Prediction And Simulation Of Spatial Pattern For Urban Growth And Change In Land Use In Sana’a City, Yemen

In this study, Sana’a master plans were evaluated and analyzed to verify whether their implementations corresponded with the actual spatial urban development. The result shows that until the present time there is still lack of clear policy that controls and guides urban development. It also shows that about 40% of the growth occurred in unplanned areas, green areas and reserved land without suitable protection and regulations. GIS, remote sensing techniques and field survey were used to study the spatial pattern growth for the spontaneous areas in Sana’a city as well as the physical, socio-economic, and environmental conditions. There is no specific planning pattern was found in these settlements. Development has taken place randomly in unplanned areas, following the pattern of topography and concentrating along main roads. The study has successfully developed a model for locating suitable land for urban development in Sana’a by integrating GIS and Multi-criteria Analysis and Cellular Automata methods. The potential suitable lands were generated and the validation of the model was done by overlaying the generated suitability map on the potential land for residential development proposed by 1999 Sana’a master plan. The result shows the areas for future development proposed by the master plan corresponded well with the high to very high suitability zones except for illegal areas. The prediction and simulation of the urban growth and land use change were done successfully in GIS-based CA model which output “managed growth scenario”. Based on the land suitability assessment produced by the model, the demand for land for urban development during the period from 2004 to 2020 was then estimated using statistical tools. Then, the candidature of a cell by adopting again MCA method was evaluated. It provides dynamic transition rule for land use conversion at each time step of the simulation model based on the following factors used: land suitability, proximity to existing developed areas, proximity to prioritized land, and current land use. Variable calculation produces land use conversion probabilities for each cell. The rules are updated at each time step in order to reflect the land dynamics of the previous step. The result was validated through the process of running the model for the period from 1994 to 2003. The result gives an overall accuracy of 99.6%, producer’s accuracy of 83.3% and the user’s accuracy of 83.6%. In this study the SLEUTH model was also used to predict the urban growth and land use change. It was calibrated using 35-year time series dataset compiled from interpreted historical topographical maps, aerial photographs and satellite imageries for the entire study area to identify the parameters that influenced the urban growth in Sana’a city. Results from the calibration modes- coarse, fine, and final represented the top five scorings from thousands of iterations. The composite results of the optimum values for the diffusion, spread, slope and road gravity parameters show successive improvements in the parameters that control the behavior of the system. In the mechanism of self-modification rules, parameters averaging on the best results from the final calibration were used. The prediction mode of the SLEUTH model uses the best fit growth rule parameters from the calibration to begin the process of ‘‘growing’’ urban settlements, starting at the most recent urban data layer. The resulting forecast of future urban growth outputs a probability map where individual grid cells are being urbanized at some future date, assuming the same unique ‘‘urban growth signature’’ is still in effect as it was in the past. The final results of the model are annual layers map of future urban growth and land use change (2004–2020). Based on the analysis the comparison between GIS-based CA model and SLEUTH model carried out and the strong and weak points of them were highlighted. This study benefits decision makers and planners in carrying out future urban growth planning and it gives them the opportunity to know the advantages and consequences for each growth scenario in order to promote the continuity and sustainability of urban development in the Sana’a city.

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