Data Science & Spatial Analysis Archives - Page 7 of 8

Continuous Quality Improvement Techniques for Data Collection in Asset Management Systems

Migliaccio, G. C.; Bogus, Susan M.; Cordova-Alvidrez, A. A. (2014). Continuous Quality Improvement Techniques for Data Collection in Asset Management Systems. Journal Of Construction Engineering And Management, 140(4).

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Abstract

Transportation infrastructure assets are among the largest investments made by governmental agencies. These agencies use data on asset conditions to make decisions regarding the timing of maintenance activities, the type of treatment, and the resources to employ. To collect and record these data, agencies often utilize trained evaluators who assess the asset either on site or by analyzing photos and/or videos. These visual assessments are widely used to evaluate conditions of various assets, including pavement surface distresses. This paper describes a Data Quality Assessment & Improvement Framework (DQAIF) to measure and improve the performance of multiple evaluators of pavement distresses by controlling for subjective judgment by the individual evaluators. The DQAIF is based on a continuous quality improvement cyclic process that is based on the following main components: (1)assessment of the consistency over timeperformed using linear regression analysis; (2)assessment of the agreement between evaluatorsperformed using inter-rater agreement analysis; and (3)implementation of management practices to improve the results shown by the assessments. A large and comprehensive case study was employed to describe, refine, and validate the framework. When the DQAIF is applied to pavement distress data collected on site by different evaluators, the results show that it is an effective method for quickly identifying and solving data collection issues. The benefit of this framework is that the analyses employed produce performance measures during the data collection process, thus minimizing the risk of subjectivity and suggesting timely corrective actions. The DQAIF can be used as part of an asset management program, or in any engineering program in which the data collected are subjected to the judgment of the individuals performing the evaluation. The process could also be adapted for assessing performance of automated distress data acquisition systems.

Keywords

Asset Management; Civil Engineering Computing; Data Acquisition; Decision Making; Inspection; Maintenance Engineering; Quality Control; Regression Analysis; Roads; Transportation; Continuous Quality Improvement Techniques; Asset Management System; Governmental Agencies; Transportation Infrastructure Assets; Maintenance Activities; Visual Assessment; Pavement Surface Distresses; Data Quality Assessment & Improvement Framework; Dqaif; Linear Regression Analysis; Interrater Agreement Analysis; Data Collection Process; Automated Distress Data Acquisition System; Manual Pavement Distress; Pavement Management; Quantitative Analysis; Data Collection; Assets; Reliability; Case Studies

The Association between Park Facilities and Duration of Physical Activity During Active Park Visits

Stewart, Orion T.; Moudon, Anne Vernez; Littman, Alyson J.; Seto, Edmund; Saelens, Brian E. (2018). The Association between Park Facilities and Duration of Physical Activity During Active Park Visits. Journal Of Urban Health, 95(6), 869 – 880.

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Abstract

Public parks provide places for urban residents to obtain physical activity (PA), which is associated with numerous health benefits. Adding facilities to existing parks could be a cost-effective approach to increase the duration of PA that occurs during park visits. Using objectively measured PA and comprehensively measured park visit data among an urban community-dwelling sample of adults, we tested the association between the variety of park facilities that directly support PA and the duration of PA during park visits where any PA occurred. Cross-classified multilevel models were used to account for the clustering of park visits (n=1553) within individuals (n=372) and parks (n=233). Each additional different PA facility at a park was independently associated with a 6.8% longer duration of PA bouts that included light-intensity activity, and an 8.7% longer duration of moderate to vigorous PA time. Findings from this study are consistent with the hypothesis that more PA facilities increase the amount of PA that visitors obtain while already active at a park.

Keywords

Park Facilities; Physical Activity; Park Use; Recreation; Built Environment; Global Positioning System; Accelerometer; Gis; Gps; Accelerometer Data; United-states; Adults; Proximity; Features; Walking; Size; Attractiveness; Improvements; Environment; Parks & Recreation Areas; Parks; Luminous Intensity; Clustering; Urban Areas

Techniques for Continuous Improvement of Quality of Data Collection in Systems of Capital Infrastructure Management

Migliaccio, G. C.; Bogus, Susan M.; Cordova-Alvidrez, A. A. (2014). Techniques for Continuous Improvement of Quality of Data Collection in Systems of Capital Infrastructure Management. Journal Of Construction Engineering And Management, 140(4).

