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Spatial Data Quality: From Process to Decisions

Data Quality: From Process to Decisions provides an up-to-date overview of scientific progress in this core sub-discipline of the Geographic;

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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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Quality Aspects in Spatial Data Mining

indispensable volume addresses quality aspects in the entire spatial data mining process, from data acquisition to end user. It also alleviates what;

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Quality Aspects in Spatial Data Mining

indispensable volume addresses quality aspects in the entire spatial data mining process, from data acquisition to end user. It also alleviates what;

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Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses

analyses, uncertainty modeling for spatial data to spatial models, and error description of spatial data to spatial data quality control;

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Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses

analyses, uncertainty modeling for spatial data to spatial models, and error description of spatial data to spatial data quality control;

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Fundamentals of Spatial Data Quality

This book explains the concept of spatial data quality, a key theory for minimizing the risks of data misuse in a specific decision-making;

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Spatial Data Quality

quality, leading to inaccurate results, uncertainty, error propagation, and potentially legal liability. Spatial data quality has become an;

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Geocomputation and Urban Planning

data and information is growing, together with the capacity of users to operate with IT tools and instruments. Spatial data infrastructures are;

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Statistical Analysis of Spatial and Spatio-Temporal Point Patterns

how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several packages;

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Statistical Analysis of Spatial and Spatio-Temporal Point Patterns

how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several;

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Principles Of Geographical Information Systems

described in detail, including the use of geostatistics for interpolating from points to continuous fields. Examples of how spatial data and an;

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Advanced Information Systems Engineering

Visualization, Big Data and Intelligence, Data Modelling and Mining, Quality Requirements and Software, and Tutorials.;

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Translating Data into Information to Improve Teaching and Learning

elements and data tools needed to support quality decisions for improving teaching and learning. It shows you how to use data to help make;

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Translating Data into Information to Improve Teaching and Learning

elements and data tools needed to support quality decisions for improving teaching and learning. It shows you how to use data to help make;

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Spatial Data Analysis in Ecology and Agriculture Using R

instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms;

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Toward a Coordinated Spatial Data Infrastructure for the Nation

The National Spatial Data Infrastructure (NSDI) is the means to assemble geographic information that describes the arrangement and;

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Spatial Data Handling in Big Data Era

computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge;

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More Judgment Than Data

ability to extract meaning from data. Including data in the decision-making process can bring considerable clarity in answering our;

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Python Geospatial Analysis Cookbook

GeoDjango to include your spatial analysis tools built from the previous recipes In Detail Geospatial development links your data to places on;

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Guidelines For Improving Plant Reliability Through Data Collection And Analysis

to collect and organize high quality plant performance, maintenance, and repair data from your own operations, and includes methods and;

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Spatial Data Handling in Big Data Era

computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge;

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Spatial Data Infrastructures at Work

administrative practices. In order to facilitate access, use, and sharing of spatial data among organisations, information is brought together;

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Scalable Processing of Spatial-Keyword Queries

tweet is associated with the location where the tweet has been issued. We use the term spatial-keyword data to refer to this type of data;

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Scalable Processing of Spatial-Keyword Queries

tweet is associated with the location where the tweet has been issued. We use the term spatial-keyword data to refer to this type of data;

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The Future of Spatial Data and Society

depends on how these spatial data activities will be relevant to future needs and demands. The Mapping Science Committee, in cooperation with;

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