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

Abstract

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.

Emerging Opportunities for Landscape Ecological Modelling

“…A number of highly focussed artificial landscape generators have been developed, which simulate a specific process to replicate real-world patterns. 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].…”

Modeling spatial decisions with graph theory: logging roads and forest fragmentation in the Brazilian Amazon

“…In pursuing this interest, the article presents a computational approach that simulates road network formation by translating the economic behavior of loggers into spatial outcomes. The simulation of road networks has often focused on the minimization of road building costs (e.g., Tomlin 1990, Soares-Filho et al 2004, Jiang 2007. Arima et al (2005Arima et al ( , 2008 build on this literature for the Amazonian case by addressing harvest revenues in addition to costs.…”

“…Although simulation results are interpreted in light of a formal statement of the behavior of an economic agent, namely the logger, the computational approach is not ''agent-based'' as the modeling community has come to understand the term (Parker et al 2003). Nor does it rely strictly on the identification of least-cost pathways, a functionality available in current GIS software (Tomlin 1990, Jiang 2007. Rather, the software builds on classical optimization algorithms in operations research designed to identify networks that achieve explicit goals, like profit maximization (Merry et al 2009).…”

Communicating sustainability: Sustainability and communication in the engineering, science, and technical communication classrooms

“…Sustainability science and collaboration efforts are built on information technologies. Improved environmental impact modeling methods, say, lead to better decisions on topics like land use incursions [7]. Regional information systems are needed to help guide development projects in a larger context [8].…”