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The State of Illinois is examining prospects to increase the development of in-state renewable energy resources on public lands. In response, this research develops a scalable decision-support tool for identifying suitable areas for solar energy generation in the state. This paper provides guidance for state agency-driven solar development by evaluating the suitability of potential generation areas in terms of environmental impact, socioeconomic costs, and energy productivity, and providing a forum for critical decision-making. More specifically, geospatial technologies are combined with a suitability analysis to reveal the potential for solar energy generation on public lands. This study demonstrates the usefulness of the resulting information for supporting both regional and local decision-making as a Planning Support System (PSS). Our analysis suggests that the large-scale analysis using fine resolution data is useful for comparison and site-specific decision making - with site verification protocols in terms of physical implementation. We find that planning decisions for solar development should use a fine-grained suitability approach at a large scale and a feasibility analysis at a specific scale. We present our findings in statewide application along with a scalable PSS tool to optimize and support solar decision-making process and democratize the information for engaging a broader audience.
YoonShin Kwak; Brian Deal; Tom Heavisides. A large scale multi criteria suitability analysis for identifying solar development potential: A decision support approach for the state of Illinois, USA. Renewable Energy 2021, 177, 554 -567.
AMA StyleYoonShin Kwak, Brian Deal, Tom Heavisides. A large scale multi criteria suitability analysis for identifying solar development potential: A decision support approach for the state of Illinois, USA. Renewable Energy. 2021; 177 ():554-567.
Chicago/Turabian StyleYoonShin Kwak; Brian Deal; Tom Heavisides. 2021. "A large scale multi criteria suitability analysis for identifying solar development potential: A decision support approach for the state of Illinois, USA." Renewable Energy 177, no. : 554-567.
Given that evolving urban systems require ever more sophisticated and creative solutions to deal with uncertainty, designing for resilience in contemporary landscape architecture represents a cross-disciplinary endeavor. While there is a breadth of research on landscape resilience within the academy, the findings of this research are seldom making their way into physical practice. There are existent gaps between the objective, scientific method of scientists and the more intuitive qualitative language of designers and practitioners. The purpose of this paper is to help bridge these gaps and ultimately support an endemic process for more resilient landscape design creation. This paper proposes a framework that integrates analytic research (i.e., modeling and examination) and design creation (i.e., place-making) using processes that incorporate feedback to help adaptively achieve resilient design solutions. Concepts of Geodesign and Planning Support Systems (PSSs) are adapted as part of the framework to emphasize the importance of modeling, assessment, and quantification as part of processes for generating information useful to designers. This paper tests the suggested framework by conducting a pilot study using a coupled sociohydrological model. The relationships between runoff and associated design factors are examined. Questions on how analytic outcomes can be translated into information for landscape design are addressed along with some ideas on how key variables in the model can be translated into useful design information. The framework and pilot study support the notion that the creation of resilient communities would be greatly enhanced by having a navigable bridge between science and practice.
YoonShin Kwak; Brian Deal; Grant Mosey. Landscape Design toward Urban Resilience: Bridging Science and Physical Design Coupling Sociohydrological Modeling and Design Process. Sustainability 2021, 13, 4666 .
AMA StyleYoonShin Kwak, Brian Deal, Grant Mosey. Landscape Design toward Urban Resilience: Bridging Science and Physical Design Coupling Sociohydrological Modeling and Design Process. Sustainability. 2021; 13 (9):4666.
Chicago/Turabian StyleYoonShin Kwak; Brian Deal; Grant Mosey. 2021. "Landscape Design toward Urban Resilience: Bridging Science and Physical Design Coupling Sociohydrological Modeling and Design Process." Sustainability 13, no. 9: 4666.
The United States faces twin crises of housing affordability and environmental degradation. Under these clouds, the nation is experiencing an explosive growth in new construction multi-family housing. This paper seeks to evaluate how designers might optimize the organization of such projects to minimize cost and maximize environmental performance. A method is developed for evaluating the construction costs and environmental performance of multifamily developments across four variables: building height, number of buildings, building width, and building floor area. Our analysis suggests that buildings with deeper floor plates are preferable for both economic and environmental reasons. We also suggest that taller buildings have more performative envelopes while shorter buildings are more economical to construct. Finally, we offer a method of finding a compromise between economic and environmental objectives for projects of a given square footage. Most commonly, this “compromise” takes the form of a moderate number of mid-rise buildings with deep floor plates. This investigation adds nuance to the existing literature on the effects of building shape on building cost and envelope performance. It also provides designers with a method of potentially constructing multifamily buildings in a less expensive and more environmentally conscious way.
