Applies principles and techniques from geography and other disciplines to ecological research, and thus delivers the tools of cartography, cognition, spatial statistics, remote sensing and computer sciences by way of spatial data.
Introduction and Overview.- Use of Spatial Data in Ecological Analysis Spatial Ecological Models.- Coastal Sage Scrub Case Study.- Incorporating Uncertainties in Animal Location and Map Classification into Habitat Relationships Modeling.- Generic Issues Regarding Uncertainty in Spatial Data.- METHODS Mapping Ecological Uncertainty.- A Cognitive View of Spatial Uncertainty.- Spatial Analyses of Ecological Data.- Geostatistical Models of Uncertainty for Spatial Data.- Spatial Linear Models in Ecology.- Characterizing Uncertainty in Digital Elevation Models.- Uncertainty of Multinominal Spatial Data.- An Overview of Uncertainty in Remote Sensing for Ecological Applications.- Remote Sensing Classification of Forest Covertype and Estimation of Stand Leaf Area Index for Modeling Net Primary Production.- Spatially Variable Thematic Accuracy: Beyond the Confusion Matrix.- Modeling Spatial Variation of Classification Accuracy Under Fuzzy Logic.- Set Theoretic Approaches to Uncertainty in Spatial Information.- Roles of Meta-Information in Uncertainty Management.- Making Decisions Under Uncertainty Using GIS.- Epilogue.