Abstract Non-destructive estimation of chlorophyll-a (Chl-a) and chlorophyll-b (Chl-b), is required for assessment and understanding of vegetation structural and functional dynamics. We have developed an empirical model for estimating Chl-a and Chl-b for different crops using Airborne Visible-Infrared Imaging Spectrometer Next Generation (AVIRIS-NG) data. Second derivative reflectance at 672 nm and 587 nm has shown maximum sensitivity towards Chl-a and Chl-b content, respectively. Separate linear models within a bootstrapped resampling framework were developed. During calibration, mean R2 of 0.46 and 0.51 were obtained for Chl-a and -b respectively. While during model validation, in both the cases mean R2 was found to be 0.3. This work shows the capability of airborne hyperspectral imaging data in segregating chlorophyll types using a simplistic modeling framework.


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    Titel :

    A non-destructive estimation of chlorophyll-a and -b over different crops using airborne imaging spectroscopy observations


    Beteiligte:
    Kushwaha, Amit (Autor:in) / Das, Ayan (Autor:in) / Dave, Rucha (Autor:in) / Bhattacharya, Bimal K. (Autor:in)

    Erschienen in:

    Advances in Space Research ; 73 , 2 ; 1290-1303


    Erscheinungsdatum :

    2022-07-23


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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