Literature DB >> 29735177

Remote sensing of plant-water relations: An overview and future perspectives.

A Damm1, E Paul-Limoges2, E Haghighi3, C Simmer4, F Morsdorf5, F D Schneider5, C van der Tol6, M Migliavacca7, U Rascher8.   

Abstract

Vegetation is a highly dynamic component of the Earth surface and substantially alters the water cycle. Particularly the process of oxygenic plant photosynthesis determines vegetation connecting the water and carbon cycle and causing various interactions and feedbacks across Earth spheres. While vegetation impacts the water cycle, it reacts to changing water availability via functional, biochemical and structural responses. Unravelling the resulting complex feedbacks and interactions between the plant-water system and environmental change is essential for any modelling approaches and predictions, but still insufficiently understood due to currently missing observations. We hypothesize that an appropriate cross-scale monitoring of plant-water relations can be achieved by combined observational and modelling approaches. This paper reviews suitable remote sensing approaches to assess plant-water relations ranging from pure observational to combined observational-modelling approaches. We use a combined energy balance and radiative transfer model to assess the explanatory power of pure observational approaches focussing on plant parameters to estimate plant-water relations, followed by an outline for a more effective use of remote sensing by their integration into soil-plant-atmosphere continuum (SPAC) models. We apply a mechanistic model simulating water movement in the SPAC to reveal insight into the complexity of relations between soil, plant and atmospheric parameters, and thus plant-water relations. We conclude that future research should focus on strategies combining observations and mechanistic modelling to advance our knowledge on the interplay between the plant-water system and environmental change, e.g. through plant transpiration.
Copyright © 2018 Elsevier GmbH. All rights reserved.

Entities:  

Keywords:  Earth observation; Photosynthesis; SCOPE model; SPAC model; Transpiration; Water potential

Mesh:

Substances:

Year:  2018        PMID: 29735177     DOI: 10.1016/j.jplph.2018.04.012

Source DB:  PubMed          Journal:  J Plant Physiol        ISSN: 0176-1617            Impact factor:   3.549


  5 in total

1.  Scenario-based discrimination of common grapevine varieties using in-field hyperspectral data in the western of Iran.

Authors:  Mohsen Mirzaei; Safar Marofi; Mozhgan Abbasi; Eisa Solgi; Rholah Karimi; Jochem Verrelst
Journal:  Int J Appl Earth Obs Geoinf       Date:  2019-08

2.  Optimal Spectral Wavelengths for Discriminating Orchard Species Using Multivariate Statistical Techniques.

Authors:  Mozhgan Abbasi; Jochem Verrelst; Mohsen Mirzaei; Safar Marofi; Hamid Reza Riyahi Bakhtíari
Journal:  Remote Sens (Basel)       Date:  2019-12-23       Impact factor: 5.349

3.  Eco-Friendly Estimation of Heavy Metal Contents in Grapevine Foliage Using In-Field Hyperspectral Data and Multivariate Analysis.

Authors:  Mohsen Mirzaei; Jochem Verrelst; Safar Marofi; Mozhgan Abbasi; Hossein Azadi
Journal:  Remote Sens (Basel)       Date:  2019-11-20       Impact factor: 5.349

4.  Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review.

Authors:  Katja Berger; Miriam Machwitz; Marlena Kycko; Shawn C Kefauver; Shari Van Wittenberghe; Max Gerhards; Jochem Verrelst; Clement Atzberger; Christiaan van der Tol; Alexander Damm; Uwe Rascher; Ittai Herrmann; Veronica Sobejano Paz; Sven Fahrner; Roland Pieruschka; Egor Prikaziuk; Ma Luisa Buchaillot; Andrej Halabuk; Marco Celesti; Gerbrand Koren; Esra Tunc Gormus; Micol Rossini; Michael Foerster; Bastian Siegmann; Asmaa Abdelbaki; Giulia Tagliabue; Tobias Hank; Roshanak Darvishzadeh; Helge Aasen; Monica Garcia; Isabel Pôças; Subhajit Bandopadhyay; Mauro Sulis; Enrico Tomelleri; Offer Rozenstein; Lachezar Filchev; Gheorghe Stancile; Martin Schlerf
Journal:  Remote Sens Environ       Date:  2022-08-04       Impact factor: 13.850

5.  Water Stress Alters Morphophysiological, Grain Quality and Vegetation Indices of Soybean Cultivars.

Authors:  Cássio Jardim Tavares; Walter Quadros Ribeiro Junior; Maria Lucrecia Gerosa Ramos; Lucas Felisberto Pereira; Raphael Augusto das Chagas Noqueli Casari; André Ferreira Pereira; Carlos Antonio Ferreira de Sousa; Anderson Rodrigo da Silva; Sebastião Pedro da Silva Neto; Liliane Marcia Mertz-Henning
Journal:  Plants (Basel)       Date:  2022-02-21
  5 in total

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