scholarly journals Accommodation space indicates dune development potential along an urbanized and frequently nourished coastline

2018 ◽  
Author(s):  
Corjan Nolet ◽  
Michel J. P. M. Riksen
Keyword(s):  
Airborne Lidar ◽  
Nature Management ◽  
Full Potential ◽  
Ammophila Arenaria ◽  
Dune Vegetation ◽  
Coastal Morphology ◽  
Accommodation Space ◽  
Natural Dune ◽  
Favorable Conditions ◽  
Airborne Lidar Data

Abstract. With densely populated areas well below mean sea level, the Netherlands relies heavily on its dunes to ensure coastal safety. About half of the sandy coastline, however, is subject to structural marine erosion and requires frequent sand nourishments as a counteractive measure. A key component of present-day coastal safety policy is creating favorable conditions for natural dune development. These conditions essentially involve a (1) steady supply of wind-blown sand towards (2) wide accommodation space where sand can accumulate and dunes are sheltered from storm surge impact. This paper examines to what extent an experimental mega-scale beach nourishment (termed Zandmotor in Dutch) has contributed to creating accommodation space favorable for dune development. Using publicly available airborne Lidar data and Sentinel-2 satellite imagery, favorable accommodation space is identified by comparing recent changes in coastal morphology against dune vegetation cover dynamics. With a focus on European marram grass (Ammophila arenaria) as the most prominent dune-building species, this paper demonstrates that the Zandmotor supports an especially high potential for incipient (embryo) dunes to develop as most of its favorable accommodation space is located on the beach. However, considering persistent anthropogenic disturbances arising from recreation, leisure and nature management, dune development along this urbanized coastline may not reach its full potential.

scholarly journals Accommodation space indicates dune development potential along an urbanized and frequently nourished coastline

2019 ◽  
Vol 7 (1) ◽  
pp. 129-145
Author(s):  
Corjan Nolet ◽  
Michel J. P. M. Riksen
Keyword(s):  
Management Practices ◽  
Airborne Lidar ◽  
Nature Management ◽  
Full Potential ◽  
Ammophila Arenaria ◽  
Dune Vegetation ◽  
Coastal Morphology ◽  
Accommodation Space ◽  
Marram Grass ◽  
Sand Nourishment

Abstract. With densely populated areas well below mean sea level, the Netherlands relies heavily on its dunes to ensure coastal safety. About half of the sandy coastline, however, is subject to structural marine erosion and requires frequent sand nourishment as a counteractive measure. A key component of present-day coastal safety policy is creating favorable conditions for natural dune development. These conditions essentially involve (1) a steady supply of wind-blown sand towards (2) a wide accommodation space where sand can accumulate and dunes are sheltered from frequent storm surge impacts. This paper examines to what extent an experimental mega-scale beach nourishment (termed Zandmotor in Dutch) has contributed to creating accommodation space favorable for dune development. Using publicly available airborne lidar data and Sentinel-2 satellite imagery, favorable accommodation space is identified by comparing recent changes in coastal morphology against dune vegetation-cover dynamics. With a focus on European marram grass (Ammophila arenaria) as the most prominent dune-building species, this paper demonstrates that the Zandmotor supports an especially high potential for incipient (embryo) dunes to develop as most of its favorable accommodation space is located on the beach. However, considering the conditions required for successful marram grass establishment as well as persistent anthropogenic disturbances arising from recreation and nature management practices, it is not likely that dune development along this urbanized coastline reaches its full potential.

Données LiDAR aériennes: pertinence de l'interprétation visuelle pour la foresterie

2017 ◽  
Vol 168 (3) ◽  
pp. 127-133
Author(s):  
Matthew Parkan
Keyword(s):  
Cross Sections ◽  
Forest Edge ◽  
Airborne Lidar ◽  
Visual Interpretation ◽  
Individual Tree ◽  
Small Areas ◽  
Interactive 3D ◽  
The Individual ◽  
Airborne Lidar Data ◽  
Stem Position

Airborne LiDAR data: relevance of visual interpretation for forestry Airborne LiDAR surveys are particularly well adapted to map, study and manage large forest extents. Products derived from this technology are increasingly used by managers to establish a general diagnosis of the condition of forests. Less common is the use of these products to conduct detailed analyses on small areas; for example creating detailed reference maps like inventories or timber marking to support field operations. In this context, the use of direct visual interpretation is interesting, because it is much easier to implement than automatic algorithms and allows a quick and reliable identification of zonal (e.g. forest edge, deciduous/persistent ratio), structural (stratification) and point (e.g. tree/stem position and height) features. This article examines three important points which determine the relevance of visual interpretation: acquisition parameters, interactive representation and identification of forest characteristics. It is shown that the use of thematic color maps within interactive 3D point cloud and/or cross-sections makes it possible to establish (for all strata) detailed and accurate maps of a parcel at the individual tree scale.