Grant Mosey; Brian Deal. Optimizing Multi-Family Building Massing for Affordability and Envelope Performance: An Investigation of the Trade-Offs Implicit in Low Rise Residential Buildings. Buildings 2021, 11, 99 .
AMA StyleGrant Mosey, Brian Deal. Optimizing Multi-Family Building Massing for Affordability and Envelope Performance: An Investigation of the Trade-Offs Implicit in Low Rise Residential Buildings. Buildings. 2021; 11 (3):99.
Chicago/Turabian StyleGrant Mosey; Brian Deal. 2021. "Optimizing Multi-Family Building Massing for Affordability and Envelope Performance: An Investigation of the Trade-Offs Implicit in Low Rise Residential Buildings." Buildings 11, no. 3: 99.
Green spaces have a significant effect on urban living environments, providing shared natural areas and entertainment spaces among other benefits. Investigating their popularity and functionality is valuable for supporting green space design and guiding land use development around public green spaces. Conventional methods used to extract use and functionality information on public green spaces have typically relied on questionnaires and in-site observations, both resource and time consuming processes. These approaches can also be context dependent and produce less transferable data across regions. This study utilizes deep machine learning techniques to mine social media text and image data to produce useful information on public green space popularity, activities, functionality and design. Convolutional neural networks (CNN), an advanced machine learning technique, is used to analyze large scale data sets (Yelp and publicly accessible images) of public green spaces in Chicago, Illinois, US. The coupling of the two types of data enables the extraction of a rich and comprehensive analytical frame for understanding how green spaces are used and how they might be improved. The technique also utilizes a complex transfer learning process to pretrain the model and allow its quick adaptation to other regions around the world. The process will be replicated in Stockholm, Sweden. We use the analysis generated to compare open spaces in the 2 cities. The process has the potential to substantially improve nature based strategies on green space development and design.
Si Chen; Brian Deal. Using Deep Machine Learning to Understand Green Space Popularity, Activities, Functionality, and Design Implications: a comparison of Chicago and Stockholm. 2021, 1 .
AMA StyleSi Chen, Brian Deal. Using Deep Machine Learning to Understand Green Space Popularity, Activities, Functionality, and Design Implications: a comparison of Chicago and Stockholm. . 2021; ():1.
Chicago/Turabian StyleSi Chen; Brian Deal. 2021. "Using Deep Machine Learning to Understand Green Space Popularity, Activities, Functionality, and Design Implications: a comparison of Chicago and Stockholm." , no. : 1.
Planning support systems (PSSs) should generally be designed to promote the participation of stakeholders in planning and design processes through the delivery of useful, localized information, an ability to collect feedback, and an ability to model and test various ‘what-if’ scenarios. This paper focuses on such a PSS tool. The tool integrates the Land-use Evolution and Assessment Model (LEAM) with a Regional Economic Input-Output Model (REIM) in a tightly coupled computational process made accessible to stakeholders through a web-based PSS. The integrated tool allows for users to easily navigate the models and test land use and economic scenarios without expert assistance. It also keeps simulations updated with dynamic inputs and engages users in PSS development and application through responsive feedback to enhance plan-making abilities. In this paper, we demonstrate an application of the LEAM-REIM PSS in Sangamon County, Illinois. The application demonstrates an ability to provide more efficacious and detailed land use estimations through the connection of economic and land-use models, allowing users to easily engage with, navigate, and respond to scenario tests. We discuss the PSS tool, model integration approach, and detailed application to assess its usefulness in urban planning and design. We also propose some opportunities for further research.
Si Chen; YoonShin Kwak; Le Zhang; Grant Mosey; Brian Deal. Tightly Coupling Input Output Economics with Spatio-Temporal Land Use in a Dynamic Planning Support System Framework. Land 2021, 10, 78 .
