How often do we need to calibrate the models? Revalidation of the MOLAND model calibrated for the Greater Dublin Region (original) (raw)
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The MOLAND Model Calibration and Validation for the Greater Dublin Region
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The MOLAND model calibration and validation for greater Dublin region
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Calibrating land-use change models requires a time-series of reliable and consistent land-use maps, which are often not available. Medium resolution satellite images have a temporal and spatial resolution that is ideally suited for model calibration, and could therefore be an important information source to improve the performance of land-use change models. In this research, a calibration framework based on remote sensing data is proposed for the MOLAND model. Structural land-use information was first inferred from the available medium resolution satellite images by applying supervised classification at the level of predefined regions using metrics that describe the distribution of sub-pixel estimations of artificial sealed surfaces. The resulting maps were compared to the model output with a selected set of spatial metrics. Based on this comparison, the model was recalibrated according to five scenario's. While the selected metrics generally demonstrated a low sensitivity to changes in model parameters, some improvement was nevertheless noted for one particular scenario.
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Impacts of Spatial Extend and Site Location on Calibration of Urban Growth Models
During the last decades, cities in sub-saharan Africa have undergone rapid urban growth due to increased population growth and high economic activities. This research explores the impacts of varying modelling settings including spatial extend and its location for the city of Nairobi using a cellular automata (CA) urban growth model (UGM). Our UGM used multi-temporal satellite-based data for classification of urban land-use of 1986, 2000 and 2010, road data, slope data and exclusion layer. Monte-Carlo technique was used for model calibration and Multi Resolution Validation (MRV) technique for validation. Simulation of urban land-use was done up to the year 2030 when Kenya plans to attain Vision 2030. Three spatial grid sizes varying in extent and location were applied in the UGM calibration and validation. Thus, this research explored the impacts of varying spatial extent (grid) and location on urban growth modelling and hence can contribute to an improved sustainable planning and development. This is useful for future planning as the Nairobi grows and expands into the peri-urban areas.