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Predicting the expansion of an urban boundary using spatial logistic regression and hybrid raster–vector routines with remote sensing and GIS, Taylor & Francis makes every effort to ensure the accuracy of all the information (the " Content ") contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no(More)
Urbanization has increased heat in the urban environment, with many consequences for human health and well-being. Managing climate change in part through increasing vegetation is desired by many cities to mitigate current and future heat related issues. However, little information is available on what influences the current effectiveness and availability of(More)
Automatic and interactive data analysis is instrumental in making use of increasing amounts of complex data. Owing to novel sensor modalities, analysis of data generated in professional team sport leagues such as soccer, baseball, and basketball has recently become of concern, with potentially high commercial and research interest. The analysis of team ball(More)
SUMMARY The vagueness of multi criteria decision making (MCDM) is commonly handled through fuzzy sets theory, by assigning degree of membership. However, the spatial MCDM (SMCDM) problem encounters ambiguity in assigning the membership function to fuzzy pairwise comparisons, which is referred to as non-specificity.This paper attempts to reach a new method(More)
Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial(More)