AMA StyleSi Chen, YoonShin Kwak, Le Zhang, Grant Mosey, Brian Deal. Tightly Coupling Input Output Economics with Spatio-Temporal Land Use in a Dynamic Planning Support System Framework. Land. 2021; 10 (1):78.
Chicago/Turabian StyleSi Chen; YoonShin Kwak; Le Zhang; Grant Mosey; Brian Deal. 2021. "Tightly Coupling Input Output Economics with Spatio-Temporal Land Use in a Dynamic Planning Support System Framework." Land 10, no. 1: 78.
This paper explores the promise of genetic algorithms as a tool for optimization of buildings at a neighborhood scale across the conflicting demands of social, environmental, and economic sustainability. A large urban site in Chicago, Illinois, is selected to test the viability of using a multi criteria genetic algorithm to optimize the potential building mix in a newly planned development. Two variables, the number of buildings of a given use-type and their height, are analyzed against cost functions for social, economic, and environmental objectives. Single-objective algorithms are utilized to optimize the variables individually. A non-dominated genetic sorting algorithm (NGSAII) is then utilized to identify the Pareto-optimal solutions considering the three objectives simultaneously. Single-objective results are found to vary substantially by objective, with different variable values for social, economic, and environmental sustainability. For multi-objective algorithms, the results support Campbell’s notion of the three nodes of sustainability being in conflict. Solutions performing well across economic and environmental objectives were most common. Solutions performing well among environmental and social objectives were less common. Solutions performing well across economic and social performance were rare. This suggests that while economic and environmental conflicts are to some degree resolvable, conflicts between social and either of economic or environmental performance are more difficult to resolve. The failure of any solution to perform well across all three objectives lends credence to the idea of design as a series of trade-offs and that one super optimum solution may not exist. The process provides insights into the trade-offs implicit in the building design and development process and raises questions regarding the balancing of competing sustainability objectives.
Grant Mosey; Brian Deal. Multivariate Optimization in Large-Scale Building Problems: An Architectural and Urban Design Approach for Balancing Social, Environmental, and Economic Sustainability. Sustainability 2020, 12, 10052 .
AMA StyleGrant Mosey, Brian Deal. Multivariate Optimization in Large-Scale Building Problems: An Architectural and Urban Design Approach for Balancing Social, Environmental, and Economic Sustainability. Sustainability. 2020; 12 (23):10052.
Chicago/Turabian StyleGrant Mosey; Brian Deal. 2020. "Multivariate Optimization in Large-Scale Building Problems: An Architectural and Urban Design Approach for Balancing Social, Environmental, and Economic Sustainability." Sustainability 12, no. 23: 10052.
Adapting successes of policy transition from one city to another has been more difficult than single case of successful sustainability-driven projects and developments. A thorough understanding of local biophysical and socio-economic conditions is essential in formulating effective development plans and policies. Here, we propose the use of a social-ecological model as a comparative tool to help understand these critical components in order to inform sustainability-driven strategic interventions and best practice learning. We use the cities of Chicago and Stockholm as our comparison cases, and explore the spatial relationships between development patterns and accessibility attractors such as employment, transportation, and recreational opportunities. Potential environmental impacts are evaluated for comparison using ecosystem service value and Normalized Difference Vegetation Index (NDVI). The results indicate that although each city exhibits distinctive patterns of development, there are commonalities to build on for potential adaption strategies. For example, to mitigate the high ecosystem service and NDVI losses of Chicago from urban development, what can be learned from Stockholm are: 1) promoting infill for future residential development; and 2) stronger restrictions on both commercial and residential developments on buffer zones of valuable ecosystem services, especially waterways. These findings help us to understand the driving forces of different patterns of urban growth and to give suggestions on city-specific sustainability policies.
Le Zhang; Cong Cong; Haozhi Pan; Zipan Cai; Vladimir Cvetkovic; Brian Deal. Socioecological informed comparative modeling to promote sustainable urban policy transitions: Case study in Chicago and Stockholm. Journal of Cleaner Production 2020, 281, 125050 .
