Titlebook: Geomatic Approaches for Modeling Land Change Scenarios; María Teresa Camacho Olmedo,Martin Paegelow,Franci Book 2018 Springer Internationa

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https://doi.org/10.1007/978-3-658-35059-8best results across all of the statistics. Furthermore, direct conversion from the original vector map to raster format at the desired cell size was found to give better results than resampling to the desired cell size from a different cell size. We also tested the effect of changing spatial resolut

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Empirische Analyse digitaler Ungleichheiten, are applied in order to study trends in land use change. Three scenarios are designed: a baseline or trend scenario, an economic crisis scenario and a green scenario. The CLUE model (based on logistic regression) is used. LCM (based on neural networks) is also used but only in the trend scenario. B

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Geomatic Approaches for Modeling Land Change Scenarios. An Introduction,d seems to be overtaking it as the generally used term for this phenomenon. The objective of this book is also clear to see from the methods we have chosen and the subjects we address. This book deals first and foremost with spatially explicit data that can be mapped. However, its additional focus o

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Techniques for the Validation of LUCC Modeling Outputse hard-classified simulation maps, while ROC is used to test soft-classified maps. We then look at a second validation approach based on LUCC dynamics such as LUCC components, intensity analysis, data uncertainty and the impact of spatial and temporal scales. Finally, we compare a group of the most

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LUCC Scenarios scenarios of various kinds, including those on land-use cover change (LUCC) studied in this book. Such is the current popularity of scenario techniques in terms of the number of applications and users that the relevant literature reveals a wide array of different and often contradictory definitions

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Impact and Integration of Multiple Training Dates for Markov Based Land Change Modelingch is weighted according to time distance from the present in order to fix expected total change in the simulation step and at the category level. We then produce alternatives to Markov chains at a transitional level. In this way we integrate all available LUCC-budgets and propose different methods

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