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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.
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