New York : Springer, [2014]

1 online resource (vi, 84 pages) : illustrations (some color).

Electronic book.

SpringerBriefs in Computer Science, 2191-5768

SpringerBriefs in computer science.

Includes bibliographical references.

Description based on online resource; title from PDF title page (Ebsco, viewed September 18, 2014).

Introduction -- Processing coastal lidar time series -- Raster-based analysis -- Feature extraction and feature change metrics -- Volume analysis -- Visualizing coastal change -- Appendix.

This SpringerBrief presents the principles, methods, and workflows for processing and analyzing coastal LiDAR data time-series. Robust methods for computing high resolution digital elevation models (DEMs) are introduced as well as raster-based metrics for assessment of topographic change. An innovative approach to feature extraction and measurement of feature migration is followed by methods for estimating volume change and sand redistribution mapping. Simple methods for potential storm impacts and inundation pattern analysis are also covered, along with visualization techniques to support analysis of coastal terrain feature and surface dynamics. Hands-on examples in GRASS GIS and python scripts are provided for each type of analysis and visualization using public LiDAR data time-series. GIS-based Analysis of Coastal Lidar Time-Series is ideal for professors and researchers in GIS and earth sciences. Advanced-level students interested in computer applications and engineering will also find this brief a valuable resource.

Available through SpringerLink.

University staff and students only. Requires University Computer Account login off-campus.

Mode of access: World Wide Web.

Coast changes.

Optical radar.

Geographic information systems.

Hardin, Eric.

SpringerLink (Online service)

9781493918355 (electronic bk.)

1493918354 (electronic bk.)