AMA StyleLe Zhang, Cong Cong, Haozhi Pan, Zipan Cai, Vladimir Cvetkovic, Brian Deal. Socioecological informed comparative modeling to promote sustainable urban policy transitions: Case study in Chicago and Stockholm. Journal of Cleaner Production. 2020; 281 ():125050.
Chicago/Turabian StyleLe Zhang; Cong Cong; Haozhi Pan; Zipan Cai; Vladimir Cvetkovic; Brian Deal. 2020. "Socioecological informed comparative modeling to promote sustainable urban policy transitions: Case study in Chicago and Stockholm." Journal of Cleaner Production 281, no. : 125050.
Green Stormwater Infrastructure (GSI) is being implemented in cities around the globe. Although we know that GSI improves urban ecosystems in a variety of ways, we know little about the extent to which the characteristics of GSI impact human perception and preference. This gap in knowledge necessitates a greater understanding of the relationship between GSI perceptions and preference. Without this knowledge, designers and planners risk creating landscapes that people dislike, and from which they reap few health benefits. To address this gap, we deployed four sets of similar questionnaires globally in Amazon Turk. Each had 54 urban street photographs from US cities with varying levels of tree and bioretention planting density that were photomanipulated from six original images. In three questionnaires, participants rated how natural, safe, or messy they perceived the landscapes to be on a five-point Likert scale. The other questionnaire asked participants to rate their preference for each image. The researchers then examined the relationships between vegetation density, perceptions, and preference (n = 427). The results demonstrate that vegetation density levels significantly influenced people’s preference, perceived safety, and perceived naturalness. Furthermore, perceived safety and naturalness strongly correlated with preference while the three landscape characteristics predicted preference. These findings can be used to improve the design of urban GSI and help people reap the benefits of nature. Future studies should investigate the effects of seasons, the influences of cues of care, and international applications.
Pongsakorn Suppakittpaisarn; Chun-Yen Chang; Brian Deal; Linda Larsen; William C. Sullivan. Does vegetation density and perceptions predict green stormwater infrastructure preference? Urban Forestry & Urban Greening 2020, 55, 126842 .
AMA StylePongsakorn Suppakittpaisarn, Chun-Yen Chang, Brian Deal, Linda Larsen, William C. Sullivan. Does vegetation density and perceptions predict green stormwater infrastructure preference? Urban Forestry & Urban Greening. 2020; 55 ():126842.
Chicago/Turabian StylePongsakorn Suppakittpaisarn; Chun-Yen Chang; Brian Deal; Linda Larsen; William C. Sullivan. 2020. "Does vegetation density and perceptions predict green stormwater infrastructure preference?" Urban Forestry & Urban Greening 55, no. : 126842.
UHI is an important measure for understanding the urban landscape, especially in terms of thermal agglomeration and disturbance. This research aims to discern the success of sustainability planning by examining and comparing the different characteristics of UHIs through the combination of machine learning and statistical methods. To achieve this, we analyze 4 new towns in Korea, which include two ‘old’ new towns and two ‘recent’ new towns. The key difference between our test towns lies on whether or not the sustainability policies were applied to their development plans. We visualize LST and conduct a k-mean clustering to find and quantify spatial patterning in the resulting UHI measures. We then compare the statistical relations between LST and 6 UHI driven variables across the towns. Using comparative analysis, this research reveals that sustainable development policies have a notable effect on the patterns and intensities of UHI. Urban structures, planned under development policies, including green and blue space ratios, road networks, and housing distributions, were found to affect UHI significantly. We quantifiably confirm that the sustainability policies implemented in planning the ‘recent’ new towns allow the towns to experience less aggravated UHIs than the ‘old’ new towns. However, we also claim a need to develop appropriate, long-term UHI management regulations for the ‘recent’ new towns. This paper provides a solid basis for improving Korean new town planning and managing the environmental issues in urban systems for planners, designers, and decision-makers to establish the sustainable built environment.
YoonShin Kwak; Chan Park; Brian Deal. Discerning the success of sustainable planning: A comparative analysis of urban heat island dynamics in Korean new towns. Sustainable Cities and Society 2020, 61, 102341 .
AMA StyleYoonShin Kwak, Chan Park, Brian Deal. Discerning the success of sustainable planning: A comparative analysis of urban heat island dynamics in Korean new towns. Sustainable Cities and Society. 2020; 61 ():102341.
