The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues
Open accessAbstract
This paper reviews LiDAR ground filtering algorithms used in the process of creating Digital Elevation Models. We discuss critical issues for the development and application of LiDAR ground filtering algorithms, including filtering procedures for different feature types, and criteria for study site selection, accuracy assessment, and algorithm classification. This review highlights three feature types for which current ground filtering algorithms are suboptimal, and which can be improved upon in future studies: surfaces with rough terrain or discontinuous slope, dense forest areas that laser beams cannot penetrate, and regions with low vegetation that is often ignored by ground filters.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Kass, M., Witkin, A., & Terzopoulos, D. (1988) · International Journal of Computer Vision · doi:10.1007/bf00133570 · Cited by 17,070
Haralock, R. M., & Shapiro, L. G. (1991) · Addison-Wesley Longman Publishing Co., Inc. eBooks · Cited by 3,933
Airborne laser scanning—an introduction and overview
Wehr, A., & Lohr, U. (1999) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/s0924-2716(99)00011-8 · Cited by 1,414
Finite-element methods for active contour models and balloons for 2-D and 3-D images
Cohen, L. D., & Cohen, I. (1993) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.244675 · Cited by 1,378
DEM Generation from Laser Scanner Data Using Adaptive TIN Models
Axelsson, P. (2000) · ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences · Cited by 1,233
Determination of terrain models in wooded areas with airborne laser scanner data
Kraus, K., & Pfeifer, N. (1998) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/s0924-2716(98)00009-4 · Cited by 1,218
Machine contouring using minimum curvature
Briggs, I. C. (1974) · Geophysics · doi:10.1190/1.1440410 · Cited by 1,167
A progressive morphological filter for removing nonground measurements from airborne LIDAR data
Zhang, K., Chen, S.-C., Whitman, D., Shyu, M.-L., Yan, J., & Zhang, C. (2003) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2003.810682 · Cited by 1,026
Sithole, G., & Vosselman, G. (2004) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2004.05.004 · Cited by 977
A comparison between photogrammetry and laser scanning
Baltsavias, E. P. (1999) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/s0924-2716(99)00014-3 · Cited by 771
Processing of laser scanner data—algorithms and applications
Axelsson, P. (1999) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/s0924-2716(99)00008-8 · Cited by 755
Lidar Remote Sensing for Forestry
Dubayah, R. O., & Drake, J. B. (2000) · Journal of Forestry · doi:10.1093/jof/98.6.44 · Cited by 640
SLOPE BASED FILTERING OF LASER ALTIMETRY DATA
George Vosselman, A. (2000) · Cited by 635
Airborne LiDAR for DEM generation: some critical issues
Liu, X. (2008) · Progress in Physical Geography: Earth and Environment · doi:10.1177/0309133308089496 · Cited by 635
Accuracy of Airborne Lidar-Derived Elevation
Hodgson, M. E., & Bresnahan, P. (2004) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.70.3.331 · Cited by 483
Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction
Sohn, G., & Dowman, I. J. (2007) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2007.01.001 · Cited by 482
Segmentation of point clouds using smoothness constraints
Rabbani, T., den Heuvel, F. V., & Vosselman, G. (2006) · University of Twente Research Information · Cited by 464
Chaplot, V., Darboux, F., Bourennane, H., Leguédois, S., Silvera, N., & Phachomphon, K. (2006) · Geomorphology · doi:10.1016/j.geomorph.2005.12.010 · Cited by 402
A Multiscale Curvature Algorithm for Classifying Discrete Return LiDAR in Forested Environments
Evans, J. S., & Hudak, A. T. (2007) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2006.890412 · Cited by 392
Light Detection and Ranging (LIDAR): An Emerging Tool for Multiple Resource Inventory
Reutebuch, S. E., Andersen, H.-E., & McGaughey, R. J. (2005) · Journal of Forestry · doi:10.1093/jof/103.6.286 · Cited by 390
Accuracy of a high-resolution lidar terrain model under a conifer forest canopy
Reutebuch, S. E., McGaughey, R. J., Andersen, H.-E., & Carson, W. W. (2003) · Canadian Journal of Remote Sensing · doi:10.5589/m03-022 · Cited by 382
A voxel-based lidar method for estimating crown base height for deciduous and pine trees
Popescu, S. C., & Zhao, K. (2008) · Remote Sensing of Environment · doi:10.1016/j.rse.2007.06.011 · Cited by 346
Self-citationLidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers
Zhao, K., Popescu, S., & Nelson, R. (2009) · Remote Sensing of Environment · doi:10.1016/j.rse.2008.09.009 · Cited by 346
Self-citationHuising, E. J., & Gomes Pereira, L. M. (1998) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/s0924-2716(98)00013-6 · Cited by 340
The Effect of DEM Raster Resolution on First Order, Second Order and Compound Terrain Derivatives
Kienzle, S. (2004) · Transactions in GIS · doi:10.1111/j.1467-9671.2004.00169.x · Cited by 292
