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100 _aBarreira-González, Pablo
_945649
245 _aImplementation and calibration of a new irregular cellular automata-based model for local urban growth simulation: The MUGICA model
260 _bSage,
_c2019.
300 _aVol 46, Issue 2, 2019,(243-263 p.)
520 _aCellular automata-based models have traditionally employed regular grids to represent the geographical environment when simulating urban growth or land use change. Over the last two decades, the scientific community has introduced the use of other spatial structures in an attempt to represent the processes simulated by these models more realistically. Cadastre parcels are a good choice when simulating urban growth at local scales, where pixels or regular cells do not represent the geographic space properly. Furthermore, the implementation and calibration of key factors such as accessibility and suitability have not been sufficiently explored in models employing irregular structures. This paper presents a fully calibrated model to simulate urban growth: Model for Urban Growth simulation using Irregular Cellular Automata. The model uses the irregular structure of the cadastre and its smallest unit: the cadastral parcel. The factors included are based on the traditional Neighbourhood, Accessibility, Suitability and Zoning Status modelling schema, frequently employed in other models. Each factor was implemented and calibrated for the irregular structure employed by the model, and a new approach was explored to introduce a random component that would reproduce illegal growth. Several versions of Model for Urban Growth simulation using Irregular Cellular Automata were produced to calibrate the model within the period 2000–2010. The results obtained from the simulations were compared against observed growth for 2010, adapting the traditional confusion matrix to irregular space. A new metric is proposed, called growth simulation accuracy, which measures how well the model locates urban growth.
650 _aIrregular,
_945650
650 _acellular automata,
_945651
650 _a model calibration,
_945652
650 _aurban simulation,
_945653
650 _aurban growth
_945654
700 _aAguilera-Benavente, Francisco
_945655
700 _aGómez-Delgado, Montserrat
_935392
773 0 _011590
_915512
_dSage 2019.
_t Environment and Planning B: Urban Analytics and City Science
856 _uhttps://doi.org/10.1177/2399808317709280
942 _2ddc
_cART