Urban expansion simulation and scenario prediction using cellular automata: comparison between individual and multiple influencing factors

Future urban growth scenarios and ecosystem services valuation in the Tepic-Xalisco Metropolitan area, Mexico

Currently, there is a need to establish new territorial planning instruments focused on sustainable development. The simulation of spatial scenarios is an essential tool to evaluate different alternatives for urban planning. The objective of this work was to explore future urban growth through the analysis of landscape patterns and the economic quantification of ecosystem services of three prospective scenarios, simulated towards the horizon year 2045. Each scenario was formulated, based on the application of different socioeconomic, political and environmental development strategies whose actions have a direct impact on land-use changes. The starting point was an urban growth simulation model, based on Cellular Automata with Markov Chains (CA-Markov), developed from previous work for the study area. Three scenarios were constructed with the intention of showing the spatial characteristics of three different alternatives of the evolution of future urban growth and through them, quantify the economic value and the consequences that would occur in the territory due to the effect of the different decisions taken. Landscape metrics were applied to detect the spatial processes and patterns of urban growth for each of the simulated scenarios and, finally, the costs of ecosystem services associated with the loss or gain of territory (that each of the different land covers and land uses would contribute) were quantified. The three simulated scenarios revealed that the Tepic-Xalisco Metropolitan Zone (MZ) will be in a process of urban coalescence in the next 30 years; and that the path designed to move towards an Industrialisation Scenario (ES2-IN) estimates economic losses of more than $31 million dollars per year for the ecosystem services associated particularly with the reduction of forest cover.

Scenario simulation of land use and land cover change in mining area

In this study, we selected 11 townships with severe ground subsidence located in Weishan County as the study area. Based on the interpretation data of Landsat images, the Binary logistic regression model was used to explore the relationship between land use and land cover (LULC) change and the related 7 driving factors at a resolution of 60 m. Using the CLUE-S model, combined with Markov model, the simulation of LULC under three scenarios-namely, natural development scenario, ecological protection scenario and farmland protection scenario-were explored. Firstly, using LULC map in 2005 as input data, we predicted the land use spatial distribution pattern in 2016. By comparing the actual LULC map in 2016 with the simulated map in 2016, the prediction accuracy was evaluated based on the Kappa index. Then, after validation, the spatial distribution pattern of LULC in 2025 under the three scenarios was simulated. The results showed the following: (1) The driving factors had satisfactory explanatory power for LULC changes. The Kappa index was 0.82, which indicated good simulation accuracy of the CLUE-S model. (2) Under the three scenarios, the area of other agricultural land and water body showed an increasing trend; while the area of farmland, urban and rural construction land, subsided land with water accumulation, and tidal wetland showed a decreasing trend, and the area of urban and rural construction land and tidal wetland decreased the fastest. (3) Under the ecological protection scenario, the farmland decreased faster than the other two scenarios, and most of the farmland was converted to ecological land such as garden land and water body. Under the farmland protection scenario, the area of tidal wetland decreased the fastest, followed by urban and rural construction land. We anticipate that our study results will provide useful information for decision-makers and planners to take appropriate land management measures in the mining area.