GIS-based Analysis of Coastal Lidar Time-Series [electronic resource] / by Eric Hardin, Helena Mitasova, Laura Tateosian, Margery Overton.

By:

Hardin, Eric [author.]

Contributor(s):

Series: SpringerBriefs in Computer SciencePublisher: New York, NY : Springer New York : Imprint: Springer, 2014Description: VI, 84 p. 35 illus., 34 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781493918355

Subject(s):

Genre/Form:

Electronic books.

Additional physical formats: Printed edition:: No titleDDC classification:

910.285 23

LOC classification:

GA1-1776

Online resources:

Click here to access online

Contents:

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

In: Springer eBooksSummary: 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.

Item type:

eBooks

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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.