College of Built Environments researchers on the interdisciplinary team. The project description and research team is detailed below. “Cultivating Transdisciplinary Support for Equitable and Resilient Floodplain Solutions” Project Description: In 2021 a massive flood on the Nooksack River left a trail of destruction in its wake. Floods are the most expensive natural hazard in Washington State, a risk that is exacerbated by climate change….
Population Health Initiative awards multiple College of Built Environments teams planning grants
The Population Health Initiative announced 12 climate change planning grant awardees. Of those 12 teams, 4 include College of Built Environments researchers. Descriptions of their projects are below. Read the CBE News story here. Linking Climate Adaptation and Public Health Outcomes in Yavatmal, Maharashtra Investigators Sameer H. Shah, Environmental and Forest Sciences Celina Balderas Guzmán, Landscape Architecture Pronoy Rai, Portland State University Project abstract This proposal collects primary interview data with landed and landless agriculturalists in Yavatmal district in…
CBE researchers selected for inaugural cohort of Urban@UW Research to Action Collaboratory
College of Built Environments researchers are selected for inaugural cohort of the Urban@UW Research to Action Collaboratory (RAC). Throughout the next 18 months, Urban@UW will work with these teams and provide seed funds, dedicated time to build team cohesion and collaboration skills, and foster opportunities for peer support and shared resources and learning. The project below was one of two projects selected for this cohort. See the full story here. Just Circular Communities: A Resiliency Framework to Support a Just…