Spatial Analysis
Joseph L. Awange, John Kiema · Environmental science and engineering · 2018
Cited by 0
Search 250 million research papers
Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.
About 10,000 papers for “Spatial analysis”
Spatial Analysis
Luc Anselin, Alan T. Murray, Sergio J. Rey · Oxford University Press eBooks · 2013
Cited by 6
Spatial Analysis
2023
The geometric transformations are transformations of objects based on a coordinate system. To translate (move), scale, skew (shear), or rotate, an object with computation requires an affine transformation. Image capture and display may produce geometric distortion, or morphing, of an object. Geometric decalibration compensates for distortion and can provide a measurement of the geometric distortion of an optical system. Distortion compensation adds or subtracts pixels by interpolation. Besides revealing the problems of cultural and scientific bias, Gould points out that the pioneers of morphometrics were also the pioneers of statistics. It is enlightening reading because it also explains in relatively nonmathematical terms the method they discovered to compare data sets, principal component analysis. This, along with canonical variates analysis, can correlate species shape, finding the morphometric similarity among different species. A convolutional neural network has multiple layers of mathematical operators, some of which are convolution operations. Macro-level spatial analysis often relates to shape.
Cited by 0
SPATIAL ANALYSIS
Kalogirou, Stamatis · KALLIPOS REPOSITORY · 2016
Σκοπός του βιβλίου αυτού είναι να βοηθήσει τον αναγνώστη να κατανοήσει τι είναι η χωρική ανάλυση και πως μπορεί να εφαρμόσει μερικές μεθόδους της σε προβλήματα με χωρική διάσταση στον πραγματικό κόσμο. Ως διδακτικό εγχειρίδιο απευθύνεται σε προπτυχιακούς και μεταπτυχιακούς φοιτητές καθώς και σε υποψήφιους διδάκτορες και ερευνητές που ενδιαφέρονται γι αυτό το αντικείμενο. Το βιβλίο ασχολείται με ζητήματα της χωρικής ανάλυσης που αφορούν κατά κύριο λόγο τη χωρική στατιστική και τα Γεωγραφικά Συστήματα Πληροφοριών. Επειδή μεγάλο τμήμα του βασίζεται σε έρευνα των τελευταίων 15 ετών, παρέχει στον αναγνώστη καλές πρακτικές εφαρμοσμένης χωρικής ανάλυσης κοινωνικοοικονομικών δεδομένων όπως το οικογενειακό εισόδημα, η εκπαίδευση, η ανθρώπινη φτώχεια αλλά και δημογραφικών δεδομένων όπως η εσωτερική μετανάστευση και η γήρανση πληθυσμού. Τέλος, το βιβλίο περιλαμβάνει ένα κεφάλαιο όπου διδάσκεται βασικός στατιστικός προγραμματισμός με τη γλώσσα R η οποία αποτελεί σήμερα μια από τις πιο δημοφιλείς γλώσσες ανοιχτού λογισμικού για στατιστική και χωρική ανάλυση.
Cited by 0Open access
Spatial Analysis
Archaeopress Publishing Ltd eBooks · 2018
Cited by 0
Spatial Analysis
Clark, Andrew David, Deffner, Dominik, Laland, Kevin et al. · Figshare · 2019
Selection gradients used in the spatial analysis from Clark et al. 2019 in The American Naturalist: Niche construction affects the variability and strength of selection.
