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Present study is aimed to compare the performance of SLEUTH model from two different calibration methods, that is, brute force and GA in term of computational efficiency of calibration processes, capturing urban growth, a form of growth or growth pattern and its spatial distribution. SLEUTH has been parameterized for Ajmer city (India) and its performance has been compared in term of eight parameters/methods, that is, computational efficiency, model fitness that is, OSM, urban shape index, best fit coefficient values, hit-miss-false alarm method, kappa statistics, accuracy percentage and visual analysis. GA-based calibration has been found to be computationally more efficient and relatively better in capturing urban growth and form of growth as compared to brute force. Brute force calibration seems to be slightly better considering urban hits as compared to GA, however, GA is better with respect to lesser false alarms. [ABSTRACT FROM AUTHOR]

Urban growth is a complex spatio-temporal phenomenon that includes built-up activities taking place both horizontally and vertically. The built-up land density in a city is a function of land desirability and suitability of a location in terms of the quality of the available public services, access to infrastructure, neighborhood type, vibrancy of socio-economic and cultural characteristics. The simulation of built-up land density may help planning and development authorities in making better land developmental decisions, making appropriate provisions for services, long term land use planning, and allocation of natural resources. In the recent past, various efforts have been made to assess built-up density in terms of the densification of built-up activities at the city scale in terms of floor space indices, building density, residential density (number of housing units per hectare) and urban volume. However, only limited research was reported on the simulation and prediction of spatially distributed built-up land density. In the present study, an algorithm is developed to simulate the spatial distribution of built-up land density as a function of a set of selected urbanization explanatory variables. Its application has been demonstrated using a newly developed version of the SLEUTH model (SLEUTH-Density) to simulating the built-up land density for Ajmer city in India. Development of SLEUTH-Density included designing a density algorithm, writing the programming code, integrating the code with the existing SLEUTH model, and testing the algorithm. The model results were validated indirectly using few built-up land density indices and directly through field verification, which were found to be in good agreement with the simulated built-up land density from SLEUTH-Density • Development of an algorithm and SLEUTH-Density version of SLEUTH for the estimation of spatial built-up land density. • The model application has been demonstrated for simulating the built-up land density for Ajmer city in India. • The model may be applied to other geographical locations and helpful in making land development decisions by the developmental agencies. [ABSTRACT FROM AUTHOR]

Land suitability is one of the important variables influencing urbanization and needs to be considered in urban growth simulation and modeling. The present study is aimed to introduce land suitability which is a function of a few important urbanization explanatory drivers into an urban growth model for realistic urban growth simulation. Development of SLEUTH-Suitability, an improved version of the SLEUTH urban growth model has been presented in which land suitability has been integrated as an additional urban growth decision variable. The model development includes land suitability assessment, Multi-Criteria Evaluation (MCE) based Analytical Hierarchy Process (AHP) framework and its integration in the urban growth simulation process of the existing SLEUTH model, writing programming code, and verification of SLEUTH-Suitability version. The performance of the SLEUTH-Suitability version has been quantified in terms of relative improvement in the best fit value of the Optimal SLEUTH Metric (OSM), spatial and statistical measures while simulating urban growth of Ajmer City in the Rajasthan state of India as compared to existing SLEUTH version. Both versions i.e., SLEUTH and SLEUTH-Suitability models were parameterized and calibrated using a required dataset of 05 years over a period of 18 years i.e., 1997, 2000, 2008, 2013, and 2015. Performance of the SLEUTH-Suitability has been found to be better in terms of improved calibration as indicated by better OSM values and improved capturing of different urban growth forms like fragmented and scattered growth. Furthermore, using the SLEUTH-Suitability, urban growth is forecasted up to the year 2040 in Ajmer city to understand the growth pattern. • Land suitability assessment considering important explanatory variables. • Development of land suitability model and integration with the existing SLEUTH urban growth model. • Programming, implementation, testing and verification of the newer version of SLEUTH i.e., SLEUTH-Suitability. • Performance evaluation of SLEUTH-Suitability. [ABSTRACT FROM AUTHOR]