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      The High-Performance Airborne Imaging Spectrometer HyPlant—From Raw Images to Top-of-Canopy Reflectance and Fluorescence Products: Introduction of an Automatized Processing Chain

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          Abstract

          The HyPlant imaging spectrometer is a high-performance airborne instrument consisting of two sensor modules. The DUAL module records hyperspectral data in the spectral range from 400–2500 nm, which is useful to derive biochemical and structural plant properties. In parallel, the FLUO module acquires data in the red and near infrared range (670–780 nm), with a distinctly higher spectral sampling interval and finer spectral resolution. The technical specifications of HyPlant FLUO allow for the retrieval of sun-induced chlorophyll fluorescence (SIF), a small signal emitted by plants, which is directly linked to their photosynthetic efficiency. The combined use of both HyPlant modules opens up new opportunities in plant science. The processing of HyPlant image data, however, is a rather complex procedure, and, especially for the FLUO module, a precise characterization and calibration of the sensor is of utmost importance. The presented study gives an overview of this unique high-performance imaging spectrometer, introduces an automatized processing chain, and gives an overview of the different processing steps that must be executed to generate the final products, namely top of canopy (TOC) radiance, TOC reflectance, reflectance indices and SIF maps.

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          Distinctive Image Features from Scale-Invariant Keypoints

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            Red and photographic infrared linear combinations for monitoring vegetation

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              Overview of the radiometric and biophysical performance of the MODIS vegetation indices

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                Journal
                Remote Sensing
                Remote Sensing
                MDPI AG
                2072-4292
                December 2019
                November 23 2019
                : 11
                : 23
                : 2760
                Article
                10.3390/rs11232760
                b1593d1a-7b2e-4a9d-b26f-e86b4d526286
                © 2019

                https://creativecommons.org/licenses/by/4.0/

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