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Abstract

oLa infraestructura del transporte es una de las mas grandes inversiones que realizan los gobiernos. Las agencias gubernamentales de transporte administran este capital y utilizan la informacion de las condiciones de este para decidir la programacion y tipo de mantenimiento y recursos a ejercer. Para recolectar la informacion pertinente, las agencias emplean evaluadores adiestrados para evaluar la infraestructura, ya sea en sitio o analizando fotografias y/o videos. Las evaluaciones visuales son empleadas para inspeccionar las condiciones de la infraestructura, incluyendo el desgaste de la superficie de los caminos y carreteras. Este articulo describe un Data Quality Assessment & Improvement Framework (DQAIF) (Sistema de Evaluacion y Mejora de la Calidad de la Informacion) para medir y controlar los datos de los evaluadores del deterioro de carreteras, al controlar el criterio de estos. El DQAIF es en un proceso ciclico de Mejora Continua de Calidad compuesto por: a)la evaluacion del nivel de acuerdo entre evaluadores -por medio del analisis estadistico (inter-rater agreement analysis), b)la evaluacion de la consistencia a traves del tiempo -mediante analisis de regresion lineal, y c)la implementacion de practicas gerenciales para mejorar los resultados mostrados en las evaluaciones anteriores. Se llevo a cabo un estudio de caso para validar el sistema propuesto. Los resultados mostraron que el DQAIF es efectivo para identificar y resolver problemas de la calidad de los datos obtenidos en las inspecciones de infraestructura. Con este sistema se garantiza la reduccion del riesgo de la subjetividad y asi aplicar acciones de mantenimiento mas oportunas. El DQAIF puede ser empleado en un programa de gerencia de infraestructura o en cualquier programa de ingenieria en donde la informacion esta sujeta al juicio o criterio personal de los individuos que realizan la evaluacion. Este proceso puede ser adaptado, incluso, para evaluar el desempeno de sistemas automatizados de evaluacion de pavimentos.

Keywords

Manual Pavement Distress; Quality Control; Pavement Management; Inspection; Quantitative Analysis; Data Collection; Assets; Reliability; Construction Materials And Methods

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

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

College of Built Environments’ unique Inspire Fund aims to foster research momentum in underfunded pursuits college-wide. And it’s working.

Launching the Inspire Fund: An early step for CBE’s Office of Research “For a small college, CBE has a broad range of research paradigms, from history and arts, to social science and engineering.” — Carrie Sturts Dossick, Associate Dean of Research Upon taking on the role of Associate Dean of Research, Carrie Sturts Dossick, professor in the Department of Construction Management, undertook listening sessions to learn about the research needs of faculty, staff and students across the College of Built…

Julie Kriegh and collaborators launch studio booklet based on their work with Google

Julie Kriegh, researcher with the Carbon Leadership Forum and other CBE research centers, and owner of Kriegh Architecture Studios, collaborated with other CBE faculty and external partners to lead a UW CBE studio course in collaboration with Google that developed and delivered a design proposal for a sustainable data center. CBE collaborators included Hyun Woo “Chris” Lee, P.D. Koon Professorship in Construction Management; Jan Whittington, Associate Professor of the Department of Urban Design and Planning, and Director of the Urban…

Michael Tobey

Urban systems, system complexity, big data, artificial intelligence, smart cities, communities, and coupled human-built-environmental systems

Washington Center for Real Estate Research

Established in 1989 through two legislative programs, the WCRER compiles real estate sale transaction data, rental market statistics, and development metrics throughout the State of Washington. From this, the WCRER also develops affordable housing metrics for the state with data published in quarterly Washington State Housing Market Reports, a twice yearly Washington State Apartment Market Report, and the Washington Housing Market Data Toolkit. The WCRER also provides bespoke data driven research, educational outreach programs, and policy guidance to professional organizations consistent with its public service mandate.

The Washington Center for Real Estate Research (WCRER) was initially established by the Board of Regents at Washington State University (WSU) to provide a bridge between academic study and research on real estate topics and the professional real estate industries. It served that mission at WSU until merging with the Runstad Center at the beginning of 2012. WCRER works with faculty to ensure their rigorous research is accessible and easily usable by industry participants, the media and the general public, regardless of their statistical sophistication.

