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Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks

The leaf area index (LAI) is a key parameter in the context of monitoring the development of tree crowns and plants in general. As parameters such as carbon assimilation, environmental stress on carbon, and the water fluxes within tree canopies are correlated to the leaves surface, this parameter is...

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Autores principales: Comella, Laura Maria, Bregler, Florian, Hager, Eiko, Anys, Markus, Klueppel, Johannes, Rupitsch, Stefan J., Werner, Christiane, Woias, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269822/
https://www.ncbi.nlm.nih.gov/pubmed/35808545
http://dx.doi.org/10.3390/s22135048
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author Comella, Laura Maria
Bregler, Florian
Hager, Eiko
Anys, Markus
Klueppel, Johannes
Rupitsch, Stefan J.
Werner, Christiane
Woias, Peter
author_facet Comella, Laura Maria
Bregler, Florian
Hager, Eiko
Anys, Markus
Klueppel, Johannes
Rupitsch, Stefan J.
Werner, Christiane
Woias, Peter
author_sort Comella, Laura Maria
collection PubMed
description The leaf area index (LAI) is a key parameter in the context of monitoring the development of tree crowns and plants in general. As parameters such as carbon assimilation, environmental stress on carbon, and the water fluxes within tree canopies are correlated to the leaves surface, this parameter is essential for understanding and modeling ecological processes. However, its continuous monitoring using manual state-of-the-art measurement instruments is still challenging. To address this challenge, we present an innovative sensor concept to obtain the LAI based on the cheap and easy to integrate multi-channel spectral sensor AS7341. Additionally, we present a method for processing and filtering the gathered data, which enables very high accuracy measurements with an nRMSE of only 0.098, compared to the manually-operated state-of-the-art instrument LAI-2200C (LiCor). The sensor that is embedded on a sensor node has been tested in long-term experiments, proving its suitability for continuous deployment over an entire season. It permits the estimation of both the plant area index (PAI) and leaf area index (LAI) and provides the first wireless system that obtains the LAI solely powered by solar cells. Its energy autonomy and wireless connectivity make it suitable for a massive deployment over large areas and at different levels of the tree crown. It may be upgraded to allow the parallel measurement of photosynthetic active radiation (PAR) and light quality, relevant parameters for monitoring processes within tree canopies.
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spelling pubmed-92698222022-07-09 Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks Comella, Laura Maria Bregler, Florian Hager, Eiko Anys, Markus Klueppel, Johannes Rupitsch, Stefan J. Werner, Christiane Woias, Peter Sensors (Basel) Article The leaf area index (LAI) is a key parameter in the context of monitoring the development of tree crowns and plants in general. As parameters such as carbon assimilation, environmental stress on carbon, and the water fluxes within tree canopies are correlated to the leaves surface, this parameter is essential for understanding and modeling ecological processes. However, its continuous monitoring using manual state-of-the-art measurement instruments is still challenging. To address this challenge, we present an innovative sensor concept to obtain the LAI based on the cheap and easy to integrate multi-channel spectral sensor AS7341. Additionally, we present a method for processing and filtering the gathered data, which enables very high accuracy measurements with an nRMSE of only 0.098, compared to the manually-operated state-of-the-art instrument LAI-2200C (LiCor). The sensor that is embedded on a sensor node has been tested in long-term experiments, proving its suitability for continuous deployment over an entire season. It permits the estimation of both the plant area index (PAI) and leaf area index (LAI) and provides the first wireless system that obtains the LAI solely powered by solar cells. Its energy autonomy and wireless connectivity make it suitable for a massive deployment over large areas and at different levels of the tree crown. It may be upgraded to allow the parallel measurement of photosynthetic active radiation (PAR) and light quality, relevant parameters for monitoring processes within tree canopies. MDPI 2022-07-05 /pmc/articles/PMC9269822/ /pubmed/35808545 http://dx.doi.org/10.3390/s22135048 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Comella, Laura Maria
Bregler, Florian
Hager, Eiko
Anys, Markus
Klueppel, Johannes
Rupitsch, Stefan J.
Werner, Christiane
Woias, Peter
Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks
title Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks
title_full Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks
title_fullStr Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks
title_full_unstemmed Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks
title_short Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks
title_sort estimation of leaf area index with a multi-channel spectral micro-sensor for wireless sensing networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269822/
https://www.ncbi.nlm.nih.gov/pubmed/35808545
http://dx.doi.org/10.3390/s22135048
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