Surv Geophys https://doi.org/10.1007/s10712-018-9478-y Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods 1 2,3,4 5 Jochem Verrelst · Zbyněk Malenovský · Christiaan Van der Tol · 1 6 7,8 Gustau Camps‑Valls · Jean‑Philippe Gastellu‑Etchegorry · Philip Lewis · 9 1 Peter North · Jose Moreno Received: 2 November 2017 / Accepted: 16 May 2018 © Springer Science+Business Media B.V., part of Springer Nature 2018 Abstract An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of bio- chemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegeta- tion biophysical variables. Identified retrieval methods are categorized into: (1) paramet - ric regression, including vegetation indices, shape indices and spectral transformations; (2) * Jochem Verrelst firstname.lastname@example.org Image Processing Laboratory (IPL), Parc Científic, Universitat de València, Paterna, València 46980, Spain Surveying and Spatial Sciences Group, School of Technology, Environments and Design, University of Tasmania, Private
Surveys in Geophysics – Springer Journals
Published: Jun 1, 2018
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