Canopy temperatures of selected tree species growing in the forest and outside the forest using aerial thermal infrared (3.6–4.9 µm) data
Studies conducted in recent years have demonstrated high application potential of thermal remote sensing data in environmental analyses. The main goal of our studies was to determine the variability of tree canopy temperatures using a new sensor which acquires data in the still rarely used thermal s...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2022-12-01
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| Series: | European Journal of Remote Sensing |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/22797254.2022.2062055 |
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| Summary: | Studies conducted in recent years have demonstrated high application potential of thermal remote sensing data in environmental analyses. The main goal of our studies was to determine the variability of tree canopy temperatures using a new sensor which acquires data in the still rarely used thermal spectral range (3.6–4.9 μm). This study was conducted on five selected tree species growing in the forest and outside the forest: Alnus glutinosa, Pinus sylvestris, Quercus petraea, Quercus rubra and Robinia pseudoacacia. Thermal data were acquired on 9 June 2019, between 8:10 and 14:00 (CET). The findings were as follows: i) Trees growing in the forest are on average 0.4–0.7°C cooler than trees outside the forest; ii) The canopy temperatures of species under study differ statistically irrespective of data acquisition time. Alnus glutinosa, Quercus rubra and Quercus petraea are species with the lowest canopy temperatures, and Pinus sylvestris has the highest canopy temperature. The studies showed that the biggest variation between species in the canopy temperature occurs at noon (12:00–13:00); iii) A thermal spectral range of 3.6–4.9 μm registers the canopy temperature of tree species with a high accuracy, which supports its usage in remote sensing vegetation studies. |
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| ISSN: | 2279-7254 |