A dynamic modeling approach to simulating socioeconomic effects on landscape changes

摘要: Abstract Modeling and simulating the effects of human factors on landscape change remain as challenges for ecological studies. In this paper, we present a dynamic simulation (DLS) approach to elucidate human-induced changes 5104 km2 study area within Chicago metropolitan region. The DLS consists an urban growth submodel land-cover submodel. This simulates land-use expansion by incorporating socioeconomic demographic data predicts in result expansion. A utility function spatial choice methodology construction that were developed execute process. approach, with adjustment transition structures (i.e. potentials, threshold rate), overcomes shortcomings static statistical models use constant probability modeling. It also allows selected economic principles be integrated into simulation. study, historical census applied derive thresholds rates land cover changes. Comparison 1997 maps derived classification Landsat Thematic Mapper (TM) remotely sensed indicated 62.3% overall agreement was achieved among changed areas. Landscape simulations from 2020 at 5 year time interval prepared. results depicted trends large setting area.