Chicago/Turabian StyleYoonShin Kwak; Chan Park; Brian Deal. 2020. "Discerning the success of sustainable planning: A comparative analysis of urban heat island dynamics in Korean new towns." Sustainable Cities and Society 61, no. : 102341.
The preservation of open spaces is treated as an important policy in recent years as urbanization level is increasing higher in the world (Geoghegan, 2002). There are multiple positive effects associated with open spaces, including recreation, aesthetic and environment values (Geoghegan, 2002). The positive effects of open space as a nature-based solution on urban social, economic and environmental factors have been explored by a number of previous papers, such as housing price (Lutzenhiser & Netusil, 2001; Bolitzer & Netusil, 2000), spatial pattern (Lewis et al., 2009; Irwin & Bockstael, 2004), human health (Groenewegen et al., 2006; Irvine et al., 2013) and social safety (Groenewegen et al., 2006; Fischer et al., 2004). However, relatively less papers have predicted the open spaces’ influences on socio-economic development. This paper will firstly verify the open space influences on economic factor (housing sale prices) and social factor (sense of safety, residential agglomeration) using a linear regression model. We consider the housing attributes, urban form attributes (eg. population density, block size, road density), driving and walking accessibility to different types of public open spaces, and accessibility to other amenities (eg. hospitals and schools) as influential features. Then, we test several machine learning algorithms in predicting the housing price and sense of safety change based on future open space planning scenarios, and choose the most suitable machine learning algorithm. City of Chicago, Illinois, US is chosen to be study area since data availability, sufficient open space types and long-term open space preservation strategies. This study can quantify the values of the open spaces in influencing socio-economic developments and provide a way to test the open space scenarios. It has potential to work as a tool for local planners to make better nature-based solutions in open space designs and plans.
Si Chen; Zipan Cai; Brian Deal. Test the Effectiveness of the Open Spaces Scenario in Promoting Socio-economic Development. 2020, 1 .
AMA StyleSi Chen, Zipan Cai, Brian Deal. Test the Effectiveness of the Open Spaces Scenario in Promoting Socio-economic Development. . 2020; ():1.
Chicago/Turabian StyleSi Chen; Zipan Cai; Brian Deal. 2020. "Test the Effectiveness of the Open Spaces Scenario in Promoting Socio-economic Development." , no. : 1.
Human-induced urban growth and sprawl have implications for greenhouse gas (GHG) emissions that may not be included in conventional GHG accounting methods. Improved understanding of this issue requires use of interactive, spatial-explicit social–ecological systems modeling. This paper develops a comprehensive approach to modeling GHG emissions from urban developments, considering Stockholm County, Sweden as a case study. GHG projections to 2040 with a social–ecological system model yield overall greater emissions than simple extrapolations in official climate action planning. The most pronounced difference in emissions (39% higher) from energy use single-residence buildings resulting from urban sprawl. And this difference is not accounted for in the simple extrapolations. Scenario results indicate that a zoning policy, restricting urban development in certain areas, can mitigate 72% of the total emission effects of the model-projected urban sprawl. The study outcomes include a decision support interface for communicating results and policy implications with policymakers.
Haozhi Pan; Jessica Page; Le Zhang; Cong Cong; Carla Ferreira; Elisie Jonsson; Helena Näsström; Georgia Destouni; Brian Deal; Zahra Kalantari. Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region. Ambio 2019, 49, 1313 -1327.
AMA StyleHaozhi Pan, Jessica Page, Le Zhang, Cong Cong, Carla Ferreira, Elisie Jonsson, Helena Näsström, Georgia Destouni, Brian Deal, Zahra Kalantari. Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region. Ambio. 2019; 49 (7):1313-1327.
Chicago/Turabian StyleHaozhi Pan; Jessica Page; Le Zhang; Cong Cong; Carla Ferreira; Elisie Jonsson; Helena Näsström; Georgia Destouni; Brian Deal; Zahra Kalantari. 2019. "Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region." Ambio 49, no. 7: 1313-1327.
