The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model

Wei Fu; Huan Pei; Zeng-shun Li; Hao Shen; Jun-shuai Li; Peng-yuan Wang

doi:doi:10.11648/j.earth.20170606.15

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The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model

Wei Fu, Huan Pei, Zeng-shun Li, Hao Shen, Jun-shuai Li, Peng-yuan Wang

Published in Earth Sciences (Volume 6, Issue 6)

Received: 30 May 2017 Accepted: 12 June 2017 Published: 30 October 2017

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Abstract

This paper puts forward a novel approach for model inversion of leaf area index (LAI) of vegetation based on the integrated arithmetic of data assimilation and genetic-particle swarm algorithm (DAGS). The article expounds the design principle of electromagenetic wave radiative transfer model (ERTM) for vegetation canopies. On this basis, this study constructs the inversion model of LAI based on DAGS. Furthermore, this experiment realizes the model inversion of LAI with the aid of Remote Sensing (RS) multi-spectral data and biophysical component data of vegetation canopies, which are provided by the multispectral RS observation data set (MOD15A2). The bullet points of the text are summarized as follows. (1) The contribution proposes DAGS for LAI inversion. (2) The article discusses ERTM model for electromagenetic wave radiative transfer mechanism of vegetation canopies. (3) This text achieves LAI inversion with the help of RS multi-spectral data and biophysical component data of vegetation canopies supplied by MOD15A2. The experimental results demonstrate the validity and reliability of the model inversion of LAIby making use of DAGS. The proposed algorithm exploits a novel algorithmic pathway for the model inversion of LAI by means of RS multi-spectral data and biophysical component data of vegetation canopies.

Published in	Earth Sciences (Volume 6, Issue 6)
DOI	10.11648/j.earth.20170606.15
Page(s)	131-141
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

LAI, Model Inversion, Biophysics Component Parameters, DAGS, ERTM

References

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APA Style

Wei Fu, Huan Pei, Zeng-shun Li, Hao Shen, Jun-shuai Li, et al. (2017). The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model. Earth Sciences, 6(6), 131-141. https://doi.org/10.11648/j.earth.20170606.15

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ACS Style

Wei Fu; Huan Pei; Zeng-shun Li; Hao Shen; Jun-shuai Li, et al. The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model. Earth Sci. 2017, 6(6), 131-141. doi: 10.11648/j.earth.20170606.15

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AMA Style

Wei Fu, Huan Pei, Zeng-shun Li, Hao Shen, Jun-shuai Li, et al. The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model. Earth Sci. 2017;6(6):131-141. doi: 10.11648/j.earth.20170606.15

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@article{10.11648/j.earth.20170606.15,
  author = {Wei Fu and Huan Pei and Zeng-shun Li and Hao Shen and Jun-shuai Li and Peng-yuan Wang},
  title = {The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model},
  journal = {Earth Sciences},
  volume = {6},
  number = {6},
  pages = {131-141},
  doi = {10.11648/j.earth.20170606.15},
  url = {https://doi.org/10.11648/j.earth.20170606.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20170606.15},
  abstract = {This paper puts forward a novel approach for model inversion of leaf area index (LAI) of vegetation based on the integrated arithmetic of data assimilation and genetic-particle swarm algorithm (DAGS). The article expounds the design principle of electromagenetic wave radiative transfer model (ERTM) for vegetation canopies. On this basis, this study constructs the inversion model of LAI based on DAGS. Furthermore, this experiment realizes the model inversion of LAI with the aid of Remote Sensing (RS) multi-spectral data and biophysical component data of vegetation canopies, which are provided by the multispectral RS observation data set (MOD15A2). The bullet points of the text are summarized as follows. (1) The contribution proposes DAGS for LAI inversion. (2) The article discusses ERTM model for electromagenetic wave radiative transfer mechanism of vegetation canopies. (3) This text achieves LAI inversion with the help of RS multi-spectral data and biophysical component data of vegetation canopies supplied by MOD15A2. The experimental results demonstrate the validity and reliability of the model inversion of LAIby making use of DAGS. The proposed algorithm exploits a novel algorithmic pathway for the model inversion of LAI by means of RS multi-spectral data and biophysical component data of vegetation canopies.},
 year = {2017}
}

