scholarly journals Canopy and Terrain Height Retrievals with ICESat-2: A First Look

2019 ◽  
Vol 11 (14) ◽  
pp. 1721 ◽  
Author(s):  
Amy L. Neuenschwander ◽  
Lori A. Magruder
Keyword(s):  
Sea Ice ◽  
Quantitative Assessment ◽  
Vantage Point ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Scientific Objective ◽  
Ice Cloud ◽  
Elevation Data ◽  
Airborne Lidar Data ◽  
Along Track

NASA’s Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) launched in fall 2018 and has since collected continuous elevation data over the Earth’s surface. The primary scientific objective is to measure the cryosphere for studies related to land ice and sea ice characteristics. The vantage point from space, however, provides the opportunity to measure global surfaces including oceans, land, and vegetation. The ICESat-2 mission has dedicated products to the represented surface types, including an along-track elevation profile of terrain and canopy heights (ATL08). This study presents the first look at the ATL08 product and the quantitative assessment of the canopy and terrain height retrievals as compared to airborne lidar data. The study also provides qualitative examples of ICESat-2 observations from selected ecosystems to highlight the broad capability of the satellite for vegetation applications. Analysis of the mission’s preliminary ATL08 data product accuracy using an ICESat-2 transect over a vegetated region of Finland indicates a 5 m offset in geolocation knowledge (horizontal accuracy) well within the 6.5 m mission requirement. The vertical RMSE for the terrain and canopy height retrievals for one transect are 0.85 m and 3.2 m respectively.

scholarly journals Validation of TanDEM-X elevation data for a forested karst area in Slovakia (Central Europe)

2018 ◽  
Author(s):  
Peter Bandura ◽  
Michal Gallay
Keyword(s):  
Multiple Scales ◽  
Space Mission ◽  
Airborne Lidar ◽  
Karst Area ◽  
Lidar Data ◽  
Reference Dataset ◽  
Landform Classification ◽  
Elevation Data ◽  
Airborne Lidar Data ◽  
Srtm Data

Recent production of a new radar-based global DEM by the TanDEM-X space mission has opened new options for geomorphometric analysis across multiple scales providing 0.4 arc second spatial resolution. However, the accuracy and suitability of this data has not been evaluated in such an extensive manner as for the widely exploited SRTM data. We present a validation of the vertical accuracy of TanDEM-X DEM product and evaluation of its suitability for landform classification in a forested karst area. The Geomorphons method was used for the automated landform classification focused on identification of dolines for which polygons of dolines mapped by expert-driven approach were used for validation. Airborne lidar data in the form of DSM and DTM were used as the reference dataset for validation of the DEM. The results show that the vertical RMSE of the TanDEM-X data is 3.42 m with respect to lidar DSM and 9.64 m with respect to lidar DTM. The identification of dolines by the geomorphon approach achieved 73 % with TanDEM-X, lower than for the lidar DTM (85 %).

scholarly journals Validation of TanDEM-X elevation data for a forested karst area in Slovakia (Central Europe)

2018 ◽  
Author(s):  
Peter Bandura ◽  
Michal Gallay
Keyword(s):  
Multiple Scales ◽  
Space Mission ◽  
Airborne Lidar ◽  
Karst Area ◽  
Lidar Data ◽  
Reference Dataset ◽  
Landform Classification ◽  
Elevation Data ◽  
Airborne Lidar Data ◽  
Srtm Data

Recent production of a new radar-based global DEM by the TanDEM-X space mission has opened new options for geomorphometric analysis across multiple scales providing 0.4 arc second spatial resolution. However, the accuracy and suitability of this data has not been evaluated in such an extensive manner as for the widely exploited SRTM data. We present a validation of the vertical accuracy of TanDEM-X DEM product and evaluation of its suitability for landform classification in a forested karst area. The Geomorphons method was used for the automated landform classification focused on identification of dolines for which polygons of dolines mapped by expert-driven approach were used for validation. Airborne lidar data in the form of DSM and DTM were used as the reference dataset for validation of the DEM. The results show that the vertical RMSE of the TanDEM-X data is 3.42 m with respect to lidar DSM and 9.64 m with respect to lidar DTM. The identification of dolines by the geomorphon approach achieved 73 % with TanDEM-X, lower than for the lidar DTM (85 %).

Software for GIS-processing of airborne lidar data

2020 ◽  
pp. 2-11
Author(s):  
B.A. Novakovsky ◽  
◽  
A.V. Kudryavtsev ◽  
A.L. Entin ◽  
◽  
...  
Keyword(s):  
Computational Efficiency ◽  
Laser Scanning ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Advantages And Disadvantages ◽  
3D Data ◽  
Erdas Imagine ◽  
Elevation Data ◽  
Airborne Lidar Data ◽  
Gis Software

The paper considers GIS software which may be utilized for airborne lidar data processing. Software list includes proprietary MicroStation with TerraScan plugin, Global Mapper, ArcGIS, ERDAS Imagine, LAStools, as well as free and open source SAGA, WhiteboxTools, and PDAL.io. Possibilities of import-export, 2D and 3D data visualization, point cloud editing and derivation of GIS datasets are examined for each software. Computational efficiency assessment is performed for the procedure of interpolation point elevation data in different software. As a result, the advantages and disadvantages of the considered programs were identified in relation to various tasks. Key words: airborne laser scanning, software, geoinformation mapping, computational efficiency.

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.

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.

scholarly journals Supervised Classification of Power Lines from Airborne LiDAR Data in Urban Areas

2017 ◽  
Vol 9 (8) ◽  
pp. 771 ◽  
Author(s):  
Yanjun Wang ◽  
Qi Chen ◽  
Lin Liu ◽  
Dunyong Zheng ◽  
Chaokui Li ◽  
...  
Keyword(s):  
Urban Areas ◽  
Supervised Classification ◽  
Airborne Lidar ◽  
Power Lines ◽  
Lidar Data ◽  
Airborne Lidar Data
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