scholarly journals Cloth simulation-based construction of pit-free canopy height models from airborne LiDAR data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Wuming Zhang ◽  
Shangshu Cai ◽  
Xinlian Liang ◽  
Jie Shao ◽  
Ronghai Hu ◽  
...  
Keyword(s):  
Tree Height ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Canopy Height ◽  
Lidar Data ◽  
Cloth Simulation ◽  
Simulation Based ◽  
Maximum Tree Height ◽  
Airborne Lidar Data ◽  
Better Than

Abstract Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

scholarly journals Documentation of Archaeology-Specific Workflow for Airborne LiDAR Data Processing

Geosciences ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 26
Author(s):  
Edisa Lozić ◽  
Benjamin Štular
Keyword(s):  
Data Processing ◽  
Good Practice ◽  
Airborne Lidar ◽  
Archaeological Prospection ◽  
Hard Data ◽  
Cloud Processing ◽  
Archaeological Interpretation ◽  
Point Cloud Processing ◽  
Data Acquisition And Processing ◽  
Airborne Lidar Data

Airborne LiDAR is a widely accepted tool for archaeological prospection. Over the last decade an archaeology-specific data processing workflow has been evolving, ranging from raw data acquisition and processing, point cloud processing and product derivation to archaeological interpretation, dissemination and archiving. Currently, though, there is no agreement on the specific steps or terminology. This workflow is an interpretative knowledge production process that must be documented as such to ensure the intellectual transparency and accountability required for evidence-based archaeological interpretation. However, this is rarely the case, and there are no accepted schemas, let alone standards, to do so. As a result, there is a risk that the data processing steps of the workflow will be accepted as a black box process and its results as “hard data”. The first step in documenting a scientific process is to define it. Therefore, this paper provides a critical review of existing archaeology-specific workflows for airborne LiDAR-derived topographic data processing, resulting in an 18-step workflow with consistent terminology. Its novelty and significance lies in the fact that the existing comprehensive studies are outdated and the newer ones focus on selected aspects of the workflow. Based on the updated workflow, a good practice example for its documentation is presented.

The use of Otsu algorithm and multi-temporal airborne LiDAR data to detect building changes in urban space

2021 ◽  
Author(s):  
Renato César dos Santos ◽  
Mauricio Galo ◽  
André Caceres Carrilho ◽  
Guilherme Gomes Pessoa
Keyword(s):  
Urban Space ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Multi Temporal ◽  
Airborne Lidar Data

scholarly journals A Comparative Study about Data Structures Used for Efficient Management of Voxelised Full-Waveform Airborne LiDAR Data during 3D Polygonal Model Creation

2021 ◽  
Vol 13 (4) ◽  
pp. 559
Author(s):  
Milto Miltiadou ◽  
Neill D. F. Campbell ◽  
Darren Cosker ◽  
Michael G. Grant
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Airborne Lidar ◽  
Memory Allocation ◽  
Lidar Data ◽  
Full Waveform ◽  
Waveform Lidar ◽  
Airborne Lidar Data ◽  
Full Waveform Lidar ◽  
Polygonal Model

In this paper, we investigate the performance of six data structures for managing voxelised full-waveform airborne LiDAR data during 3D polygonal model creation. While full-waveform LiDAR data has been available for over a decade, extraction of peak points is the most widely used approach of interpreting them. The increased information stored within the waveform data makes interpretation and handling difficult. It is, therefore, important to research which data structures are more appropriate for storing and interpreting the data. In this paper, we investigate the performance of six data structures while voxelising and interpreting full-waveform LiDAR data for 3D polygonal model creation. The data structures are tested in terms of time efficiency and memory consumption during run-time and are the following: (1) 1D-Array that guarantees coherent memory allocation, (2) Voxel Hashing, which uses a hash table for storing the intensity values (3) Octree (4) Integral Volumes that allows finding the sum of any cuboid area in constant time, (5) Octree Max/Min, which is an upgraded octree and (6) Integral Octree, which is proposed here and it is an attempt to combine the benefits of octrees and Integral Volumes. In this paper, it is shown that Integral Volumes is the more time efficient data structure but it requires the most memory allocation. Furthermore, 1D-Array and Integral Volumes require the allocation of coherent space in memory including the empty voxels, while Voxel Hashing and the octree related data structures do not require to allocate memory for empty voxels. These data structures, therefore, and as shown in the test conducted, allocate less memory. To sum up, there is a need to investigate how the LiDAR data are stored in memory. Each tested data structure has different benefits and downsides; therefore, each application should be examined individually.

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