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Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses

for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial Data and Spatial;

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Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses

for spatial data and spatial analysis is an important branch of that theory. Principles of Modeling Uncertainties in Spatial Data and Spatial;

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Advances in Geo-Spatial Information Science

-spatial information science (such as spatial data mining, mobile data modeling, and location-based services). The book contains selected and;

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Spatial Analysis

spatial data analysis, spatial autocorrelation, spatial interpolation, spatial regression, and simulation and modeling, among many others. The;

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Uncertainty Modelling and Quality Control for Spatial Data

aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book;

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Uncertainty Modelling and Quality Control for Spatial Data

aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book;

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Uncertainty in Geographical Information

aspects of spatial data processing and uncertainties, and covers a wide range of types of errors and fuzziness and emphasizes description and;

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Uncertainty in Geographical Information

aspects of spatial data processing and uncertainties, and covers a wide range of types of errors and fuzziness and emphasizes description and;

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Hierarchical Modeling and Analysis for Spatial Data

, Hierarchical Modeling and Analysis for Spatial Data, Second Edition reflects the major growth in spatial statistics as both a research area and an area;

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Computing in Geographic Information Systems

large volume of spatial data. Computing in Geographic Information Systems considers the computational aspects, and helps students;

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Computing in Geographic Information Systems

large volume of spatial data. Computing in Geographic Information Systems considers the computational aspects, and helps students;

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Mapping, Monitoring, and Modeling Land and Water Resources: Advanced Techniques Using Open Source Software

The wide range of challenges in studying Earth system dynamics due to uncertainties in climate change and complex interference from human;

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Spatial Statistics

with field data-vegetation, soil, and environmental-to produce a spatial model that can be reconstructed and displayed using GIS software;

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Spatial Microsimulation with R

Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data;

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Spatial Microsimulation with R

Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data;

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Spatial Regression Analysis Using Eigenvector Spatial Filtering

scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation;

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Spatial Data Handling in Big Data Era

This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial;

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Spatial Data Handling in Big Data Era

This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial;

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Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

simulated data and real applications. This book has been authored by leading experts in spatial statistics, including the main developers;

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Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

simulated data and real applications. This book has been authored by leading experts in spatial statistics, including the main developers of the;

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Spatial Statistics

field data-vegetation, soil, and environmental-to produce a spatial model that can be reconstructed and displayed using GIS software. Readers;

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The 3D Global Spatial Data Model Principles and Applications, Second Edition

, but modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Principles and Applications, Second;

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Spatial Data Analysis

Spatial Data Analysis: Theory and Practice, first published in 2003, provides a broad ranging treatment of the field of spatial data;

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Spatial Econometrics using Microdata

This book provides an introduction to spatial analyses concerning disaggregated (or micro) spatial data. Particular emphasis is put on;

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Scale in Spatial Information and Analysis

spatial data and their analyses. They also explore a process-pattern paradigm in approaching scale issues. This is well reflected, for example;

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Scale in Spatial Information and Analysis

spatial data and their analyses. They also explore a process-pattern paradigm in approaching scale issues. This is well reflected, for example;

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Overview of Bayesian methods and Bayesian hierarchical modeling as applied to spatial data Bayesian Computation and goodness-of-fit;

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