Tenneson, Karis; Patterson, Matthew S.; Mellin, Thomas; Nigrelli, Mark; Joria, Peter; Mitchell, Brent. (2018). Development of a Regional Lidar-Derived Above-Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA. Remote Sensing, 10(3).
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Abstract
Historical forest management practices in the southwestern US have left forests prone to high-severity, stand-replacement fires. Reducing the cost of forest-fire management and reintroducing fire to the landscape without negative impact depends on detailed knowledge of stand composition, in particular, above-ground biomass (AGB). Lidar-based modeling techniques provide opportunities to increase ability of managers to monitor AGB and other forest metrics at reduced cost. We developed a regional lidar-based statistical model to estimate AGB for Ponderosa pine and mixed conifer forest systems of the southwestern USA, using previously collected field data. Model selection was performed using Bayesian model averaging (BMA) to reduce researcher bias, fully explore the model space, and avoid overfitting. The selected model includes measures of canopy height, canopy density, and height distribution. The model selected with BMA explains 71% of the variability in field-estimates of AGB, and the RMSE of the two independent validation data sets are 23.25 and 32.82 Mg/ha. The regional model is structured in accordance with previously described local models, and performs equivalently to these smaller scale models. We have demonstrated the effectiveness of lidar for developing cost-effective, robust regional AGB models for monitoring and planning adaptively at the landscape scale.
Keywords
Laser Scanner Data; Landscape Restoration Program; Canopy Fuel Parameters; Discrete-return Lidar; Western United-states; Wave-form Lidar; Airborne Laser; Tropical Forest; Climate-change; Adaptive Management; Forest Biomass; Aboveground Biomass; Airborne Lidar; Monitoring; Regional Forest Inventory; Variable Selection; Bayesian Model Averaging; Multiple Linear Regression
Kim, Yong-Woo; Rhee, Byong-Duk. (2020). The Impact of Empowering Front-Line Managers on Planning Reliability and Project Schedule Performance. Journal Of Management In Engineering, 36(3).
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Abstract
This study applies empowerment theory to production planning at the level of frontline managers in a construction project. Using structural equation modeling, we investigate how empowering frontline managers impacts their planning performance. In contrast to prior studies, we find that although psychological empowerment of frontline managers has no direct effect on their production planning reliability or scheduling performance, it has an indirect effect on planning reliability and scheduling performance, as long as the organization supports the empowerment structurally during production planning. This implies that a project manager should provide frontline managers at the operational level with proper formal and informal authority over workflow development, shielding, and resource allocation when planning production in order to enhance job performance through psychological empowerment. This study contributes to the body of knowledge on construction management by exploring the impact of psychological and structural empowerment of frontline managers on their performance of production planning reliability and scheduling performance.
Keywords
Psychological Empowerment; Work; Model; Variables; System; Job; Planning Reliability; Production Planning; Scheduling Performance; Structural Empowerment; Structural Equation Modeling
Parsaee, Mojtaba; Demers, Claude M. H.; Potvin, Andre; Lalonde, Jean-Francois; Inanici, Mehlika; Hebert, Marc. (2021). Biophilic Photobiological Adaptive Envelopes for Sub-Arctic Buildings: Exploring Impacts of Window Sizes and Shading Panels’ Color, Reflectance, and Configuration. Solar Energy, 220, 802 – 827.
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Abstract
Northern building envelopes must provide efficient indoor-outdoor connections based on photobiologicalpsychological needs of occupants for positive relationships with the sub-Arctic nature, particularly daylighting and day/night cycles. Envelope configurations of Northern Canada's buildings have not yet considered such requirements. Potentials of adaptive systems are also still limited. This research develops a fundamental model of adaptive multi-skin envelopes for sub-Arctic buildings based on main biophilic and photobiological indicators which characterize efficient indoor-outdoor connections. Biophilic indicators characterize the state of connections among occupants and outdoors which could stimulate biological-psychological responses. Photobiological indicators determine human-centric lighting adaptation scenarios for hourly lighting qualities and sufficient darkness in relation to local day/night cycles and daylighting. Biophilic performance of the proposed envelope was evaluated through 18 numerical models in terms of impacts of window and shading sizes on occupants' field of views. Photobiological lighting performance was evaluated by experimental methods using 23 physical models at 1:10 scale. Surface characteristics of dynamic shading panels, including color, reflectance, orientation, and inclination, were studied for potential photobiological impacts in terms of melanopic/photopic ratios and color temperatures. Results show that the proposed envelope could (i) offer acceptable direct visual connections with the outdoor nature through efficient window sizes for biophilia, and (ii) modify daylighting qualities to address hourly/seasonal photobiological needs of sub-Arctic occupants. Challenges of the proposed envelope to implement under sub-Arctic climatic conditions are underlined especially in terms of energy issues. The research outcomes help architects and decision-makers to improve occupants' wellbeing and healthy buildings in subArctic climates.
