Journal Article Archives - Page 10 of 66

Alternative gentrification: coexistence of traditional and new industries in historic districts through transfer of development rights in Dihua Street, Taiwan

Sho, K., Chen, Y.-L., & Oshima, K. T. (2023). Alternative gentrification: coexistence of traditional and new industries in historic districts through transfer of development rights in Dihua Street, Taiwan. International Journal of Heritage Studies : IJHS, 1–16. https://doi.org/10.1080/13527258.2023.2250776

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Abstract

The transfer of development rights (TDR) has been widely used in the preservation of historic districts. The Dihua Street TDR (DS-TDR) in Taipei, Taiwan, successfully preserves the exteriors of historic buildings and traditional landscape in Dihua Street, without significant displacement of previous residents or increases in rents. This study describes this process as 'alternative gentrification', which facilitates the coexistence of traditional and new industries in historic districts, unlike typical gentrification in other cities. Although new shops gradually replace existing shops, the rent level remains relatively affordable compared with other shopping streets in the Taipei city centre. These aspects enable the coexistence of a clustering of new creative-industrial stores and existing stores within the buildings restored and landscaped by the DS-TDR.

Keywords

Historic district; transfer of development rights; historic buildings; restoration; landscaping; Commercial Gentrification; Heritage; Displacement; TDR; Urbanization; Conservation; Neighborhood; Culture; State

An Economic Analysis of Incorporating New Shared Mobility into Public Transportation Provision

Wang, Y., & Shen, Q. (2023). An economic analysis of incorporating new shared mobility into public transportation provision. Transport Policy, 141, 263–273. https://doi.org/10.1016/j.tranpol.2023.07.025

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Abstract

Transit agencies in the US have shown great interests in the possibility of incorporating on-demand shared mobility modes into their fixed-route transit services. However, the cost-effectiveness of on-demand modes has not been clearly demonstrated, and there lacks an effective method for transit agencies to compare the costs of different service provision options. This study develops an economic-theory-based framework that appropriately conceptualizes the total economic cost of incorporating on-demand modes into transit. Based on the theoretical framework, a simulation model is built to operationalize an approach for evaluating the cost-effectiveness of transit-supplementing, on-demand mobility services. We demonstrate the applicability of this approach using Via to Transit program in the Seattle region. By accounting for both the service provider's cost and the users' cost, we obtain a more complete and accurate measure for the cost advantages of the on-demand modes in this case in comparison to expanding fixed-route transit, where the total economic cost for the on-demand mode is 22% lower than the fixed route transit. The theoretical framework and the simulation model can support the decision-making of public transit agencies as they explore incorporating mobility on demand to supplement traditional transit.

Keywords

Public transit; On-demand shared mobility; Marginal cost; Generalized travel cost; Transportation simulation

Blockchain-Enabled Supply Chain Coordination for Off-Site Construction Using Bayesian Theory for Plan Reliability

Kim, M., Zhao, X., Kim, Y.-W., & Rhee, B.-D. (2023). Blockchain-enabled supply chain coordination for off-site construction using Bayesian theory for plan reliability. Automation in Construction, 155, 105061–. https://doi.org/10.1016/j.autcon.2023.105061

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Abstract

The potential of blockchain is being widely explored within the construction industry, particularly for transparent communication and information sharing. However, only limited research has focused on implementing blockchain to address the challenge of aligning conflicting interests among independent agents, specifically, supply chain coordination. This paper develops a blockchain-enabled supply chain coordination system that facilitates the alignment of diverse decisions made by stakeholders in an off-site construction supply chain. To achieve this goal, Bayesian updating is employed to estimate the probabilistic distribution of plan reliability, enabling the calculation of a supplier rebate that incentivizes the contractor to schedule deliveries aimed at minimizing joint supply chain costs. Additionally, the paper describes a blockchain-enabled system that allows practitioners to measure plan reliability. The research findings demonstrate that the blockchain-enabled supply chain coordination system fosters shared common knowledge among project stakeholders and facilitates real-time updates of changes in the contractor's plan reliability, aligning the interests of both the supplier and contractor.

Keywords

Supply chain coordination; Bayesian updating; Plan reliability; Rebate pricing; Blockchain; Smart contracts; Off-site construction

Association of Perceived Neighborhood Environments With Cognitive Function in Older Adults

Kim, B., Rosenberg, D. E., Dobra, A., Barrington, W. E., Hurvitz, P. M., & Belza, B. (2023). Association of Perceived Neighborhood Environments With Cognitive Function in Older Adults. Journal of Gerontological Nursing, 49(8), 35–41. https://doi.org/10.3928/00989134-20230707-04

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Abstract

The current study examined the associations between perceptions of the social and physical neighborhood environments and cognitive function in older adults. This cross-sectional study analyzed 821 adults aged & GE;65 years from the Adult Changes in Thought study. Perceived neighborhood attributes were measured by the Physical Activity Neighborhood Environment Scale. Cognitive function was assessed using the Cognitive Ability Screening Instrument. The associations were tested using multivariate linear regression. One point greater perceived access to public transit was associated with 0.56 points greater cognitive function score (95% confidence interval [CI] [0.25, 0.88]), and an additional one point of perceived sidewalk coverage was related to 0.22 points higher cognitive function score (95% CI [0.00, 0.45]) after controlling for sociodemographic factors. The perception of neighborhood attributes alongside physical infrastructure may play an important role in supporting older adults' cognitive function.

