29 research outputs found

    Advancing PSS with complex urban systems sciences and scalable spatio-temporal models

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    Planning Support System (PSS) with a core of dynamic spatio-temporal model has been developed as analytical and information tools to aid and inform urban planning processes. However, scholarly communities identify that PSS has yet been popularized in planning practices, and not fully capable of meeting the challenge of understanding complex urban environments. I am dedicated to investigate and break through the bottlenecks of PSS with my experiences with University of Illinois Landuse Evolution and Impact Assessment Model (LEAM) PSS, which exemplify a PSS that that aid the process of collaboratively building spatio-temporal scenario models and transferring the knowledge to planning practitioners. I explore the future applications of PSS including Smart Cities, sentience, resilience, and environmental planning processes and their role in improving PSS usefulness in the practice of planning. PSS improvements will be presented in terms of multi-directional spatio-temporal processes and scenario planning. Moreover, I will address the process of transferring knowledge to users on model validity and ‘goodness-of-fit’ in real world planning applications. Beyond the traditional theoretical framework of PSS, the emerging Complex Urban System Sciences (CUS) challenge the core assumptions of spatial models of PSS, and pose opportunities for updating current PSS approaches into scalable spatio-temporal model that adheres to CUS principles. I will analyze this potential infusion by examining next generation PSSs within a framework of current CUS theories and advancement in statistical and computational methods. Case studies involved in my dissertation include LEAM PSS’ applications in McHenry County (IL), Peoria (IL), Chicago (IL), and St. Louis (MO). The final part of this dissertation highlights my contributions to the existing CUS theories. I will demonstrates how evidence from empirical applications can contribute to CUS theory itself. I will show how CUS can challenge the core assumptions of “distance to CBD” models that economists use to characterize urban structure and land-use

    Remotely-sensed imagery vs. eye-level photography: Evaluating associations among measurements of tree cover density

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    AbstractThe easy availability and widespread use of remotely-sensed imagery, especially Google Earth satellite imagery, makes it simple for urban forestry professionals to assess a site and measure tree cover density without visiting the site. Remotely-sensed tree cover density has become the dominant criterion for urban forestry regulations in many countries, but it is unclear how much such measures match the eye-level tree cover density that people experience; or the information gained through site visits, eye-level photography, or from consulting with citizens. To address this uncertainty, we assessed associations among two remotely-sensed and three eye-level tree cover density measures for 140 community street sites across the Midwestern United States with low, medium, or high tree cover coverage by using linear regression analysis. We found significant associations among the two remotely-sensed measures and the three eye-level measures across the three levels of tree cover. The associations between any pair of remotely-sensed and eye-level measures, however, diminish dramatically as canopy cover increased. At high levels of canopy cover, all associations between the remotely-sensed measures and the eye-level measures became statistically insignificant. These findings suggest that measures from remotely-sensed imagery fail to represent the amount of tree cover people perceive at eye-level when canopy cover is medium or high at the site scale. Therefore, the current urban forestry planning regulations, which rely heavily on remotely-sensed tree cover density measurements, need to be revised. We suggest strategic spots where eye-level measures of tree cover density should be emphasized

    The global biogeography of tree leaf form and habit

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    Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

    The global biogeography of tree leaf form and habit.

    Get PDF
    Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

    The global biogeography of tree leaf form and habit

    Get PDF
    Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17–34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

    The global biogeography of tree leaf form and habit

    Get PDF
    Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cyclin

    Discerning and Addressing Environmental Failures in Policy Scenarios Using Planning Support System (PSS) Technologies

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    The environmental consequences of planning decisions are often undervalued. This can result from a number of potential causes: (a) there might be a lack of adequate information to correctly assess environmental consequences; (b) stakeholders might discount the spatial and temporal impacts; (c) a failure to understand the dynamic interactions between socio-ecological systems including secondary and tertiary response mechanisms; or (d) the gravity of the status quo, i.e., blindly following a traditional discourse. In this paper, we argue that a Planning Support System (PSS) that enhances an assessment of environmental impacts and is integral to a community or regional planning process can help reveal the true environmental implications of scenario planning decisions, and thus improve communal planning and decision-making. We demonstrate our ideas through our experiences developing and deploying one such PSS—the Land-use Evolution and impact Assessment Model (LEAM) Planning Support System. University of Illinois researchers have worked directly with government planning officials and community stakeholders to analyze alternate future development scenarios and improve the planning process through a participatory, iterative process of visioning, model tuning, simulation, and discussion. The resulting information enables an evaluation of alternative policy or investment choices and their potential environmental implications that can change the way communities both generate and use plans
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