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Validation of land use cover maps : a guideline

Tipo de material: Capítulo de libro
 en línea Capítulo de libro en línea Idioma: Inglés Tipo de contenido:
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Tema(s) en español: Tema(s) en inglés: Recurso en línea: En: Land use cover datasets and validation tools : validation practices with QGIS [Libro electrónico] / David García-Álvarez, María Teresa Camacho Olmedo, Martin Paegelow, Jean François Mas, editors páginas 35–46Nota de acceso: Acceso en línea sin restricciones Resumen:
Inglés

This chapter offers a general overview of the available tools and strategies for validating Land Use Cover (LUC) data—specifically LUC maps—and Land Use Cover Change Modelling (LUCCM) exercises. We give readers some guidelines according to the type of maps they want to validate: single LUC maps (Sect. 3), time series of LUC maps (Sect. 4) or the results of LUCCM exercises (Sect. 5). Despite the fact that some of the available methods are applicable to all these maps, each type of validation exercise has its own particularities which must be taken into account. Each section of this chapter starts with a brief introduction about the specific type of maps (single, time series or modelling exercises) and the reference data needed to validate them. We also present the validation methods/functions and the corresponding exercises developed in Part III of this book. To this end, we address, in this order, the tools for validating Land Use Cover data based on basic and Multiple-Resolution Cross-Tabulation (see chapter “Basic and Multiple-Resolution Cross Tabulation to Validate Land Use Cover Maps”), metrics based on the Cross-Tabulation matrix (see chapter “Metrics Based on a Cross-Tabulation Matrix to Validate Land Use Cover Maps”), Pontius Jr. methods based on the Cross-Tabulation matrix (see chapter “Pontius Jr. Methods Based on a Cross-Tabulation Matrix to Validate Land Use Cover Maps”), validation practices with soft maps produced by Land Use Cover models (see chapter “Validation of Soft Maps Produced by a Land Use Cover Change Model”), spatial metrics (see chapter “Spatial Metrics to Validate Land Use Cover Maps”), advanced pattern analysis (see chapter “Advanced Pattern Analysis to Validate Land Use Cover Maps”) and geographically weighted methods (see chapter “Geographically Weighted Methods to Validate Land Use Cover Maps”).

Número de sistema: 62673
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Acceso en línea sin restricciones

This chapter offers a general overview of the available tools and strategies for validating Land Use Cover (LUC) data—specifically LUC maps—and Land Use Cover Change Modelling (LUCCM) exercises. We give readers some guidelines according to the type of maps they want to validate: single LUC maps (Sect. 3), time series of LUC maps (Sect. 4) or the results of LUCCM exercises (Sect. 5). Despite the fact that some of the available methods are applicable to all these maps, each type of validation exercise has its own particularities which must be taken into account. Each section of this chapter starts with a brief introduction about the specific type of maps (single, time series or modelling exercises) and the reference data needed to validate them. We also present the validation methods/functions and the corresponding exercises developed in Part III of this book. To this end, we address, in this order, the tools for validating Land Use Cover data based on basic and Multiple-Resolution Cross-Tabulation (see chapter “Basic and Multiple-Resolution Cross Tabulation to Validate Land Use Cover Maps”), metrics based on the Cross-Tabulation matrix (see chapter “Metrics Based on a Cross-Tabulation Matrix to Validate Land Use Cover Maps”), Pontius Jr. methods based on the Cross-Tabulation matrix (see chapter “Pontius Jr. Methods Based on a Cross-Tabulation Matrix to Validate Land Use Cover Maps”), validation practices with soft maps produced by Land Use Cover models (see chapter “Validation of Soft Maps Produced by a Land Use Cover Change Model”), spatial metrics (see chapter “Spatial Metrics to Validate Land Use Cover Maps”), advanced pattern analysis (see chapter “Advanced Pattern Analysis to Validate Land Use Cover Maps”) and geographically weighted methods (see chapter “Geographically Weighted Methods to Validate Land Use Cover Maps”). Inglés

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