ABSTRACT
Spatial technologies such as GIS and remote sensing are widely used for environmental and natural resource studies. Spatial Accuracy Assessment provides state-of-the-science methods, techniques and real-world solutions designed to validate spatial data, to meet quality assurance objectives, and to ensure cost-effective project implementation.
TABLE OF CONTENTS
part I|32 pages
Keynote Speeches
part II|64 pages
Sensitivity of Decision-Making to Spatial Uncertainty
chapter CHAPTER 7|10 pages
Digital Terrain Modeling: Accuracy Assessment and Hydrological Simulation Sensitivity
part III|48 pages
Methods of Characterizing Uncertainty
chapter CHAPTER 12|8 pages
Characterizing Local Spatial Uncertainty in the Optimization of Thematic Class Areas
chapter CHAPTER 13|10 pages
Describing Uncertainty in Categorical Maps Using Correlated Categorical Data
part IV|28 pages
Representing Spatial Uncertainty
chapter CHAPTER 17|4 pages
Set Theoretic Considerations in the Conceptualization of Uncertainty in Natural Resource Information
chapter CHAPTER 19|8 pages
Use of Variograms to Represent Spatial Uncertainty of Geographic Linear Features
chapter CHAPTER 20|8 pages
Assessing and Visualizing Accuracy During 3D Data Capture at Digital Photogrammetric Workstations
part V|44 pages
Spatial Uncertainty Methods
chapter CHAPTER 23|6 pages
Super Ground Truth as a Foundation for a Model to Represent and Handle Spatial Uncertainty
part VI|54 pages
Generalization and Aggregation
chapter CHAPTER 28|6 pages
Evaluation of a Procedure for Line Generalization of a Statewide Land Cover Map
chapter CHAPTER 29|14 pages
ARIANNA: An Experimental Software for Regularization of Lines Surveyed by Differential CPS
chapter CHAPTER 30|8 pages
Monte Carlo Sensitivity Analysis of Spatial Partitioning Schemes: Regional Predictions of Nitrogen Loss
chapter CHAPTER 32|8 pages
Estimation of Land-Cover Proportions from Aggregated Medium-Resolution Satellite Data
part VII|90 pages
Decreasing Spatial Uncertainty
chapter CHAPTER 33|8 pages
A New Method of Photointerpretation to Increase the Overall Reliability of Forest Maps
chapter CHAPTER 34|12 pages
Local Reduction of Systematic Error in 7-1/2 Minute DEMs by Detecting Anisotropy in Derivative Surfaces
chapter CHAPTER 36|8 pages
Combining Minimum Error Variance and Spatial Variability in the Mapping of Environmental Variables
part VIII|32 pages
Decomposing Digital Images to Improve Classification and Describe Uncertainty
chapter CHAPTER 37|10 pages
Pixels and Eigenvectors: Classification of LANDSAT TM Imagery Using Spectral and Locational Information
chapter CHAPTER 38|6 pages
High Order Uncertainty in Spatial Information: Estimating the Proportion of Cover Types Within a Pixel
chapter CHAPTER 39|6 pages
Successive Approximation of Multiband Images Using Hyperdusters: The "PHASE" Approach
chapter CHAPTER 40|8 pages
Spatio-Temporal Prediction of Level 3 Data for NASAs Earth Observing System
part IX|106 pages
Characterizing and Obtaining Spatial Uncertainty Information for Specific Situations
