GIS-based Analysis of Coastal Lidar Time-Series

Eric Hardin

ISBN 10: 1493918346 / ISBN 13: 9781493918348

Verlag: Springer New York, Springer New York, 2014

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - 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.

Bestandsnummer des Verkäufers 9781493918348

Bibliografische Details

• Titel: GIS-based Analysis of Coastal Lidar Time-Series
• Verlag: Springer New York, Springer New York
• Erscheinungsjahr: 2014
• Sprache: Englisch
• ISBN-10: 1493918346
• ISBN-13: 9781493918348
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 235B x 155 H x 6 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 6 mm
• Gewicht: 154 Gramm

Über diesen Titel

Inhaltsangabe

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.