Canopy Averaged Chlorophyll Content Prediction of Pear Trees Using Convolutional Autoencoder on Hyperspectral Data
نویسندگان
چکیده
منابع مشابه
Estimating canopy water content using hyperspectral remote sensing data
Hyperspectral remote sensing has demonstrated great potential for accurate retrieval of canopy water content (CWC). This CWC is defined by the product of the leaf equivalent water thickness (EWT) and the leaf area index (LAI). In this paper, in particular the spectral information provided by the canopy water absorption feature at 970 nm for estimating and predicting CWC was studied using a mode...
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ژورنال
عنوان ژورنال: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2020
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2020.2983000