Keywords

Built environment; Physical-activity; Dementia; Reverse; Walking; Disease

Mortgage Loan Costs: Magnitude and Drivers of Variation

Arthur Acolin & Rebecca J. Walter (2023). Mortgage Loan Costs: Magnitude and Drivers of Variation. Housing Policy Debate, DOI: 10.1080/10511482.2023.2236984

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Abstract

This article uses national data disclosed as part of the Home Mortgage Disclosure Act (HMDA) to examine variations in loan costs based on type of loan, borrower, purpose (purchase, improvement, or refinance), and neighborhood characteristics. Loan costs are generally higher for nonconventional conforming loans with higher levels of credit risks (loans with higher combined loan-to-value, higher debt-to-income ratios, and for investment properties). This implies that product and borrower risk impact loan costs. However, borrower characteristics such as income and race/ethnicity are also associated with differences in loan costs even after controlling for loan characteristics, location, and lender fixed effects. Total loan costs are higher both in dollar terms and as a share of the loan amount for Black borrowers and Hispanic borrowers, and total loan costs represent a higher share of the loan amount for lower income borrowers. These disparities are larger in neighborhoods with higher levels of lender concentration and implicit racial bias. These findings suggest that in addition to access to mortgages and interest rates, loan costs can represent a barrier for access to homeownership with a disparate impact for Black and Hispanic borrowers, which contributes to perpetuate the homeownership gap.

Keywords

Mortgage loan costs; homeownership; borrowing constraints; homeownership gap

“Moving or not?”: Factors affecting community responses to environmental disruption

Depari, Catharina D.A., & Lindell, Michael K. (2023). “Moving or not?”: Factors affecting community responses to environmental disruption. International Journal of Disaster Risk Reduction, 95, 103898.

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Abstract

Disputes between government authorities and high-risk communities about community relocation following disasters are not new. Nevertheless, there remains a limited understanding of factors affecting people's decisions about whether to relocate from a hazard zone, particularly in the Indonesian context. Through the experience of the Pelemsari community, a culturally distinct community near Mt. Merapi that once was located less than five km from the volcano crater, this article attempts to explain why the Pelemsari community differed from neighboring communities by abandoning its previous resistance to relocation after an unprecedented eruption in 2010. To explain this behavior change, the study used hermeneutic phenomenology, a methodology rooted in the people-place relationship and specifically used to unfold the meaning structures of a lived experience. Data were collected using semi-structured interviews, field observations, and document reviews. The results showed that people's strong place attachment affected residents' decision to uphold unity with their neighbors, select a relocation site that is outside the hazard zone but close to the former location, and engage in collective action that pressured the government to issue legal certificates of their former homes. These results show how a deep understanding of people's place attachment can make it possible to achieve a successful community relocation.

Keywords

Post-disaster displacement; Community relocation; Place attachment; Cultural attachment; Risk perception

Automated two-dimensional geometric model reconstruction from point cloud data for construction quality inspection and maintenance

Kim, Minju & Lee, Dongmin. (2023). Automated two-dimensional geometric model reconstruction from point cloud data for construction quality inspection and maintenance. Automation in Construction, 154. https://doi.org/10.1016/j.autcon.2023.105024.

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Abstract

Despite the availability of 3D digital models, 2D floor plans remain extensively used for quality inspection and maintenance as they offer firsthand information. While laser scanners enable efficient capture and reconstruction of real-world scenes, challenges arise in accurately extracting building geometry from laser scanning data due to the loss of geometric features. This paper describes a method for accurately reconstructing 2D geometric drawings of built facilities using laser scanning data. These techniques involve transforming the dimension of 3D data into 2D and displaying the registered data as pixels to extract solid lines that represent wall structures. By employing dimensionality transformation and pixelation techniques, the method supports reliable quality inspection and maintenance processes, overcoming the challenges of extracting precise geometry from laser scanning data. This paper contributes to the automated extraction of geometric features from point clouds and inspires the future development of fully automated 2D CAD and 3D BIM in alignment with Scan-to-BIM.

Applicability of Smart Construction Technology: Prioritization and Future Research Directions

Ahn, H., Lee, C., Kim, M., Kim, T., Lee, D., Kwon, W., & Cho, H. (2023). Applicability of smart construction technology: Prioritization and future research directions. Automation in Construction., 153. https://doi.org/10.1016%2Fj.autcon.2023.104953

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Abstract

The potential for facilitating faster, safer, and more sustainable construction processes through the adoption of smart construction technologies is widely recognized. However, the limited adoption of these technologies in construction projects highlights the significance of identifying the technological needs of major stakeholders and the prioritization of research and development investment. In this study, the quality function deployment technique is employed to extract and prioritize the required technologies (RTs) from various stakeholders, while a thematic literature review is conducted to identify challenges and future research directions. The findings improve the efficiency of resource allocation, allowing policymakers to strategically address pressing issues. This can facilitate collaboration and communication among researchers, stakeholders, and the wider community, fostering a shared vision and understanding of future research goals and outcome. Prioritizing smart construction technologies can enhance their applicability. The top nine of technologies were prioritized by using quality function deployment. Thematic review was conducted for each of the top nine technologies. The challenges and future research directions were presented by review.

Keywords

Fourth industrial revolution (4IR); Prioritization; Quality function deployment (QFD); Smart construction technologies; Technology innovation

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

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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

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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