Keywords
Window Shades; Building Envelopes; Reflectance; Color Temperature; Daylighting; Building-integrated Photovoltaic Systems; Daylight; Outdoor Living Spaces; Canada; Adaptive Envelope; Arctic Climate; Biophilic Design; Healthy Building; Photobiological Lighting; Light; Exposure; Stress; Design; Architecture; Sensitivity; Illuminance; Environment; Melatonin; Recovery; Surface Properties; Performance Evaluation; Indicators; Polar Environments; Lighting; Shading; Darkness; Decision Making; Envelopes; Configurations; Buildings; Color; Adaptive Systems; Climatic Conditions; Numerical Models; Mathematical Models; Panels; Night; Climate; Orientation; Arctic Region
My research interests focus on the contemporary problems of integrated architecture, engineering, and construction practices, particularly the communication processes and team workflows that support them. This work is at the intersection of AEC and the sociological and organizational theories that help identify and analyze the activities within professional practice collaboration. I am using qualitative studies to build theory and practice models for Lean Construction, sustainable design and construction, and integration across design, construction, and facility management. I am also working with technological constructs like BIM and COBie that form foundations for new kinds of collaboration.
I am a licensed architect, and have been a long-time educator in architecture and construction. I have taught design and construction studios, building detailing and assemblages, and architectural theory, and have been recognized institutionally and nationally for teaching excellence. My instructional research is focused on studio-based learning and design thinking.
The Cyber-BE Lab integrates the latest in academic research on policy, communication, and organization with industry expertise on IoT security, risk mitigation and building operations. Cyber-BE offers a holistic understanding of IoT in the built environment. We support the organizational, communication, and policy innovations that will help minimize IoT risk through:
- Advancing social scientific research to better understand and apply smart technology in the built environment
- Delivering usable guidance and tools to address the policy, organizational, and communication challenges that industry practitioners face
- Building a community of practice of IoT security practitioners and researchers
The lab leads include Laura Osburn, Senior Research Scientist at the Department of Construction Management, Jessica Beyer, Lecturer and Research Scientist at the Jackson School of International Studies, and Chuck Benson, Director of IoT Risk Mitigation Strategy at the University of Washington.
The Pacific Northwest Transportation Consortium (PacTrans) announced in January 2021 the project proposals selected for funding. Qing Shen, Professor of Urban Design and Planning and Chair of the Interdisciplinary PhD Program in Urban Design and Planning is among those selected for project funding. Shen is working alongside Co-Principal Investigator Catherine (Casey) Gifford–Innovative Mobility Senior Planner–on the applied research project titled “Supplementing fixed-route transit with dynamic shared mobility services: a marginal cost comparison approach”. The project goal is to address a…
Sensol Systems, a startup founded in 2020 by Janie Bube–a recent UW Masters of Landscape Architecture graduate–along with other students at University of Washington, was recently awarded a National Science Foundation (NSF) award to participate in the I-Corps program. This NSF program uses experiential education to help researchers gain valuable insight into entrepreneurship, starting a business or industry requirements and challenges. The curriculum integrates scientific inquiry and industrial discovery in an inclusive, data-driven culture driven by rigor, relevance, and evidence….
On February 9, Lever for Change announced that the College of Built Environment’s Carbon Leadership Forum (CLF) and four other finalist teams will advance to the next stage of the 2030 Climate Challenge, a $10 million award launched last year to reduce greenhouse gas emissions in the U.S. by 2030. The Challenge, sponsored by an anonymous donor, will fund proven, data-driven solutions tackling greenhouse gas emissions in the buildings, industry, and/or transportation sectors in communities across the country. Sixty-eight proposals…
Urban systems, system complexity, big data, artificial intelligence, smart cities, communities, and coupled human-built-environmental systems
Climate change, smart cities, urban economics and the interaction between human behavior and built environment