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Spatial Interpolation for Climate Data

range of strategies, from traditional methods, such as those for hydromet database analysis and management, to new developing methods. As such;

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Spatial Data Analysis in the Social and Environmental Sciences

for interpretation. The purpose of this book is to describe current methods for the analysis of spatial data. Methods described include data;

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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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Advances in 3D Geoinformation

spatial relationships, 3D spatial analysis and algorithms for navigation, interpolation, advanced VR, AR and MR visualisation, as well as 3D;

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Computing in Geographic Information Systems

is emerging as a platform for scientific visualization, simulation, and computation of spatio-temporal data. New computing techniques are being;

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Computing in Geographic Information Systems

is emerging as a platform for scientific visualization, simulation, and computation of spatio-temporal data. New computing techniques are being;

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Spatial Statistics and Geostatistics

Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well;

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Spatial Statistics & Geostatistics

Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well;

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3D Modelling for Geotechnical Investigation

spaced to minimize cost of drilling boreholes at each and every meter, hence; interpolation between these widely-spaced data points is done;

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Cambridge Manuals in Archaeology

: the theoretical context and the basics of GIS; data acquisition including database design; interpolation of elevation models; exploratory data;

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Spatial interpolation of precipitation

This book deals with the spatial estimation of storm, monthly and annual precipitation in the Cetina River catchment. The river catchment;

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GIS for Environmental Applications

visualisation, spatial interpolation, spatial statistics, and remote sensing data analysis, as well as demonstrates the typical environmental;

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GIS for Environmental Applications

visualisation, spatial interpolation, spatial statistics, and remote sensing data analysis, as well as demonstrates the typical environmental;

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Geographical Information and Climatology

measurement; spatial analysis, mapping and climate; geographical information, remote sensing and climatology; and geographical information for;

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Spatial And Syndromic Surveillance For Public Health

. Spatial surveillance systems are used to detect changes in public health data, and alert us to possible outbreaks of disease, either from natural;

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Downscaling Techniques for High-Resolution Climate Projections

Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales;

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Spatial Technology and Archaeology

illustrated with worked case-studies using archaeological data. Spatial Technology and Archaeology provides a single reference source for;

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Spatial Technology And Archaeology

illustrated with worked case-studies using archaeological data. Spatial Technology and Archaeology provides a single reference source for;

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Interpolation

of tables by constructing new data points from existing points. This rigorous presentation employs only formulas for which it is possible to;

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Regional Resilience to Climate and Environmental Shocks

for spatial analysis in the study of economic resilience, the book introduces spatial econometric models, their estimation and testing;

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Machine Learning on Geographical Data Using Python

Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data;

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Spatial Data Management

support spatial data. It presents indexing approaches for spatial data, with a focus on the R-tree. Query evaluation and optimization techniques;

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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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Spatial Computing

, analyze, and visualize spatial data; spatial databases, which store multiple forms of spatial data; and spatial statistics and spatial data;

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Uncertainty Modelling and Quality Control for Spatial Data

Quality Control for Spatial Data introduces methods for managing uncertainties-such as data of questionable quality-in geographic information;

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Uncertainty Modelling and Quality Control for Spatial Data

Quality Control for Spatial Data introduces methods for managing uncertainties-such as data of questionable quality-in geographic information;

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