Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery
Thermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through ti...
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MDPI AG
2025-04-01
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| Series: | Remote Sensing |
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| author | Matthew I. Barker Jonathan D. Burnett Ivan Arismendi Michael G. Wing |
| author_facet | Matthew I. Barker Jonathan D. Burnett Ivan Arismendi Michael G. Wing |
| author_sort | Matthew I. Barker |
| collection | DOAJ |
| description | Thermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through time to assess the impacts to a river’s thermal regime. Lightweight sensors that record both thermal infrared (TIR) and multispectral data carried via unoccupied aircraft systems (UASs) present an opportunity to monitor temperature variations at high spatial (<0.5 m) and temporal resolution, facilitating the detection of the small patches of varying temperatures salmon require. Here, we present methods to classify and filter visible wetted area, including a novel procedure to measure canopy cover, and extract and correct radiant surface water temperature to evaluate changes in the variability of stream temperature pre- and post-restoration followed by a high-intensity fire in a section of the river corridor of the South Fork McKenzie River, Oregon. We used a simple linear model to correct the TIR data by imaging a water bath where the temperature increased from 9.5 to 33.4 °C. The resulting model reduced the mean absolute error from 1.62 to 0.35 °C. We applied this correction to TIR-measured temperatures of wetted cells classified using NDWI imagery acquired in the field. We found warmer conditions (+2.6 °C) after restoration (<i>p</i> < 0.001) and median absolute deviation for pre-restoration (0.30) to be less than both that of post-restoration (0.85) and post-fire (0.79) orthomosaics. In addition, there was statistically significant evidence to support the hypothesis of shifts in temperature distributions pre- and post-restoration (KS test 2009 vs. 2019, <i>p</i> < 0.001, D = 0.99; KS test 2019 vs. 2021, <i>p</i> < 0.001, D = 0.10). Moreover, we used a Generalized Additive Model (GAM) that included spatial and environmental predictors (i.e., canopy cover calculated from multispectral NDVI and photogrammetrically derived digital elevation model) to model TIR temperature from a transect along the main river channel. This model explained 89% of the deviance, and the predictor variables showed statistical significance. Collectively, our study underscored the potential of a multispectral/TIR sensor to assess thermal heterogeneity in large and complex river systems. |
| format | Article |
| id | doaj-art-cdff9f62e30d4214b1f89cd1a723e3fb |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-04-01 |
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| series | Remote Sensing |
| spelling | doaj-art-cdff9f62e30d4214b1f89cd1a723e3fb2025-08-20T03:08:54ZengMDPI AGRemote Sensing2072-42922025-04-01177125410.3390/rs17071254Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal ImageryMatthew I. Barker0Jonathan D. Burnett1Ivan Arismendi2Michael G. Wing3Department of Forest Engineering, Resources, and Management, Oregon State University, Peavy Hall, 3100 SW Jefferson Way, Corvallis, OR 97333, USAUSDA Forest Service, Pacific Northwest Olympia Forestry Sciences Lab, 3625 93rd Ave. SW, Olympia, WA 98512, USADepartment of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Nash Hall 104, Corvallis, OR 97331, USADepartment of Forest Engineering, Resources, and Management, Oregon State University, Peavy Hall, 3100 SW Jefferson Way, Corvallis, OR 97333, USAThermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through time to assess the impacts to a river’s thermal regime. Lightweight sensors that record both thermal infrared (TIR) and multispectral data carried via unoccupied aircraft systems (UASs) present an opportunity to monitor temperature variations at high spatial (<0.5 m) and temporal resolution, facilitating the detection of the small patches of varying temperatures salmon require. Here, we present methods to classify and filter visible wetted area, including a novel procedure to measure canopy cover, and extract and correct radiant surface water temperature to evaluate changes in the variability of stream temperature pre- and post-restoration followed by a high-intensity fire in a section of the river corridor of the South Fork McKenzie River, Oregon. We used a simple linear model to correct the TIR data by imaging a water bath where the temperature increased from 9.5 to 33.4 °C. The resulting model reduced the mean absolute error from 1.62 to 0.35 °C. We applied this correction to TIR-measured temperatures of wetted cells classified using NDWI imagery acquired in the field. We found warmer conditions (+2.6 °C) after restoration (<i>p</i> < 0.001) and median absolute deviation for pre-restoration (0.30) to be less than both that of post-restoration (0.85) and post-fire (0.79) orthomosaics. In addition, there was statistically significant evidence to support the hypothesis of shifts in temperature distributions pre- and post-restoration (KS test 2009 vs. 2019, <i>p</i> < 0.001, D = 0.99; KS test 2019 vs. 2021, <i>p</i> < 0.001, D = 0.10). Moreover, we used a Generalized Additive Model (GAM) that included spatial and environmental predictors (i.e., canopy cover calculated from multispectral NDVI and photogrammetrically derived digital elevation model) to model TIR temperature from a transect along the main river channel. This model explained 89% of the deviance, and the predictor variables showed statistical significance. Collectively, our study underscored the potential of a multispectral/TIR sensor to assess thermal heterogeneity in large and complex river systems.https://www.mdpi.com/2072-4292/17/7/1254riverscapesstream networkthermal regimesGISlandscape ecologyunoccupied aircraft system (UAS) |
| spellingShingle | Matthew I. Barker Jonathan D. Burnett Ivan Arismendi Michael G. Wing Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery Remote Sensing riverscapes stream network thermal regimes GIS landscape ecology unoccupied aircraft system (UAS) |
| title | Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery |
| title_full | Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery |
| title_fullStr | Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery |
| title_full_unstemmed | Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery |
| title_short | Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery |
| title_sort | assessing heterogeneity of surface water temperature following stream restoration and a high intensity fire from thermal imagery |
| topic | riverscapes stream network thermal regimes GIS landscape ecology unoccupied aircraft system (UAS) |
| url | https://www.mdpi.com/2072-4292/17/7/1254 |
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