Spatial Gems : Volume 2.

Format:

Book

Author/Creator:

Krumm, John.

Contributor:

Züfle, Andreas.

Shahabi, Cyrus.

Series:

ACM Bks.

Language:

English

Subjects (All):

Geospatial data.

Geographic information systems.

Physical Description:

1 online resource (158 pages)

Edition:

1st ed.

Place of Publication:

Association for Computing Machinery 2024

New York : Morgan & Claypool Publishers, 2024.

Summary:

Spatial gems are computational techniques for processing spatial data. This book, a follow-up to the first Spatial Gems volume, is a further collection of techniques contributed by leading research experts.

Contents:

Intro

Spatial Gems, Volume 2

Contents

Preface

Introduction

Acknowledgments

1 Graph Sampling for Map Comparison

1.1 Introduction

1.1.1 Related Work

1.2 Graph Sampling Methods

1.2.1 Sampling Method

1.2.1.1 Global versus Local Sampling

1.2.1.2 Graph Sampling Used in the Literature

1.2.2 Matching Rule

1.2.2.1 Matching Rules Used in the Literature

1.2.3 Score Calculation

1.2.4 Graph Sampling Toolkit

1.3 Discussion/Conclusion

References

2 Fast 3D Euclidean Connected Components

2.1 Introduction

2.2 A Better Data Structure for the Euclidean Case

2.3 Connected Component Algorithm

2.4 Implementation

2.4.1 Implementation Validation

2.5 Examples

2.5.1 Random Voxels, 26-Connectivity

2.5.2 Random Voxels, 6-Connectivity

2.5.3 Concrete under Compression

2.5.4 Random Dataset Properties

2.6 Comparison to Matlab

2.7 Summary and Future

3 Multiscale Aggregation Over Sliding Windows

3.1 Introduction

3.2 Concepts

3.3 Evaluation

3.4 Summary

4 Gaussian Process for Trajectories

4.1 Introduction

4.2 Gaussian Process

4.3 Gaussian Process Elements

4.3.1 Data Preparation

4.3.2 Mean Function

4.3.3 Kernel/Covariance Function

4.3.3.1 Common Kernel Types

4.3.3.2 Common Types of Kernel Combination

4.3.4 Training and Inference

4.4 Gaussian Process Example

4.5 Discussion

5 Mean Chord Length of a Square

5.1 Introduction

5.2 Derivation of Mean Chord Length

5.3 Summary

Reference

6 Object Delineation in Satellite Images

6.1 Introduction

6.2 Extracting Objects

6.2.1 Orthogonal Lines Detection

6.2.2 Ring Formation

6.3 Experimental Result

7 Implementing Simulation of Simplicity for Geometric Degeneracies

7.1 Introduction.

7.2 Infinitesimals

7.3 Simulation of Simplicity

7.4 Examples of SoS in Use

7.4.1 Point on Edge in 1D

7.4.2 Point in Polygon Test

7.4.3 Volume of Union of Cubes

7.4.4 Point Location in 3D Mesh

7.4.5 Intersecting 3D Triangular Meshes

7.5 Summary and Acknowledgments

8 Probabilistic Counting in Uncertain Spatial Databases Using Generating Functions

8.1 Introduction

8.2 Generating Functions for Probabilistic Counting

8.3 Complexity Analysis

8.4 Implementation

8.5 Variants, Extensions, and Improvements

8.5.1 Acceleration Using Discrete Fourier Transform

8.5.2 Extension to Uncertain Counts

8.5.3 Dynamic Polynomials

9 Statistics for All Walks on a Lattice Graph

9.1 Introduction

9.2 Computing All Walks

9.3 Statistics

9.4 Summary

10 Online Heatmap Generation with Both High and Low Weights

10.1 Introduction

10.2 Algorithms

10.2.1 Problem Formulation

10.2.2 Point Overlay Methods

10.3 Hilomap

10.4 Discussion

Appendix: Hilomap Code Access

Authors' Biographies

Editors

01 - Graph Sampling for Map Comparison

02 - Fast 3D Euclidean Connected Components

03 - Multiscale Aggregation Over Sliding Windows

04 - Gaussian Process for Trajectories

05 - Mean Chord Length of a Square

06 - Object Delineation in Satellite Images

07 - Implementing Simulation of Simplicity for Geometric Degeneracies

08 - Probabilistic Counting in Uncertain Spatial Databases Using Generating Functions

09 - Statistics for All Walks on a Lattice Graph

10 - Online Heatmap Generation with Both High and Low Weights

Index.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

979-84-00-70937-1

OCLC:

1420629074