WCRER aims to provide credible research, value-added information, education services and project-oriented research to real estate licensees, real estate consumers, real estate service providers, institutional customers, public agencies, and communities in Washington state and the Pacific Northwest region.

The Washington Center for Real Estate Research is a key provider of real estate research and data across the State of Washington. The Center is primarily funded by the State, hence its central role in the provision of quality and robust data and market reports. Among its core activities are the Quarterly Washington State Housing Market Report and the semi-annual Apartment Market Survey for the State Department of Licensing.

The Center is active across a range of other research projects and works closely with stakeholders both across the University of Washington with the public and private sectors.

Urban Form Lab

The Urban Form Lab (UFL) research aims to affect policy and to support approaches to the design and planning of more livable environments. The UFL specializes in geospatial analyses of the built environment using multiple micro-scale data in Geographic Information Systems (GIS). Current research includes the development of novel GIS routines for performing spatial inventories and analyses of the built environment, and of spatially explicit sampling techniques. Projects address such topics as land monitoring, neighborhood and street design, active transportation, non-motorized transportation safety, physical activity, and access to food environments.

Research at the UFL has been supported by the U.S. and Washington State Departments of Transportation, the Centers for Disease Control and Prevention, the Robert Wood Johnson Foundation, the National Institutes of Health, and local agencies.

The Urban Form Lab is directed by Anne Vernez Moudon, Dr es Sc, a leading researcher and educator in quantifying the properties of the built environment as related to health and transportation behaviors. Philip M. Hurvitz, PhD, a veteran of geographic information science and data processing, leads data management and GIS work.

Catherine De Almeida

Trained as a landscape architect and building architect, Catherine’s research examines the materiality and performance of waste landscapes through exploratory methods in design research and practice. Her work has ranged in scale from large bio-cultural and sacred indigenous landscapes, to site design and architectural work, to furniture design and materials research. Through her design work, research, teaching and engagement, she explores ways of creating multiplicity within a single entity, space, building or site to form greater efficiencies and performative capabilities in design. Since 2014, Catherine has developed her design research—landscape lifecycles—as a holistic approach that synthesizes multiple programs, forming hybrid assemblages in the transformation of waste landscapes and materials. She uses landscape lifecycles as a framework for investigating the performance, visibility, citizenships, emotions and injustices of waste materials and landscapes.

For several years, she was a researcher for the Materials Collection at Harvard University, where she analyzed and developed new methods for the lifecycle assessment of materials used in built environments. This led to a passion for incorporating the lifecycles of materials and sites in the multi-scalar design of waste landscapes. She was awarded a Penny White Fellowship to research the lifecycle and use of geothermal energy in Iceland, which led to her graduate thesis, “Energy Afterlife: Choreographing the Geothermal Gradient of Reykjanes, Iceland,” and has been published and presented in various outlets. More recently, she was awarded several grants to continue her research in Iceland, focused on the Blue Lagoon and its waste reuse strategies. She continues to expand this research through documenting case studies of waste landscapes that have evolved from bottom-up processes, advancing landscape lifecycles as a critical lens for evaluating the landscape performance of existing sites that engage with waste reuse.

Before joining the Department of Landscape Architecture at UW, Catherine was an Assistant Professor of Landscape Architecture at the University of Nebraska-Lincoln, where she developed courses examining the multi-scalar implications of materiality and waste. Prior to this, Catherine was a lecturer at Cornell University where she taught undergraduate and graduate design studios focused on brownfield transformation. She was also an Associate at Whitham Planning and Design in Ithaca, New York where she worked as a landscape architect and planner on numerous urban infill projects, including the transformation of a deindustrialized Superfund site into a mixed-use district known as the Chain Works District.

Catherine received her MLA from Harvard University and her BARCH from Pratt Institute. She is a certified remote drone pilot, an Honorary Member of the Tau Sigma Delta Honor Society in Architecture and Allied Arts, and a Fellow of the Center for Great Plains Studies. Her work has been supported by numerous grants, and recognized in national and international publications and media outlets, including the Landscape Research Record, Journal of Landscape Architecture, and Journal of Architectural Education.