Titlebook: Land Use Cover Datasets and Validation Tools; Validation Practices David García-álvarez,María Teresa Camacho Olmedo,J Book‘‘‘‘‘‘‘‘ 2022 The

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Land Use Cover Mapping, Modelling and Validation. A Backgroundng and the uncertainty and validation of LUC and LUCC data and model outputs. The chapter summarizes the theoretical fundamentals required to understand the rest of the book. First, we define Land Use and Land Cover concepts that have been extensively discussed and debated in the literature (Sect.?.

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Validation of Land Use Cover Maps: A Guidelinese Cover Change Modelling (LUCCM) exercises. We give readers some guidelines according to the type of maps they want to validate: single LUC maps (Sect.?.), time series of LUC maps (Sect.?.) or the results of LUCCM exercises (Sect.?.). Despite the fact that some of the available methods are applicab

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Sample Data for Thematic Accuracy Assessment in QGIShere maps are validated by comparison with other maps with better resolution and/or quality, this approach requires a ground sample dataset, i.e. a set of sites where LUC can be observed in the field or interpreted from high-resolution imagery. Map error is assessed using techniques based on statist

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Basic and Multiple-Resolution Cross-Tabulation to Validate Land Use Cover Mapss (Sect.?.) is usually the first step in the validation of Land Use Cover (LUC) data. It compares two datasets to observe their spatial relationship, i.e. their degree of spatial (dis)agreement. Results are usually displayed in the form of maps, tables and other statistical measures. Multiple-Resolu

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