Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death
The early detection of plant pathogens at the landscape scale holds great promise for better managing forest ecosystem threats. In Hawai‘i, two recently described fungal species are responsible for increasingly widespread mortality in ‘ōhi‘a <i>Metrosideros polymorpha</i>, a foundational...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/11/1846 |
| _version_ | 1797565857300217856 |
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| author | Ryan L. Perroy Marc Hughes Lisa M. Keith Eszter Collier Timo Sullivan Gabriel Low |
| author_facet | Ryan L. Perroy Marc Hughes Lisa M. Keith Eszter Collier Timo Sullivan Gabriel Low |
| author_sort | Ryan L. Perroy |
| collection | DOAJ |
| description | The early detection of plant pathogens at the landscape scale holds great promise for better managing forest ecosystem threats. In Hawai‘i, two recently described fungal species are responsible for increasingly widespread mortality in ‘ōhi‘a <i>Metrosideros polymorpha</i>, a foundational tree species in Hawaiian native forests. In this study, we share work from repeat laboratory and field measurements to determine if visible near-infrared and optical remote sensing can detect pre-symptomatic trees infected with these pathogens. After generating a dense time series of laboratory spectral reflectance data and red green blue (RGB) images for inoculated ‘ōhi‘a seedlings, seedlings subjected to extreme drought, and control plants, we found few obvious spectral indicators that could be used for reliable pre-symptomatic detection in the inoculated seedlings, which quickly experienced complete and total wilting following stress onset. In the field, we found similar results when we collected repeat multispectral and RGB imagery over inoculated mature trees (sudden onset of symptoms with little advance warning). We found selected vegetation indices to be reliable indicators for detecting non-specific stress in ‘ōhi‘a trees, but never providing more than five days prior warning relative to visual detection in the laboratory trials. Finally, we generated a sequence of linear support vector machine classification models from the laboratory data at time steps ranging from pre-treatment to late-stage stress. Overall classification accuracies increased with stress stage maturity, but poor model performance prior to stress onset and the sudden onset of symptoms in infected trees suggest that early detection of rapid ‘ōhi‘a death over timescales helpful for land managers remains a challenge. |
| first_indexed | 2024-03-10T19:18:55Z |
| format | Article |
| id | doaj.art-6f13285db7c446f4929f1b1d44563eff |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T19:18:55Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-6f13285db7c446f4929f1b1d44563eff2023-11-20T03:08:06ZengMDPI AGRemote Sensing2072-42922020-06-011211184610.3390/rs12111846Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a DeathRyan L. Perroy0Marc Hughes1Lisa M. Keith2Eszter Collier3Timo Sullivan4Gabriel Low5Department of Geography & Environmental Science, University of Hawai‘i at Hilo, Hilo, HI 96720, USACollege of Tropical Agriculture and Human Resources, University of Hawai‘i at Manoa, Hilo, HI 96720, USADaniel K. Inouye U.S. Pacific Basin Agricultural Research Center, United States Department of Agriculture, Agricultural Research Service, Hilo, HI 96720, USASpatial Data Analysis & Visualization Laboratory, University of Hawai‘i at Hilo, Hilo, HI 96720, USASpatial Data Analysis & Visualization Laboratory, University of Hawai‘i at Hilo, Hilo, HI 96720, USAUniversity of Alaska at Fairbanks, Fairbanks, AK 99775, USAThe early detection of plant pathogens at the landscape scale holds great promise for better managing forest ecosystem threats. In Hawai‘i, two recently described fungal species are responsible for increasingly widespread mortality in ‘ōhi‘a <i>Metrosideros polymorpha</i>, a foundational tree species in Hawaiian native forests. In this study, we share work from repeat laboratory and field measurements to determine if visible near-infrared and optical remote sensing can detect pre-symptomatic trees infected with these pathogens. After generating a dense time series of laboratory spectral reflectance data and red green blue (RGB) images for inoculated ‘ōhi‘a seedlings, seedlings subjected to extreme drought, and control plants, we found few obvious spectral indicators that could be used for reliable pre-symptomatic detection in the inoculated seedlings, which quickly experienced complete and total wilting following stress onset. In the field, we found similar results when we collected repeat multispectral and RGB imagery over inoculated mature trees (sudden onset of symptoms with little advance warning). We found selected vegetation indices to be reliable indicators for detecting non-specific stress in ‘ōhi‘a trees, but never providing more than five days prior warning relative to visual detection in the laboratory trials. Finally, we generated a sequence of linear support vector machine classification models from the laboratory data at time steps ranging from pre-treatment to late-stage stress. Overall classification accuracies increased with stress stage maturity, but poor model performance prior to stress onset and the sudden onset of symptoms in infected trees suggest that early detection of rapid ‘ōhi‘a death over timescales helpful for land managers remains a challenge.https://www.mdpi.com/2072-4292/12/11/1846Hawai‘ivegetation indicesCeratocystis lukuohiaCeratocystis huliohia |
| spellingShingle | Ryan L. Perroy Marc Hughes Lisa M. Keith Eszter Collier Timo Sullivan Gabriel Low Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death Remote Sensing Hawai‘i vegetation indices Ceratocystis lukuohia Ceratocystis huliohia |
| title | Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death |
| title_full | Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death |
| title_fullStr | Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death |
| title_full_unstemmed | Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death |
| title_short | Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid ‘Ōhi‘a Death |
| title_sort | examining the utility of visible near infrared and optical remote sensing for the early detection of rapid ohi a death |
| topic | Hawai‘i vegetation indices Ceratocystis lukuohia Ceratocystis huliohia |
| url | https://www.mdpi.com/2072-4292/12/11/1846 |
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