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Titlebook: GIS-based Analysis of Coastal Lidar Time-Series; Eric Hardin,Helena Mitasova,Margery Overton Book 2014 The Author(s) 2014 Beach Erosion.Co

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發(fā)表于 2025-3-21 17:00:35 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱GIS-based Analysis of Coastal Lidar Time-Series
編輯Eric Hardin,Helena Mitasova,Margery Overton
視頻videohttp://file.papertrans.cn/381/380122/380122.mp4
概述Includes supplementary material:
叢書名稱SpringerBriefs in Computer Science
圖書封面Titlebook: GIS-based Analysis of Coastal Lidar Time-Series;  Eric Hardin,Helena Mitasova,Margery Overton Book 2014 The Author(s) 2014 Beach Erosion.Co
描述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.
出版日期Book 2014
關(guān)鍵詞Beach Erosion; Coastal Change; DEM Time Series; GIS; LiDAR; Sand dunes; Visualization of Coastal Dynamics;
版次1
doihttps://doi.org/10.1007/978-1-4939-1835-5
isbn_softcover978-1-4939-1834-8
isbn_ebook978-1-4939-1835-5Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Author(s) 2014
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 20:43:12 | 只看該作者
Processing Coastal Lidar Time Series,n this analysis and a given application we select appropriate resolution and interpolation method for computation of raster-based digital elevation model (DEM). We explain computation of DEMs by per raster-cell averaging, two types of splines. Assessment of systematic error using geodetic benchmarks
板凳
發(fā)表于 2025-3-22 01:16:32 | 只看該作者
Raster-Based Analysis,een two surveys is DEM differencing, performed by map algebra within GIS (. in GRASS). For a larger number of elevation data snapshots, per cell statistics can be applied to the raster DEMs to derive summary maps, which reveal the spatial patterns of stable and dynamic sites, the time periods when s
地板
發(fā)表于 2025-3-22 07:38:02 | 只看該作者
5#
發(fā)表于 2025-3-22 11:37:24 | 只看該作者
Visualizing Coastal Change,nd explore. This particularly applies to coastal geomorphology, where 3D spatial and temporal patterns and relationships are critical for capturing landscape features and their dynamics. In this chapter we present GIS-based techniques for visualizing dynamic coastal landscapes using 2D maps, 3D pers
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發(fā)表于 2025-3-22 15:48:23 | 只看該作者
2191-5768 or 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.978-1-4939-1834-8978-1-4939-1835-5Series ISSN 2191-5768 Series E-ISSN 2191-5776
7#
發(fā)表于 2025-3-22 18:37:56 | 只看該作者
Book 2014sualization 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.
8#
發(fā)表于 2025-3-22 21:21:23 | 只看該作者
Introduction,sing Geographic Information Systems (GIS). In this chapter we discuss mapping of coastal change, on-line data resources, and the basics of installation and working with open source GRASS GIS used in this book.
9#
發(fā)表于 2025-3-23 01:26:26 | 只看該作者
Processing Coastal Lidar Time Series,del (DEM). We explain computation of DEMs by per raster-cell averaging, two types of splines. Assessment of systematic error using geodetic benchmarks or other ground truth point data and correction of any shifted DEMs is the final step in creating a consistent DEM time series.
10#
發(fā)表于 2025-3-23 07:43:34 | 只看該作者
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