Exploring Canopy Temperature and Height Dynamics in Forest Ecosystems

Riyaaz Uddien Shaik, Kathiravan Thangavel, Sriram Babu Jallu, Dario Spiller, Roberto Sabatini, Weiping Zeng

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Within this study, we examined the correlation between tree canopy temperature, canopy height, and vegetation types. Furthermore, we conducted a similar analysis in the southern region of the island of Sardinia, renowned for its dense forests and frequent wildfires. We successfully mapped the vegetation types in the region using PRISMA hyperspectral data and the SVM classifier with an accuracy of over 80% for all classes. We utilized Random Forest Regression on Sentinel-1 SAR data, Sentinel-2 multispectral data, and the SRTM DEM to determine the canopy heights of various plant classes. Our estimation had an RMSE of 2.9176 meters and an R2 of 0.791. In addition, we used the MODIS LST and emissivity product regardless of Land Use and Land Cover (LULC) type to calculate the ground surface temperature. Using LST measurements over tree canopies, we identified a correlation between canopy temperature and corresponding canopy heights as well as vegetation types for five vegetation types, including evergreen oak, olive, juniper, silicicole, and riparian trees. For various vegetation types, the results and graph demonstrate that lower tree canopy temperatures corresponded to higher tree canopies, with a range of -0.4 to -0.5.

    Original languageBritish English
    Title of host publication2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages706-710
    Number of pages5
    ISBN (Electronic)9798350300802
    DOIs
    StatePublished - 2023
    Event2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023 - Milano, Italy
    Duration: 25 Oct 202327 Oct 2023

    Publication series

    Name2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023 - Proceedings

    Conference

    Conference2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023
    Country/TerritoryItaly
    CityMilano
    Period25/10/2327/10/23

    Keywords

    • canopy heights
    • climate change
    • Earth observation
    • estimation
    • forestry
    • GEDI
    • machine learning
    • random forest regression
    • SAR

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