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  1. Article ; Online: Evaluating Predictive Models of Tree Foliar Moisture Content for Application to Multispectral UAS Data: A Laboratory Study

    Lad, Lauren E. / Tinkham, Wade T. / Sparks, Aaron M. / Smith, Alistair M. S.

    Remote Sensing. 2023 Dec. 12, v. 15, no. 54 p.5703-

    2023  

    Abstract: Water supply is a critical component of tree physiological health, influencing a tree’s photosynthetic activity and resilience to disturbances. The climatic regions of the western United States are particularly at risk from increasing drought, fire, and ... ...

    Abstract Water supply is a critical component of tree physiological health, influencing a tree’s photosynthetic activity and resilience to disturbances. The climatic regions of the western United States are particularly at risk from increasing drought, fire, and pest interactions. Existing methods for quantifying drought stress and a tree’s relative resilience against disturbances mostly use moderate-scale (20–30 m) multispectral satellite sensor data. However, tree water status (i.e., water stress) quantification using sensors like Landsat and Sentinel are error-prone given that the spectral reflectance of pixels are a mixture o
    Keywords Landsat ; canopy ; drought ; pests ; photosynthesis ; reflectance ; risk ; soil ; trees ; vegetation ; water content ; water stress ; water supply
    Language English
    Dates of publication 2023-1212
    Publishing place MDPI AG
    Document type Article ; Online
    Note Resource is Open Access
    ZDB-ID 2513863-7
    ISSN 2072-4292
    ISSN 2072-4292
    DOI 10.3390/rs15245703
    Database NAL-Catalogue (AGRICOLA)

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  2. Article ; Online: Preface: Special Issue on Advances in the Measurement of Fuels and Fuel Properties

    Tinkham, Wade T. / Lad, Lauren E. / Smith, Alistair M. S.

    Fire. 2023 Mar. 09, v. 6, no. 3

    2023  

    Abstract: Increasing global temperatures and variability in the timing, quantity, and intensity of precipitation and wind have led to longer fire season lengths, greater fuel availability, and more intense and severe wildfires [ ... ] ...

    Abstract Increasing global temperatures and variability in the timing, quantity, and intensity of precipitation and wind have led to longer fire season lengths, greater fuel availability, and more intense and severe wildfires [...]
    Keywords fire season ; fuels ; wind
    Language English
    Dates of publication 2023-0309
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article ; Online
    ISSN 2571-6255
    DOI 10.3390/fire6030108
    Database NAL-Catalogue (AGRICOLA)

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  3. Article ; Online: Modeling the Missing DBHs: Influence of Model Form on UAV DBH Characterization

    Tinkham, Wade T. / Swayze, Neal C. / Hoffman, Chad M. / Lad, Lauren E. / Battaglia, Mike A.

    Forests. 2022 Dec. 06, v. 13, no. 12

    2022  

    Abstract: The reliability of forest management decisions partly depends on the quality and extent of the data needed for the decision. However, the relatively high cost of traditional field sampling limits sampling intensity and data quality. One strategy to ... ...

    Abstract The reliability of forest management decisions partly depends on the quality and extent of the data needed for the decision. However, the relatively high cost of traditional field sampling limits sampling intensity and data quality. One strategy to increase data quality and extent, while reducing the overall sample effort, is using remote sensing-based data from unmanned aerial vehicles (UAV). While these techniques reliably identify most tree locations and heights in open-canopied forests, their ability to characterize diameter at breast height (DBH) is limited to estimates of a fraction of trees within the area. This study used UAV-derived DBHs and explanatory variables to test five model forms in predicting the missing DBHs. The results showed that filtering UAV DBHs using regionally derived height to DBH allometries significantly improved model performance. The best predicting model was slightly biased, with a 5.6 cm mean error and a mean absolute error of 6.8 cm. When applied across the stand, the number of trees was underestimated by 26.7 (3.9%), while the basal area and quadratic mean diameter were overestimated by 3.3 m² ha⁻¹ (13.1%) and 1.8 cm (8.3%), respectively. This study proposes a pathway for remotely sensed DBHs to predict missing DBHs; however, challenges are highlighted in ensuring the model training dataset represents the population.
    Keywords allometry ; data quality ; forest management ; model validation ; models ; tree and stand measurements ; trees
    Language English
    Dates of publication 2022-1206
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article ; Online
    ZDB-ID 2527081-3
    ISSN 1999-4907
    ISSN 1999-4907
    DOI 10.3390/f13122077
    Database NAL-Catalogue (AGRICOLA)

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