We present a comparative socio-ecological modeling approach to identify possible improvement opportunities for Climate Action Plans (CAPs), focusing on two cities, Chicago and Stockholm. The aim is to provide a tool for capturing and addressing deep-rooted behavioral and institutional preferences that may aggravate greenhouse gas (GHG) emissions in cities. Socio-economic activities, land use change, and future urban forms are considered and forecast to the year 2040 on 30m × 30m spatial grids. GHG emissions associated with these urban development aspects are calculated and compared between the cities. Innovative policy instruments for growth control and zoning (GCZ) are simulated and tested through the socio-ecological model, to determine their effectiveness when added to other interventions included in the CAPs. Our findings show that behavioral/institutional preference for sprawl, its low-density form, and resultant carbon sink losses are main factors driving current and future residential and transportation GHG emissions in Chicago. GCZ policies are shown to counteract and mitigate around 20% of these factors in the form of future GHG emissions.
Haozhi Pan; Jessica Page; Le Zhang; Si Chen; Cong Cong; Georgia Destouni; Zahra Kalantari; Brian Deal. Using comparative socio-ecological modeling to support Climate Action Planning (CAP). Journal of Cleaner Production 2019, 232, 30 -42.
AMA StyleHaozhi Pan, Jessica Page, Le Zhang, Si Chen, Cong Cong, Georgia Destouni, Zahra Kalantari, Brian Deal. Using comparative socio-ecological modeling to support Climate Action Planning (CAP). Journal of Cleaner Production. 2019; 232 ():30-42.
Chicago/Turabian StyleHaozhi Pan; Jessica Page; Le Zhang; Si Chen; Cong Cong; Georgia Destouni; Zahra Kalantari; Brian Deal. 2019. "Using comparative socio-ecological modeling to support Climate Action Planning (CAP)." Journal of Cleaner Production 232, no. : 30-42.
Advances in energy systems for the valorization of the aqueous byproduct generated from the hydrothermal processing of biomass: a perspective and review of the recent progress.
Yexuan Gu; Xuesong Zhang; Brian Deal; Lujia Han; Jilu Zheng; Haoxi Ben. Advances in energy systems for valorization of aqueous byproducts generated from hydrothermal processing of biomass and systems thinking. Green Chemistry 2019, 21, 2518 -2543.
AMA StyleYexuan Gu, Xuesong Zhang, Brian Deal, Lujia Han, Jilu Zheng, Haoxi Ben. Advances in energy systems for valorization of aqueous byproducts generated from hydrothermal processing of biomass and systems thinking. Green Chemistry. 2019; 21 (10):2518-2543.
Chicago/Turabian StyleYexuan Gu; Xuesong Zhang; Brian Deal; Lujia Han; Jilu Zheng; Haoxi Ben. 2019. "Advances in energy systems for valorization of aqueous byproducts generated from hydrothermal processing of biomass and systems thinking." Green Chemistry 21, no. 10: 2518-2543.
Scholars from a variety of disciplines have been working to unravel the complexities of geodesign as an approach to tackling a host of problems. We argue that a mature understanding of geodesign requires a systemic perspective to organize the interconnections between ecological, social and economic conditions at multiple spatial and temporal scales. We reviewed definitions and perspectives of geodesign and key concepts of ecological systems thinking to develop a new framework for landscape architecture. We provide the state-of-the-art in geodesign within the context of systems thinking and coupled human-environmental resilience. We show that geodesign is capable to encourage public participation and interdisciplinary collaboration through its systemic planning processes and synergetic technologies. The thrust of geodesign-related research is the emerging paradigm of landscape-based sustainability. While landscape architecture is complex in many aspects, the integrated framework promotes our understanding about its social-ecological potential, spatial-temporal association and resilience of coupled human-environment systems. Based on the findings, we outline key contributions, implications, challenges and recommendations for future research.
Yexuan Gu; Brian Deal; Linda Larsen. Geodesign Processes and Ecological Systems Thinking in a Coupled Human-Environment Context: An Integrated Framework for Landscape Architecture. Sustainability 2018, 10, 3306 .
AMA StyleYexuan Gu, Brian Deal, Linda Larsen. Geodesign Processes and Ecological Systems Thinking in a Coupled Human-Environment Context: An Integrated Framework for Landscape Architecture. Sustainability. 2018; 10 (9):3306.
