1st Edition

Statistical Geoinformatics for Human Environment Interface

By Wayne L. Myers, Ganapati P. Patil Copyright 2013
    223 Pages 148 B/W Illustrations
    by Chapman & Hall

    223 Pages 148 B/W Illustrations
    by Chapman & Hall

    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 paired paradigms enable:

    • The capacity to cope with complexity
    • Systematic surveillance
    • Visualization and communication
    • Preliminary prioritization
    • Coupling of GIS and statistical software
    • Avenues for automation

    Illustrating the interdisciplinary nature of geoinformatics, this book offers a novel approach to the spatial analysis of human influences and environmental resources. It includes practical strategies for statistical and spatial analysis.

    Statistical Geoinformatics of Human Linkage with Environment
    Human Environment Informational Interface and Its Indicators
    The "-matics" of Geoinformatics
    Spatial Synthesis of Disparate Data by Localization as Vicinity Variates
    Spatial Posting of Tabulations (SPOTing)
    Exemplifying County Context
    Posting Points and Provisional Proximity Perimeters for Lackawanna County
    Surveillance with Software Sentinels
    Backdrop: Distributed Data Depots and Digital Delivery

    Localizing Fixed-Form Features
    Locality Layer as Poly-Place Purview
    Localizing Layer of Proximity Perimeters
    Localizing Linears by Determining Densities
    Transfer from Perimeters to Points
    Apportioning Attributes of Partial Polygons
    Backdrop: GIS Generics

    Precedence and Patterns of Propensity
    Prescribing Precedence
    Product–Order Precedence Protocol
    Precedence Plot
    Propensities as Progression of Precedence
    Progression Plot
    Reversing Ranks
    Inconsistency Indicator
    Backdrop: Statistical Software

    Raster-Referenced Cellular Codings and Map Modeling
    Fixed-Frame Micromapping with Conceptual Cells
    Cover Classes and Localizing Logic
    Raster Regions and Associated Attributes
    Map Modeling
    Layer Logic

    Similar Settings as Clustered Components
    CLAN Clusters
    CLUMP Clusters
    CLAN Cluster Centroids
    Salient Centroids
    Graded Groups by Representative Ranks
    Rank Rods
    Salient Sequences by Representative Ranks

    Intensity Images and Map Multimodels
    Intensity as Frequency of Occurrence
    Hillshades and Slopes
    Interposed Distance Indicators
    Backdrop: Pictures as Pixels and Remote Sensing

    High Spots, Hot Spots, and Scan Statistics
    Concentration of CIT Core Development
    Complexion of CIT Developments
    Particular Proximity
    Upper Level Set (ULS) Scanning
    Backdrop: Python Programming

    Shape, Support, and Partial Polygons
    Inscribed Octagons
    Matching Margins and Adjusting Areas
    Shape and Support for Local Roads
    Precedence Plot for Shapes and Supports
    Supports Spanning Several Partial Polygons

    Semisynchronous Signals and Variant Vicinities
    Distal Data
    Median Models
    Pairing/Placement Patterns of Signal Strengths

    Auto-Association: Local Likeness and Distance Decline
    Cluster Companions
    Kindred Clusters
    Local Averages
    LISA: Local Indicator of Spatial Association
    Picking Pairs at Lagged Locations
    Empirical (Semi-)Variogram
    Moran’s I and Similar Spatial Statistics

    Regression Relations for Spatial Stations
    Trend Surfaces
    Regression Relations among Vicinity Variates
    Restricted Regression

    Spatial Stations as Surface Samples
    Interpolating Intensity Indicators as Smooth Surfaces
    Spline Smoothing

    Shifting Spatial Structure
    Space–Time Hotspots
    Salient Shifts
    Paired Plots
    Primary Partition Plots
    Backdrop: Spectral Detection of Change with Remote Sensing

    Synthesis and Synopsis with Allegheny Application
    Localization Logic
    Locality Layer
    Localizing Layer
    Poly-Place Purviews
    Significant Spatial Sectors with Scan Statistics
    Scale Sensitivity and Partial Precedence
    Cluster Components and Cluster Companions
    Trend Surfaces
    Surveillance Systems: Sentinel Stations and Signaling
    Scripted Sentinels
    Smart-Sentinel Socialization


    References appear at the end of each chapter.


    Wayne L. Myers is Professor Emeritus of Forest Biometrics at the Pennsylvania State University. He is a Certified Forester of the Society of American Foresters, an Emeritus Member of the American Society of Photogrammetry and Remote Sensing, and a 40-year member of the American Statistical Association. Dr. Myers specializes in landscape analysis using GIS and remote sensing in conjunction with multivariate approaches to analysis and prioritization.

    Ganapati P. Patil is Director of the Center for Statistical Ecology and Environmental Statistics and Distinguished Professor Emeritus of Mathematical and Environmental Statistics at the Pennsylvania State University. He is a fellow of the American Statistical Association, American Association of Advancement of Science, Institute of Mathematical Statistics, International Statistical Institute, Royal Statistical Society, International Association for Ecology, International Indian Statistical Association, Indian National Institute of Ecology, and Indian Society for Medical Statistics. Dr. Patil has served on panels for numerous international organizations, including the United Nations Environment Programme, U.S. National Science Foundation, U.S. Environmental Protection Agency, U.S. Forest Service, and U.S. National Marine Fisheries Service. He has authored/coauthored more than 300 research papers and more than 30 cross-disciplinary volumes.

    "… a refreshingly different approach to geospatial analysis, which has the potential to unify the disparate worlds of raster and vector GIS and to provide an integrated treatment of space and time. Readers accustomed to more traditional approaches to geoinformatics may find the book particularly thought provoking."
    —Sally E. Goldin, Photogrammetric Engineering and Remote Sensing, December 2013