UPlan: A Versatile Urban Growth Model for Transportation Planning

Johnston, Robert A.; Shabazian, David; Gao, Shengyi

doi:10.3141/1831-23

Cited by 54 publications

(46 citation statements)

References 11 publications

(15 reference statements)

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“…Many of these are concerned with human impacts on landscape, for example models of road development [127], and of the conversion of forests to arable land by the processes of road and field creation [30]. A substantial focus of modelling of this kind has been on urban growth [128][129][130]. Equivalent approaches are taken to discrete processes in natural systems.…”

Section: Integrated Modelsmentioning

confidence: 99%

Emerging Opportunities for Landscape Ecological Modelling

Synes

Brown

Watts

et al. 2016

Curr Landscape Ecol Rep

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Landscape ecological modelling provides a vital means for understanding the interactions between geographical, climatic, and socio-economic drivers of land-use and the dynamics of ecological systems. This growing field is playing an increasing role in informing landscape spatial planning and management. Here, we review the key modelling approaches that are used in landscape modelling and in ecological modelling. We identify an emerging theme of increasingly detailed representation of process in both landscape and ecological modelling, with complementary suites of modelling approaches ranging from correlative, through aggregated process based approaches to models with much greater structural realism that often represent behaviours at the level of agents or individuals. We provide examples of the considerable progress that has been made at the intersection of landscape modelling and ecological modelling, while also highlighting that the majority of this work has to date exploited a relatively small number of the possible combinations of model types from each discipline. We use this review to identify key gaps in existing landscape ecological modelling effort and highlight emerging opportunities, in particular for future work to progress in novel directions by combining classes of landscape models and ecological models that have rarely been used together.

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Section: Integrated Modelsmentioning

confidence: 99%

Emerging Opportunities for Landscape Ecological Modelling

Synes

Brown

Watts

et al. 2016

Curr Landscape Ecol Rep

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“…Mobile emissions within the SJV were calculated using a modeling system composed of a GIS-based land-use model (UPlan), a four-step travel demand model (specified in TPþ/Viper), and a new mobile emissions inventory model (UCDrive-MOBILE). UPlan is a rule-based urban growth model that allocates future land use using a set of rules that spatially allocate population increases given among other factors, local land-use plans, existing city footprints, and existing/planned transportation routes (Johnston et al,, 2003). Four-step travel demand models were obtained for all 8 counties within the SJV.…”

Section: Base-case 2030 Emissionsmentioning

confidence: 99%

Influence of regional development policies and clean technology adoption on future air pollution exposure

Hixson

Mahmud

et al. 2010

Atmospheric Environment

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a b s t r a c tFuture air pollution emissions in the year 2030 were estimated for the San Joaquin Valley (SJV) in central California using a combined system of land use, mobile, off-road, stationary, area, and biogenic emissions models. Four scenarios were developed that use different assumptions about the density of development and level of investment in transportation infrastructure to accommodate the expected doubling of the SJV population in the next 20 years. Scenario 1 reflects current land-use patterns and infrastructure while scenario 2 encouraged compact urban footprints including redevelopment of existing urban centers and investments in transit. Scenario 3 allowed sprawling development in the SJV with reduced population density in existing urban centers and construction of all planned freeways. Scenario 4 followed currently adopted land use and transportation plans for the SJV. The air quality resulting from these urban development scenarios was evaluated using meteorology from a winter stagnation event that occurred on December 15th, 2000 to January 7th 2001. Predicted base-case PM2.5 mass concentrations within the region exceeded 35 mg m À3 over the 22-day episode. Compact growth reduced the PM2.5 concentrations by w1 mg m À3 relative to the base-case over most of the SJV with the exception of increases (w1 mg m À3 ) in urban centers driven by increased concentrations of elemental carbon (EC) and organic carbon (OC).Low-density development increased the PM2.5 concentrations by 1e4 mg m À3 over most of the region, with decreases (0.5e2 mg m À3 ) around urban areas. Population-weighted average PM2.5 concentrations were very similar for all development scenarios ranging between 16 and 17.4 mg m À3 . Exposure to primary PM components such as EC and OC increased 10e15% for high density development scenarios and decreased by 11e19% for low-density scenarios. Patterns for secondary PM components such as nitrate and ammonium ion were almost exactly reversed, with a 10% increase under low-density development and a 5% decrease under high density development. The increased human exposure to primary pollutants such as EC and OC could be predicted using a simplified analysis of population-weighted primary emissions. Regional planning agencies should develop thresholds of population-weighted primary emissions exposure to guide the development of growth plans. This metric will allow them to actively reduce the potential negative impacts of compact growth while preserving the benefits.

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“…At LUHA's request, we modeled selected urban growth scenarios defined by the working group to provide a multicounty visualization of the spatial urban footprints resulting from seven broad land use policies. We used UPlan (Johnston, Shabazian, & Gao, 2003), a rule-based, spatially explicit urban growth model, to develop the urban growth projections, then assessed the outputs in terms of their relative costs for service provision and impacts on agricultural production.…”

Section: Study Location: San Joaquin Valleymentioning

confidence: 99%

“…Varying GIS-based approaches have been used to project future land use, including expert panels, statistical projections, rule-based models, and economically driven models (Johnston et al, 2003). Expert panel modeling relies on experts' experience and assumes that the panel is able to accurately predict growth patterns.…”

Section: Spatial Modeling Of Growth Footprintsmentioning

confidence: 99%

Modeling Impacts to Agricultural Revenue and Government Service Costs from Urban Growth

Roth

Thorne

Johnston

et al. 2012

JAFSCD

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Urban expansion in rural areas may impact agricultural revenues and the burden of service provision on local governments. Spatially explicit urban growth models shed light on the consequences of such land use decisions. The San Joaquin Valley, an important agricultural region of California, will double in population by 2050. Using this region as an example, we modeled the spatial patterns of urban growth under seven policy scenarios and calculated potential loss of annual agricultural revenue from each. We also measured the distance from existing urban areas to new development in order to develop scenario-specific indicators of the cost to local governments for providing urban services such as sewer, water, roads, police and fire protection.As with all modeling exercises, an understanding of the strengths and weaknesses of the model being applied is essential for interpretation.

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UPlan: A Versatile Urban Growth Model for Transportation Planning

Cited by 54 publications

References 11 publications

Emerging Opportunities for Landscape Ecological Modelling

Emerging Opportunities for Landscape Ecological Modelling

Influence of regional development policies and clean technology adoption on future air pollution exposure

Modeling Impacts to Agricultural Revenue and Government Service Costs from Urban Growth

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