Chicago/Turabian StyleYexuan Gu; Brian Deal; Linda Larsen. 2018. "Geodesign Processes and Ecological Systems Thinking in a Coupled Human-Environment Context: An Integrated Framework for Landscape Architecture." Sustainability 10, no. 9: 3306.
This paper argues that a systems thinking and explicit modeling approach is needed to address noted weaknesses (in terms of practicality and usefulness) in Integrated Water Resource Management. A process of coupling complex regional land‐use, economy, and water system interactions in integrated modeling is demonstrated with proof‐of‐concept applications to two urban cases (Chicago and Stockholm). In this uniquely coupled systems model, urban land‐use scenarios are considered a complex urban system represented by dynamic systems models of land use, economics, and water with a focus on urban environments that includes drivers and system feedbacks with implications focused on urban water systems. The integrated model results reveal that the physical availability of land for economic activities (forecasted via a bottom‐up land‐use change model) and their locations differ sharply from top‐down sectoral based economic forecasts. This shows that both human systems (economic and land‐use planning) and natural systems (land‐use limitations and associated water implications) need to be considered in order to accurately account for system (s) impacts. For example, flood‐zone regulations divert land‐use to other locations, while land‐cover changes can greatly affect the water infiltration characteristics of land surfaces and thereby alter hydrological outcomes. Our results indicate that modeling social and natural processes using a systems approach can provide a more comprehensive understanding of coupled causal mechanisms, impacts and feedbacks in applications of Integrated Water Resource Management.
Haozhi Pan; Brian Deal; Georgia Destouni; Yalei Zhang; Zahra Kalantari. Sociohydrology modeling for complex urban environments in support of integrated land and water resource management practices. Land Degradation & Development 2018, 29, 3639 -3652.
AMA StyleHaozhi Pan, Brian Deal, Georgia Destouni, Yalei Zhang, Zahra Kalantari. Sociohydrology modeling for complex urban environments in support of integrated land and water resource management practices. Land Degradation & Development. 2018; 29 (10):3639-3652.
Chicago/Turabian StyleHaozhi Pan; Brian Deal; Georgia Destouni; Yalei Zhang; Zahra Kalantari. 2018. "Sociohydrology modeling for complex urban environments in support of integrated land and water resource management practices." Land Degradation & Development 29, no. 10: 3639-3652.
Distance to the CBD and neighboring commercial employment (land-use) have been the core determinants of spatial-related production externalities for firms. In these models, travel time to work (firms) is the single most important factor for residential land-use allocation. New theories of complex urban systems (CUS), however, have begun to cast some doubt on the efficacy of the “distance to CBD” model. There is some evidence for example, that large urban systems might evolve with scale-free transportation networks. In this paper, we examine urban land-use data from the Chicago Metropolitan Statistical Area (MSA) to argue for a theoretical shift from a “distance to CBD” based prototype to one that considers the complexity inherent in urban systems structure. We use a Stochastic Greedy Algorithm to quantify connectivity and attractions to every land cell (30 × 30 m) to existing population and employment centers, Points of Interests (POIs), and highway and major roads. We measure the frequency of commercial and resident land-uses relative to these found attraction levels and develop algorithms that help explain the relations. Using these methods, we find that both CBD-driven and network-driven approaches are empirically valid for explaining current urban structures. We also find, however, that these relations change when temporal variables are considered. For example, we found that the land-use change in Chicago from 2001 to 2011 is an obvious deviation from the “distance to CBD” based urban growth assumption. Our results suggest that we should re-examine the core urban structure assumptions of spatial equilibrium models.
Haozhi Pan; Brian Deal; Yan Chen; Geoffrey Hewings. A Reassessment of urban structure and land-use patterns: distance to CBD or network-based? — Evidence from Chicago. Regional Science and Urban Economics 2018, 70, 215 -228.
AMA StyleHaozhi Pan, Brian Deal, Yan Chen, Geoffrey Hewings. A Reassessment of urban structure and land-use patterns: distance to CBD or network-based? — Evidence from Chicago. Regional Science and Urban Economics. 2018; 70 ():215-228.