Photogrammetric and Lidar Data Registration Using Linear Features
Habib, A., Ghanma, M., Morgan, M., & Al-Ruzouq, R. (2005) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.71.6.699 · Cited by 239
Zhao, K., & Popescu, S. (2009) · Remote Sensing of Environment · doi:10.1016/j.rse.2009.03.006 · Cited by 232
Self-citationADVANCED DTM GENERATION FROM LIDAR DATA
Kraus, K., & Pfeifer, N. (2001) · Cited by 194
An Evaluation of Lidar-derived Elevation and Terrain Slope in Leaf-off Conditions
Hodgson, M. E., Jensen, J., Raber, G., Tullis, J., Davis, B. A., Thompson, G., & Schuckman, K. (2005) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.71.7.817 · Cited by 168
Deriving DSMs from LiDAR data with kriging
Lloyd, C. D., & Atkinson, P. M. (2002) · International Journal of Remote Sensing · doi:10.1080/01431160110097998 · Cited by 155
Effects of Interpolation Errors on the Analysis of DEMs
Desmet, P. (1997) · Earth Surface Processes and Landforms · Cited by 147
DEM Generation and Building Detection from Lidar Data
Ma, R. (2005) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.71.7.847 · Cited by 129
Separation of Ground and Low Vegetation Signatures in LiDAR Measurements of Salt-Marsh Environments
Wang, C., Menenti, M., Stoll, M. P., Feola, A., Belluco, E., & Marani, M. (2009) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2008.2010490 · Cited by 120
The choice of window size in approximating topographic surfaces from Digital Elevation Models
Albani, M., Klinkenberg, B., Andison, D., & Kimmins, J. P. (2004) · International Journal of Geographical Information Systems · doi:10.1080/13658810410001701987 · Cited by 117
Impact of Lidar Nominal Post-spacing on DEM Accuracy and Flood Zone Delineation
Raber, G. T., Jensen, J. R., Hodgson, M. E., Tullis, J. A., Davis, B. A., & Berglund, J. (2007) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.73.7.793 · Cited by 108
LIDAR Data Filtering and DTM Interpolation Within GRASS
Brovelli, M. A., Cannata, M., & Longoni, U. (2004) · Transactions in GIS · doi:10.1111/j.1467-9671.2004.00173.x · Cited by 108
Morphology-based Building Detection from Airborne Lidar Data
Meng, X., Wang, L., & Currit, N. (2009) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.75.4.437 · Cited by 106
Self-citationCreation of digital terrain models using an adaptive lidar vegetation point removal process
Schuckman, K., Raber, G. T., Jensen, J. R., & Schill, S. R. (2002) · Photogrammetric Engineering & Remote Sensing · Cited by 103
A multi-resolution approach for filtering LiDAR altimetry data
Silván-Cárdenas, J. L., & Wang, L. (2006) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2006.06.002 · Cited by 97
Laser altimetry : From science to commercial lidar mapping
Flood, M. (2001) · Photogrammetric Engineering & Remote Sensing · Cited by 84
The effect of LiDAR data density on DEM accuracy
Liu, X., Zhang, Z., Peterson, J. A., & Chandra, S. (2007) · University of Southern Queensland ePrints (University of Southern Queensland) · Cited by 67
Elevation accuracy of laser scanning-derived digital terrain and target models in forest environment
Hyyppa, J. M., Pyysalo, U., Hyyppä, H., & Samberg, A. (2001) · Cited by 65
Digital Elevation Models By Laser Scanning
Lohr, U. (1998) · The Photogrammetric Record · doi:10.1111/0031-868x.00117 · Cited by 58
Quantifying Interpolation Errors in Urban Airborne Laser Scanning Models
Smith, S. L., Holland, D. A., & Longley, P. (2005) · Geographical Analysis · doi:10.1111/j.1538-4632.2005.00636.x · Cited by 55
Hill, J. M., Graham, L. A., Henry, R. J., Cotter, D., & Young, D. A. (2000) · Photogrammetric Engineering & Remote Sensing · Cited by 52
A hybrid interpolation method for the refinement of a regular grid digital elevation model
Shi, W., & Tian, Y. W. (2006) · International Journal of Geographical Information Systems · doi:10.1080/13658810500286943 · Cited by 48
Cited by
Che, E., Jung, J., & Olsen, M. J. (2019) · Sensors · doi:10.3390/s19040810 · Cited by 253
3D Convolutional Neural Networks for landing zone detection from LiDAR
Maturana, D., & Scherer, S. (2015) · 2015 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2015.7139679 · Cited by 203
The Use of LiDAR-Derived DEM in Flood Applications: A Review
Muhadi, N. A., Abdullah, A. F., Bejo, S. K., Mahadi, M. R., & Mijic, A. (2020) · Remote Sensing · doi:10.3390/rs12142308 · Cited by 172
Quantifying understory vegetation density using small-footprint airborne lidar
Campbell, M. J., Dennison, P. E., Hudak, A. T., Parham, L. M., & Butler, B. W. (2018) · Remote Sensing of Environment · doi:10.1016/j.rse.2018.06.023 · Cited by 126
Campbell, M. J., Dennison, P. E., & Butler, B. W. (2017) · International Journal of Geographical Information Science · doi:10.1080/13658816.2016.1270453 · Cited by 35
Metadata
- Authors
- Meng, X., Currit, N., & Zhao, K.
- Venue
- Remote Sensing
- Publisher
- MDPI AG
- Published
- 2010-03-22
- Volume
- 2
- Issue
- 3
- Pages
- 833-860
- ISSN
- 2072-4292 (ISSN-L)
- OpenAlex
- W2014091167
- Cited by
- 573
- References
- 46
- FWCI
- 19.48
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.