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Point Density Variations in Airborne Lidar Point Clouds
In spite of increasing point density and accuracy, airborne lidar point clouds often exhibit point density variations. Some of these density variations indicate issues with point clouds, potentially leading to errors in derived products. To highlight these issues, we provide an overview of point den...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920349/ https://www.ncbi.nlm.nih.gov/pubmed/36772634 http://dx.doi.org/10.3390/s23031593 |
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author | Petras, Vaclav Petrasova, Anna McCarter, James B. Mitasova, Helena Meentemeyer, Ross K. |
author_facet | Petras, Vaclav Petrasova, Anna McCarter, James B. Mitasova, Helena Meentemeyer, Ross K. |
author_sort | Petras, Vaclav |
collection | PubMed |
description | In spite of increasing point density and accuracy, airborne lidar point clouds often exhibit point density variations. Some of these density variations indicate issues with point clouds, potentially leading to errors in derived products. To highlight these issues, we provide an overview of point density variations and show examples in six airborne lidar point cloud datasets that we used in our topographic and geospatial modeling research. Using the published literature, we identified sources of point density variations and issues indicated or caused by these variations. Lastly, we discuss the reduction in point density variations using decimations, homogenizations, and their applicability. |
format | Online Article Text |
id | pubmed-9920349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99203492023-02-12 Point Density Variations in Airborne Lidar Point Clouds Petras, Vaclav Petrasova, Anna McCarter, James B. Mitasova, Helena Meentemeyer, Ross K. Sensors (Basel) Article In spite of increasing point density and accuracy, airborne lidar point clouds often exhibit point density variations. Some of these density variations indicate issues with point clouds, potentially leading to errors in derived products. To highlight these issues, we provide an overview of point density variations and show examples in six airborne lidar point cloud datasets that we used in our topographic and geospatial modeling research. Using the published literature, we identified sources of point density variations and issues indicated or caused by these variations. Lastly, we discuss the reduction in point density variations using decimations, homogenizations, and their applicability. MDPI 2023-02-01 /pmc/articles/PMC9920349/ /pubmed/36772634 http://dx.doi.org/10.3390/s23031593 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Petras, Vaclav Petrasova, Anna McCarter, James B. Mitasova, Helena Meentemeyer, Ross K. Point Density Variations in Airborne Lidar Point Clouds |
title | Point Density Variations in Airborne Lidar Point Clouds |
title_full | Point Density Variations in Airborne Lidar Point Clouds |
title_fullStr | Point Density Variations in Airborne Lidar Point Clouds |
title_full_unstemmed | Point Density Variations in Airborne Lidar Point Clouds |
title_short | Point Density Variations in Airborne Lidar Point Clouds |
title_sort | point density variations in airborne lidar point clouds |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920349/ https://www.ncbi.nlm.nih.gov/pubmed/36772634 http://dx.doi.org/10.3390/s23031593 |
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