Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

"Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements, but modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Principles and Applications, Second Edition maintains a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This second edition expands to new topics that satisfy a growing need in the GIS, professional surveyor, machine control, and Big Data communities while continuing to embrace the earth center fixed coordinate system as the fundamental point of origin of one, two, and three-dimensional data sets. Ideal for both beginner and advanced levels, this book also provides guidance and insight on how to link to the data collected and stored in legacy systems."--Provided by publisher.

Spatial data infrastructures --- Spatial systems. --- Three-dimensional imaging. --- Mathematics.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Spatial analysis assists theoretical understanding and empirical testing in the social sciences, and rapidly expanding applications of geographic information technologies have advanced the spatial data-gathering needed for spatial analysis and model making. This much-needed volume covers outstanding examples of spatial thinking in the social sciences, with each chapter showing some aspect of how certain social processes can be understood by analyzing their spatial context. The audience for this work is as trans-disciplinary as its authorship because it contains approaches and methodologies use

Spatial analysis (Statistics) --- Population geography --- Demography --- Human geography --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems --- Statistical methods. --- Social sciences --- Research.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Advances in Econometrics is a research annual whose editorial policy is to publish original research articles that contain enough details so that economists and econometricians who are not experts in the topics will find them accessible and useful in their research. Volume 37 exemplifies this focus by highlighting key research from new developments in econometrics.

Space in economics --- Mathematical models. --- Econometrics --- Spatial analysis (Statistics) --- E-books --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems --- Economics, Mathematical --- Statistics --- Business & Economics --- Econometrics. --- Economics --- Macroeconomics.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

"Spatial Regression Analysis Using Eigenvector Spatial Filtering provides both theoretical foundations and guidance on practical implementation for the eigenvector spatial filtering (ESF) technique. ESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in georeferenced data analyses. With its flexible structure, ESF can be easily applied to generalized linear regression models. The book discusses ESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, and spatial interaction models. In addition, it provides a tutorial for ESF model specification and interfaces, including author developed, user-friendly software"--

Spatial analysis (Statistics) --- Regression analysis. --- Eigenvectors. --- Matrices --- Vector spaces --- Eigenfactor --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Spatial Data Analysis: Theory and Practice, first published in 2003, provides a broad ranging treatment of the field of spatial data analysis. It begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and policy related research. Covering fundamental problems concerning how attributes in geographical space are represented to the latest methods of exploratory spatial data analysis and spatial modeling, it is designed to take the reader through the key areas that underpin the analysis of spatial data, providing a platform from which to view and critically appreciate many of the key areas of the field. Parts of the text are accessible to undergraduate and master's level students, but it also contains sufficient challenging material that it will be of interest to geographers, social and economic scientists, environmental scientists and statisticians, whose research takes them into the area of spatial analysis.

Spatial analysis (Statistics) --- Geology --- Geognosy --- Geoscience --- Earth sciences --- Natural history --- Analysis, Spatial (Statistics) --- Correlation (Statistics) --- Spatial systems --- Statistical methods --- Data processing.