Estimating Leaf Water Content through Low-Cost LiDAR
In recent years, rapid development has been achieved in technologies and sensors related to autonomous driving and assistive technologies. In this study, low-cost light detection and ranging (LiDAR) was used to estimate leaf water content (LWC) by measuring LiDAR reflectance instead of morphological...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/12/5/1183 |
| _version_ | 1797502188125159424 |
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| author | Akira Hama Yutaro Matsumoto Nobuhiro Matsuoka |
| author_facet | Akira Hama Yutaro Matsumoto Nobuhiro Matsuoka |
| author_sort | Akira Hama |
| collection | DOAJ |
| description | In recent years, rapid development has been achieved in technologies and sensors related to autonomous driving and assistive technologies. In this study, low-cost light detection and ranging (LiDAR) was used to estimate leaf water content (LWC) by measuring LiDAR reflectance instead of morphological measurement (e.g., plant size), which is the conventional method. Experimental results suggest that reflection intensity can be corrected using the body temperature of LiDAR, when using reflection intensity observed by LiDAR. Comparisons of corrected LiDAR observation data and changes in reflectance attributed to leaf drying suggest that the reflectance increases with leaf drying in the 905 nm band observed with a hyperspectral camera. The LWC is estimated with an R<sup>2</sup> of 0.950, RMSE of 6.78%, and MAPE of 18.6% using LiDAR reflectance. Although the 905 nm wavelength used by LiDAR is not the main water absorption band, the reflectance is closely related to the leaf structure; therefore, it is believed that the reflectance changes with structural changes accompanying drying, which allows for the indirect estimation of LWC. This can help utilize the reflectance of the 905 nm single-wavelength LiDAR, which, to the best of our knowledge has not been used in plant observations for estimating LWC. |
| first_indexed | 2024-03-10T03:29:22Z |
| format | Article |
| id | doaj.art-803ddf2602914f23bce3c81310f48858 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T03:29:22Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-803ddf2602914f23bce3c81310f488582023-11-23T09:44:01ZengMDPI AGAgronomy2073-43952022-05-01125118310.3390/agronomy12051183Estimating Leaf Water Content through Low-Cost LiDARAkira Hama0Yutaro Matsumoto1Nobuhiro Matsuoka2Graduate School of Horticulture, Chiba University, 648, Matsudo, Matsudo-shi 271-8510, JapanGraduate School of Horticulture, Chiba University, 648, Matsudo, Matsudo-shi 271-8510, JapanGraduate School of Horticulture, Chiba University, 648, Matsudo, Matsudo-shi 271-8510, JapanIn recent years, rapid development has been achieved in technologies and sensors related to autonomous driving and assistive technologies. In this study, low-cost light detection and ranging (LiDAR) was used to estimate leaf water content (LWC) by measuring LiDAR reflectance instead of morphological measurement (e.g., plant size), which is the conventional method. Experimental results suggest that reflection intensity can be corrected using the body temperature of LiDAR, when using reflection intensity observed by LiDAR. Comparisons of corrected LiDAR observation data and changes in reflectance attributed to leaf drying suggest that the reflectance increases with leaf drying in the 905 nm band observed with a hyperspectral camera. The LWC is estimated with an R<sup>2</sup> of 0.950, RMSE of 6.78%, and MAPE of 18.6% using LiDAR reflectance. Although the 905 nm wavelength used by LiDAR is not the main water absorption band, the reflectance is closely related to the leaf structure; therefore, it is believed that the reflectance changes with structural changes accompanying drying, which allows for the indirect estimation of LWC. This can help utilize the reflectance of the 905 nm single-wavelength LiDAR, which, to the best of our knowledge has not been used in plant observations for estimating LWC.https://www.mdpi.com/2073-4395/12/5/1183LiDARsensingreflectancewater stressleaf water content |
| spellingShingle | Akira Hama Yutaro Matsumoto Nobuhiro Matsuoka Estimating Leaf Water Content through Low-Cost LiDAR Agronomy LiDAR sensing reflectance water stress leaf water content |
| title | Estimating Leaf Water Content through Low-Cost LiDAR |
| title_full | Estimating Leaf Water Content through Low-Cost LiDAR |
| title_fullStr | Estimating Leaf Water Content through Low-Cost LiDAR |
| title_full_unstemmed | Estimating Leaf Water Content through Low-Cost LiDAR |
| title_short | Estimating Leaf Water Content through Low-Cost LiDAR |
| title_sort | estimating leaf water content through low cost lidar |
| topic | LiDAR sensing reflectance water stress leaf water content |
| url | https://www.mdpi.com/2073-4395/12/5/1183 |
| work_keys_str_mv | AT akirahama estimatingleafwatercontentthroughlowcostlidar AT yutaromatsumoto estimatingleafwatercontentthroughlowcostlidar AT nobuhiromatsuoka estimatingleafwatercontentthroughlowcostlidar |