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Estimating Air Temperature Profiles in Forest Canopy Using Empirical Models and Landsat Data

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The objective of this study was to characterize and predict the air-temperature profiles in forest canopy using empirical models and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) thermal infrared (TIR) data. For each hour of the day, empirical models were developed using the air temperatures measured in a mixed forest in Tolland, Connecticut during the summer of 2001. Air-temperature profiles measured on eight randomly selected days over the study period were used to evaluate the models' performance. The results show high agreement between model-predicted temperatures and field observations (R 2=0.96 and RMSE=0.5°C). Forest canopy-surface temperature was estimated from Landsat ETM+ TIR data and then applied on the empirical model at 10:30 to predict air temperatures below the forest canopy. Compared with field-measured air temperatures on the same day, good agreement (R 2=0.80 and RMSE=0.7°C) was obtained between predicted and observed air-temperature profile in this mixed forest. This study implies that Landsat TIR data combined with empirical models have the potential to characterize and further predict the air-temperature profile in forest canopies.
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Keywords: Landsat; air-temperature profile; canopy-surface temperature; thermal remote sensing

Document Type: Research Article

Publication date: 2007-02-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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