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Statistical geoinformatics for human environment interface
Title statement Statistical geoinformatics for human environment interface / Wayne L. Myers, Ganapati Patil Personal name Myers, Wayne L., 1942- (author) Publication Boca Raton : CRC Press, [2013] Copyright notice date ©2013 Phys.des. 1 online zdroj : ilustrace ISBN 9781420082883 (online) 1420082884 (online) Edition Applied environmental statistics Internal Bibliographies/Indexes Note Obsahuje bibliografické odkazy Contents Statistical Geoinformatics of Human Linkage with Environment -- Localizing Fixed-Form Features -- Precedence and Patterns of Propensity -- Raster-Referenced Cellular Codings and Map Modeling -- Similar Settings as Clustered Components -- Intensity Images and Map Multimodels -- High Spots, Hot Spots, and Scan Statistics -- Shape, Support, and Partial Polygons -- Semisynchronous Signals and Variant Vicinities -- Auto-Association: Local Likeness and Distance Decline -- Regression Relations for Spatial Stations -- Spatial Stations as Surface Samples -- Shifting Spatial Structure -- Synthesis and Synopsis with Allegheny Application. Notes to Availability Přístup pouze pro oprávněné uživatele Note Způsob přístupu: World Wide Web Defekty eBooks on EBSCOhost Another responsib. Patil, Ganapati P. (author) Subj. Headings ekologie člověka human ecology * geoinformatika geoinformatics * statistické metody statistical methods Form, Genre elektronické knihy electronic books Conspect 502 - Životní prostředí a jeho ochrana UDC 004:91 , 519.23/.24 , 502.22 , (0.034.2:08) Country Florika Language angličtina Document kind Electronic sources URL http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=467616 book
Statistical Geoinformatics for Human Environment Interface presents two paradigms for studying both space and interface with regard to human/environment: localization and multiple indicators. The first approach localizes thematic targets by treating space as a pattern of vicinities, with the pattern being a square grid and the placement of vicinities centrically referenced. The second approach explores human/environment interface as an abstraction through indicators, neutralizing the common conundrum of how to reconcile disparate spatial structures such as points, lines, and polygons. These pa.
Statistical Geoinformatics of Human Linkage with Environment -- Localizing Fixed-Form Features -- Precedence and Patterns of Propensity -- Raster-Referenced Cellular Codings and Map Modeling -- Similar Settings as Clustered Components -- Intensity Images and Map Multimodels -- High Spots, Hot Spots, and Scan Statistics -- Shape, Support, and Partial Polygons -- Semisynchronous Signals and Variant Vicinities -- Auto-Association: Local Likeness and Distance Decline -- Regression Relations for Spatial Stations -- Spatial Stations as Surface Samples -- Shifting Spatial Structure -- Synthesis and Synopsis with Allegheny Application.
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