A Theoretical Model of Road Development Dynamics

Ralston, Bruce A.; Barber, Gerald M.

doi:10.1111/j.1467-8306.1982.tb01819.x

Cited by 14 publications

(9 citation statements)

References 3 publications

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“…A destination is selected from candidate nodes as the one that maximizes the transport demands, flow, or speed, or minimizes the cost under given constraints, which is usually solved through linear programming [14,19]. The problem is formulated as seeking equilibrium between travel demands and supplies [19]. Typical approaches involve flow generation, spatial interaction, gravity model, or spatial choice of destinations.…”

Section: Individual Road Locationmentioning

confidence: 99%

“…Prediction of road location is defined as processes of determining nodes and links, namely the destination identification and route selection [3,4]. A destination is selected from candidate nodes as the one that maximizes the transport demands, flow, or speed, or minimizes the cost under given constraints, which is usually solved through linear programming [14,19]. The problem is formulated as seeking equilibrium between travel demands and supplies [19].…”

Section: Individual Road Locationmentioning

confidence: 99%

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The road extension model in the land change modeler for ecological sustainability of IDRISI

Jiang

2007

Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems

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Road development is an important proximate cause of deforestation and consequent biodiversity loss. The interaction between road extension and land use calls for an integration of road simulation into land change models to improve model performance. To date there have been few attempts to simulate road development to support land change modeling. The objective of this research is to develop a road extension model to simulate roads network expansion. This road extension model forecasts the location of individual roads at local scale and produces the given spatial pattern of road network at regional scale. Locating individual roads is divided into two consecutive steps, identifying endpoints and locati * ng routes. Spatial pattern is controlled through altering the local road growth process, specifically limiting the number and locations of endpoints. The road extension model was released in 2006 as a component of the Land Change Modeler for Ecological Sustainability in IDRISI 15.0 (the Andes Edition). The model was applied to simulate scenarios of different road placement strategies in lowland Bolivia. The model results showed that the simulated road network exhibited varying spatial arrangements under different pattern parameter settings. The result provides insights into the ecological consequence of human land use policies. It also calls for an empirical based pattern parameter specification to predict road expansion that maintains existing network patterns.

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Section: Individual Road Locationmentioning

confidence: 99%

Section: Individual Road Locationmentioning

confidence: 99%

The road extension model in the land change modeler for ecological sustainability of IDRISI

Jiang

2007

Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems

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“…Since the road will never extend beyond the margin of production (Ralston and Barber 1982), we can show that the total commodity supplied at the port in time period t + 1 will be 'For an extended description of the developmental model, see Ralston and Barber (1982).…”

Section: Fig 1 the Developmental Frameworkmentioning

confidence: 99%

“…3The astute reader will note that equation (1) does not hold if the road exceeds the margin of production. The existence of such a solution is nonoptimal (Ralston and Barber 1982).…”

Section: Fig 1 the Developmental Frameworkmentioning

confidence: 99%

Taxation and Optimal Road Penetration

Ralston

Barber

1984

Geographical Analysis

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Virtually without exception, geographic models of network investment and optimization have ignored the implications of the methods of taxation and finance used to generate new transport facilities. It is standard to cast these problems in a joint fixed and variable cost framework or to minimize variable cost, subject to an exogenously specified budget on fixed costs. To be sure, this simplistic view of financing arrangements in the transport sector can be defended on the basis that more serious deficiencies in these models are of greater concern-for example, the failure to account adequately for transport system economic interdependencies. However, since the taxation and financing arrangements themselves affect the spatial pattern of road impact, it seems timely to examine their implications in a dynamic geographical road model. We take a step in this direction by combining a quite simple geometric network representation with a fully dynamic economic model and an explicit taxation and road financing framework.Specifically, this paper concerns itself with a comparison of three different road financing schemes that could be used by an authority faced with the problem of defining the optimal road penetration schedule from a coastal port into its hinterland. The effects of road extension are captured in a fully dynamic, recursively structured, single-commodity market centered at the port. The three taxation schemes include:(1) a tax on incremental rent (partial land value capture), (2) a ton-mile or vehicle mile tax, and (3) a commodity sales tax. We consider each method as a means of financing road extension and show that each method gives rise to a different pattern of spatial development around the port, to a different level of benefits, and to a different equilibrium condition.The structure of the paper is straightforward. First, we outline the road development model and relate it functionally to the dynamics of the commodity market. Second, we identify the costs and benefits of road penetration and specify the general form of the road extension problem. Benefits are taken to be only those occurring to producers. Other possible benefits, such as agglomerative economies at the port, are ignored. Next, we describe the impacts of the three taxes and derive the revenues from each method. Then, the three taxation methods are embedded *Preliminary work on this topic was supported by the National Science Foundation Grant SES Bruce A. Ralston is associate professor of geography, University of Tennessee. Gerald M . 8105838.Barber is associate professor of geography, University of Victoria, British Columbia.

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“…For example, road development predictions are used to aid environmental impact assessments, producing likely scenarios of environmental change and associated impact estimations, such as predicting future biodiversity outcomes (Soares-Filho et al 2006;Alkemade et al 2009). However, as described, multiple factors influence road development, and potentially do so in complicated ways involving nonlinear feedbacks and interactions, time lags and stochasticity (Ralston & Barber 1982). This resulted in early road models that were focused on describing and explaining the spatiotemporal development of roads, highlighting the influence of geopolitics on road location (Andersen & Reis 1997;Carvalho et al 2002;Perz et al 2007), but lacking analytical or predictive elements.…”

Section: Introductionmentioning

confidence: 99%

Large scale spatio-temporal patterns of road development in the Amazon rainforest

2013

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SUMMARYThere is burgeoning interest in predicting road development because of the wide ranging important socioeconomic and environmental issues that roads present, including the close links between road development, deforestation and biodiversity loss. This is especially the case in developing nations, which are high in natural resources, where road development is rapid and often not centrally managed. Characterization of large scale spatio-temporal patterns in road network development has been greatly overlooked to date. This paper examines the spatiotemporal dynamics of road density across the Brazilian Amazon and assesses the relative contributions of local versus neighbourhood effects for temporal changes in road density at regional scales. To achieve this, a combination of statistical analyses and modeldata fusion techniques inspired by studies of spatiotemporal dynamics of populations in ecology and epidemiology were used. The emergent development may be approximated by local growth that is logistic through time and directional dispersal. The current rates and dominant direction of development may be inferred, by assuming that roads develop at a rate of 55 km per year. Large areas of the Amazon will be subject to extensive anthropogenic change should the observed patterns of road development continue.

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A Theoretical Model of Road Development Dynamics

Cited by 14 publications

References 3 publications

The road extension model in the land change modeler for ecological sustainability of IDRISI

The road extension model in the land change modeler for ecological sustainability of IDRISI

Taxation and Optimal Road Penetration

Large scale spatio-temporal patterns of road development in the Amazon rainforest

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