Cited by 0Open access
Spatial Analysis
George ThomasKurian · The Encyclopedia of Political Science · 2011
Cited by 2
Spatial Analysis
Fischer, Manfred M. · WU Research · 1999
This article views spatial analysis as a research paradigm that provides a unique set of specialised <br/>techniques and models for a wide range of research questions in which the prime variables of interest <br/>vary significantly over space. The heartland of spatial analysis is concerned with the analysis and <br/>modeling of spatial data. Spatial point patterns and area referenced data represent the most appropriate <br/>perspectives for applications in the social sciences. The researcher analysing and modeling spatial data <br/>tends to be confronted with a series of problems such as the data quality problem, the ecological <br/>fallacy problem, the modifiable areal unit problem, boundary and frame effects, and the spatial <br/>dependence problem. The problem of spatial dependence is at the core of modern spatial analysis and <br/>requires the use of specialised techniques and models in the data analysis. The discussion focuses on <br/>exploratory techniques and model-driven [confirmatory] modes of analysing spatial point patterns and <br/>area data. In closing, prospects are given towards a new style of data-driven spatial analysis <br/>characterized by computational intelligence techniques such as evolutionary computation and neural <br/>network modeling to meet the challenges of huge quantities of spatial data characteristic in remote <br/>sensing, geodemographics and marketing. (author's abstract)
Cited by 0Open access
Spatial Analysis
Mark R. T. Dale, Marie‐Josée Fortin · Cambridge University Press eBooks · 2014
Nowadays, ecologists worldwide recognize the use of spatial analysis as essential. However, because of the fast-growing range of methods available, even an expert might occasionally find it challenging to choose the most appropriate one. Providing the ecological and statistical foundations needed to make the right decision, this second edition builds and expands upon the previous one by: • Encompassing the basic methods for spatial analysis, for both complete census and sample data • Investigating updated treatments of spatial autocorrelation and spatio-temporal analysis • Introducing detailed explanations of currently developing approaches, including spatial and spatio-temporal graph theory, scan statistics, fibre process analysis, and Hierarchical Bayesian analysis • Offering practical advice for specific circumstances, such as how to analyze forest Permanent Sample Plot data and how to proceed with transect data when portions of the data series are missing. Written for graduates, researchers and professionals, this book will be a valuable source of reference for years to come.
Cited by 223
Spatial Analysis
Auerbach Publications eBooks · 2008
Cited by 0
Spatial Analysis
Shashi Shekhar, Hui Xiong · Encyclopedia of GIS · 2008
Cited by 1
Spatial Analysis
Orton, C · UCL Discovery (University College London) · 2000
Cited by 0
Spatial analysis
Ramsden, Mark · Research Repository (Kingston University London) · 2011
Cited by 0
Spatial Analysis
Qiyu Chen, Gang Liu, Xiaogang Ma et al. · Encyclopedia of earth sciences series/Encyclopedia of earth sciences · 2021
Cited by 0
Spatial Analysis
Marc D. Gellman, J. Rick Turner · 2013
Cited by 0
Spatial Analysis
Xuan Zhu · 2024
Cited by 0
Spatial analysis
RJ Johnston · Bristol Research (University of Bristol) · 1996
Cited by 0
Spatial analysis
RJ Johnston · Bristol Research (University of Bristol) · 2001
Cited by 0
Spatial Analysis
Mardia, K., Kent, J. · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2022
Explore the foundations and latest developments in spatial statistical analysis. \n \nIn Spatial Analysis, two distinguished authors deliver a practical and insightful exploration of the statistical investigation of the interdependence of random variables as a function of their spatial proximity. The book expertly blends theory and application, offering numerous worked examples and exercises at the end of each chapter. \n \nIncreasingly relevant to fields as diverse as epidemiology, geography, geology, image analysis, and machine learning, spatial statistics is becoming more important to a wide range of specialists and professionals. \n \nThe book includes: \n \nThorough introduction to stationary random fields, intrinsic and generalized random fields, and stochastic models \n \nComprehensive exploration of the estimation of spatial structure \n \nPractical discussion of kriging and the spatial linear model. \n \nSpatial Analysis is an invaluable resource for advanced undergraduate and postgraduate students in statistics, data science, digital imaging, geostatistics, and agriculture. It’s also an accessible reference for professionals who are required to use spatial models in their work.
Cited by 0
Spatial analysis
Starnini E · CINECA IRIS Institutial research information system (University of Pisa) · 1997
Cited by 0