Chicago/Turabian StyleHaozhi Pan; Brian Deal; Yan Chen; Geoffrey Hewings. 2018. "A Reassessment of urban structure and land-use patterns: distance to CBD or network-based? — Evidence from Chicago." Regional Science and Urban Economics 70, no. : 215-228.
A growing body of literature has explored the psychological benefits associated with contact with nature. Many studies have employed experimental designs that compared various levels of nature exposure, or have used exogenous neighborhood-based measures of nature. The exact places where adolescents visit, as well as their street-level experiences with nature, remain unexplored. As a result, we know very little about the extent to which adolescents' actual exposure to nature is related to their moods. In this study, we examined the daily activities and moods of 155 adolescents from central Illinois to understand the association between exposure to varying concentrations of nature and adolescents' mood. Each participant wore a Global Positioning System (GPS) device for four consecutive days and completed an adapted Profile of Mood States questionnaire at the end of each day. We calculated the concentration of nature participants were exposed to by assessing the Google Street View images at the locations they visited throughout each day. Multi-level modeling analysis revealed significant associations between the concentration of nature and daily mood in participating adolescents, even after controlling for intra-individual and inter-individual level confounding variables. This relationship did not vary by demographic or socio-economic background. We discuss the implications for greening urban public space and resurrecting time for adolescents to engage in unstructured activities. The methods used in this study—combining GPS tracking and environmental exposure assessment—can be applied to a variety of research studies regarding human-landscape relationships.
Dongying Li; Brian Deal; Xiaolu Zhou; Marcus Slavenas; William C. Sullivan. Moving beyond the neighborhood: Daily exposure to nature and adolescents’ mood. Landscape and Urban Planning 2018, 173, 33 -43.
AMA StyleDongying Li, Brian Deal, Xiaolu Zhou, Marcus Slavenas, William C. Sullivan. Moving beyond the neighborhood: Daily exposure to nature and adolescents’ mood. Landscape and Urban Planning. 2018; 173 ():33-43.
Chicago/Turabian StyleDongying Li; Brian Deal; Xiaolu Zhou; Marcus Slavenas; William C. Sullivan. 2018. "Moving beyond the neighborhood: Daily exposure to nature and adolescents’ mood." Landscape and Urban Planning 173, no. : 33-43.
Brian Deal; Haozhi Pan; Youshan Zhuang. Modeling Land-Use Change in Complex Urban Environments. Comprehensive Geographic Information Systems 2018, 401 -423.
AMA StyleBrian Deal, Haozhi Pan, Youshan Zhuang. Modeling Land-Use Change in Complex Urban Environments. Comprehensive Geographic Information Systems. 2018; ():401-423.
Chicago/Turabian StyleBrian Deal; Haozhi Pan; Youshan Zhuang. 2018. "Modeling Land-Use Change in Complex Urban Environments." Comprehensive Geographic Information Systems , no. : 401-423.
Brian Deal; Aaron Petri; Haozhi Pan; Stephanie Timm. Big data, socio-environmental resilience and urban systems planning support. Big Data for Regional Science 2017, 164 -175.
AMA StyleBrian Deal, Aaron Petri, Haozhi Pan, Stephanie Timm. Big data, socio-environmental resilience and urban systems planning support. Big Data for Regional Science. 2017; ():164-175.
Chicago/Turabian StyleBrian Deal; Aaron Petri; Haozhi Pan; Stephanie Timm. 2017. "Big data, socio-environmental resilience and urban systems planning support." Big Data for Regional Science , no. : 164-175.
Brian Deal; Haozhi Pan; Stephanie Timm; Varkki Pallathucheril. The role of multidirectional temporal analysis in scenario planning exercises and Planning Support Systems. Computers, Environment and Urban Systems 2017, 64, 91 -102.
AMA StyleBrian Deal, Haozhi Pan, Stephanie Timm, Varkki Pallathucheril. The role of multidirectional temporal analysis in scenario planning exercises and Planning Support Systems. Computers, Environment and Urban Systems. 2017; 64 ():91-102.
Chicago/Turabian StyleBrian Deal; Haozhi Pan; Stephanie Timm; Varkki Pallathucheril. 2017. "The role of multidirectional temporal analysis in scenario planning exercises and Planning Support Systems." Computers, Environment and Urban Systems 64, no. : 91-102.