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.Eric Hardin, Helena Mitasova, Laura Tateosian, Margery Overton ... and Mac OS X. The basic terminology and data organization in GRASS7 is described in the GRASS GIS Quickstart document (http://grass.osgeo.org/grass71/manuals/anbsp;...
|Title||:||GIS-based Analysis of Coastal Lidar Time-Series|
|Author||:||Eric Hardin, Helena Mitasova, Laura Tateosian, Margery Overton|
|Publisher||:||Springer - 2014-09-12|