Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties
Reliable measurements of the 3D distribution of Leaf Area Density (LAD) in forest canopy are crucial for describing and modelling microclimatic and eco-physiological processes involved in forest ecosystems functioning. To overcome the obvious limitations of direct measurements, several indirect meth...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/10/10/1580 |
| _version_ | 1819125293999194112 |
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| author | Maxime Soma François Pimont Sylvie Durrieu Jean-Luc Dupuy |
| author_facet | Maxime Soma François Pimont Sylvie Durrieu Jean-Luc Dupuy |
| author_sort | Maxime Soma |
| collection | DOAJ |
| description | Reliable measurements of the 3D distribution of Leaf Area Density (LAD) in forest canopy are crucial for describing and modelling microclimatic and eco-physiological processes involved in forest ecosystems functioning. To overcome the obvious limitations of direct measurements, several indirect methods have been developed, including methods based on Terrestrial LiDAR scanning (TLS). This work focused on various LAD estimators used in voxel-based approaches. LAD estimates were compared to reference measurements at branch scale in laboratory, which offered the opportunity to investigate in controlled conditions the sensitivity of estimations to various factors such as voxel size, distance to scanner, leaf morphology (species), type of scanner and type of estimator. We found that all approaches to retrieve LAD estimates were highly sensitive to voxel size whatever the species or scanner and to distance to the FARO scanner. We provided evidence that these biases were caused by vegetation heterogeneity and variations in the effective footprint of the scanner. We were able to identify calibration functions that could be readily applied when vegetation and scanner are similar to those of the present study. For different vegetation and scanner, we recommend replicating our method, which can be applied at reasonable cost. While acknowledging that the test conditions in the laboratory were very different from those of the measurements taken in the forest (especially in terms of occlusion), this study revealed existence of strong biases, including spatial biases. Because the distance between scanner and vegetation varies in field scanning, these biases should occur in a similar manner in the field and should be accounted for in voxel-based methods but also in gap-fraction methods. |
| first_indexed | 2024-12-22T07:37:51Z |
| format | Article |
| id | doaj.art-15b8c113ae13430584fe2a37d61a81ce |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-22T07:37:51Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-15b8c113ae13430584fe2a37d61a81ce2022-12-21T18:33:49ZengMDPI AGRemote Sensing2072-42922018-10-011010158010.3390/rs10101580rs10101580Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner PropertiesMaxime Soma0François Pimont1Sylvie Durrieu2Jean-Luc Dupuy3UR 629 Ecologies des Forêts Méditerranéennes (URFM), INRA, 84000 Avignon, FranceUR 629 Ecologies des Forêts Méditerranéennes (URFM), INRA, 84000 Avignon, FranceUMR Territoires, Environnement, Télédétection et Information Spatiale (TETIS), IRSTEA, 34196 Montpellier, FranceUR 629 Ecologies des Forêts Méditerranéennes (URFM), INRA, 84000 Avignon, FranceReliable measurements of the 3D distribution of Leaf Area Density (LAD) in forest canopy are crucial for describing and modelling microclimatic and eco-physiological processes involved in forest ecosystems functioning. To overcome the obvious limitations of direct measurements, several indirect methods have been developed, including methods based on Terrestrial LiDAR scanning (TLS). This work focused on various LAD estimators used in voxel-based approaches. LAD estimates were compared to reference measurements at branch scale in laboratory, which offered the opportunity to investigate in controlled conditions the sensitivity of estimations to various factors such as voxel size, distance to scanner, leaf morphology (species), type of scanner and type of estimator. We found that all approaches to retrieve LAD estimates were highly sensitive to voxel size whatever the species or scanner and to distance to the FARO scanner. We provided evidence that these biases were caused by vegetation heterogeneity and variations in the effective footprint of the scanner. We were able to identify calibration functions that could be readily applied when vegetation and scanner are similar to those of the present study. For different vegetation and scanner, we recommend replicating our method, which can be applied at reasonable cost. While acknowledging that the test conditions in the laboratory were very different from those of the measurements taken in the forest (especially in terms of occlusion), this study revealed existence of strong biases, including spatial biases. Because the distance between scanner and vegetation varies in field scanning, these biases should occur in a similar manner in the field and should be accounted for in voxel-based methods but also in gap-fraction methods.http://www.mdpi.com/2072-4292/10/10/1580Terrestrial LiDAR Scanning (TLS)Leaf Area Density (LAD)Leaf Area Index (LAI)LiDAR scannervegetation heterogeneitygap fractionvoxel sizespatial biasFARO Focus 130XRIEGL VZ 400 |
| spellingShingle | Maxime Soma François Pimont Sylvie Durrieu Jean-Luc Dupuy Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties Remote Sensing Terrestrial LiDAR Scanning (TLS) Leaf Area Density (LAD) Leaf Area Index (LAI) LiDAR scanner vegetation heterogeneity gap fraction voxel size spatial bias FARO Focus 130X RIEGL VZ 400 |
| title | Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties |
| title_full | Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties |
| title_fullStr | Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties |
| title_full_unstemmed | Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties |
| title_short | Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties |
| title_sort | enhanced measurements of leaf area density with t lidar evaluating and calibrating the effects of vegetation heterogeneity and scanner properties |
| topic | Terrestrial LiDAR Scanning (TLS) Leaf Area Density (LAD) Leaf Area Index (LAI) LiDAR scanner vegetation heterogeneity gap fraction voxel size spatial bias FARO Focus 130X RIEGL VZ 400 |
| url | http://www.mdpi.com/2072-4292/10/10/1580 |
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