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TY - JOUR
T1 - The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model
AU - Wei Fu
AU - Huan Pei
AU - Zeng-shun Li
AU - Hao Shen
AU - Jun-shuai Li
AU - Peng-yuan Wang
Y1 - 2017/10/30
PY - 2017
N1 - https://doi.org/10.11648/j.earth.20170606.15
DO - 10.11648/j.earth.20170606.15
T2 - Earth Sciences
JF - Earth Sciences
JO - Earth Sciences
SP - 131
EP - 141
PB - Science Publishing Group
SN - 2328-5982
UR - https://doi.org/10.11648/j.earth.20170606.15
AB - This paper puts forward a novel approach for model inversion of leaf area index (LAI) of vegetation based on the integrated arithmetic of data assimilation and genetic-particle swarm algorithm (DAGS). The article expounds the design principle of electromagenetic wave radiative transfer model (ERTM) for vegetation canopies. On this basis, this study constructs the inversion model of LAI based on DAGS. Furthermore, this experiment realizes the model inversion of LAI with the aid of Remote Sensing (RS) multi-spectral data and biophysical component data of vegetation canopies, which are provided by the multispectral RS observation data set (MOD15A2). The bullet points of the text are summarized as follows. (1) The contribution proposes DAGS for LAI inversion. (2) The article discusses ERTM model for electromagenetic wave radiative transfer mechanism of vegetation canopies. (3) This text achieves LAI inversion with the help of RS multi-spectral data and biophysical component data of vegetation canopies supplied by MOD15A2. The experimental results demonstrate the validity and reliability of the model inversion of LAIby making use of DAGS. The proposed algorithm exploits a novel algorithmic pathway for the model inversion of LAI by means of RS multi-spectral data and biophysical component data of vegetation canopies.
VL - 6
IS - 6
ER -

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Author Information

Wei Fu

Department of Communication & Electronic Engineering of the Information Institute, Yanshan University, Qinhuangdao, China
Huan Pei

Department of Communication & Electronic Engineering of the Information Institute, Yanshan University, Qinhuangdao, China
Zeng-shun Li

Department of Communication & Electronic Engineering of the Information Institute, Yanshan University, Qinhuangdao, China
Hao Shen

Department of Communication & Electronic Engineering of the Information Institute, Yanshan University, Qinhuangdao, China
Jun-shuai Li

Department of Communication & Electronic Engineering of the Information Institute, Yanshan University, Qinhuangdao, China
Peng-yuan Wang

Department of Communication & Electronic Engineering of the Information Institute, Yanshan University, Qinhuangdao, China

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Plain Text BibTeX RIS

APA Style

Wei Fu, Huan Pei, Zeng-shun Li, Hao Shen, Jun-shuai Li, et al. (2017). The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model. Earth Sciences, 6(6), 131-141. https://doi.org/10.11648/j.earth.20170606.15

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ACS Style

Wei Fu; Huan Pei; Zeng-shun Li; Hao Shen; Jun-shuai Li, et al. The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model. Earth Sci. 2017, 6(6), 131-141. doi: 10.11648/j.earth.20170606.15

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AMA Style

Wei Fu, Huan Pei, Zeng-shun Li, Hao Shen, Jun-shuai Li, et al. The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model. Earth Sci. 2017;6(6):131-141. doi: 10.11648/j.earth.20170606.15

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@article{10.11648/j.earth.20170606.15,
  author = {Wei Fu and Huan Pei and Zeng-shun Li and Hao Shen and Jun-shuai Li and Peng-yuan Wang},
  title = {The Model Inversion of Leaf Area Index of Vegetation by Means of Electromagenetic Wave Radiative Transfer Model},
  journal = {Earth Sciences},
  volume = {6},
  number = {6},
  pages = {131-141},
  doi = {10.11648/j.earth.20170606.15},
  url = {https://doi.org/10.11648/j.earth.20170606.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20170606.15},
  abstract = {This paper puts forward a novel approach for model inversion of leaf area index (LAI) of vegetation based on the integrated arithmetic of data assimilation and genetic-particle swarm algorithm (DAGS). The article expounds the design principle of electromagenetic wave radiative transfer model (ERTM) for vegetation canopies. On this basis, this study constructs the inversion model of LAI based on DAGS. Furthermore, this experiment realizes the model inversion of LAI with the aid of Remote Sensing (RS) multi-spectral data and biophysical component data of vegetation canopies, which are provided by the multispectral RS observation data set (MOD15A2). The bullet points of the text are summarized as follows. (1) The contribution proposes DAGS for LAI inversion. (2) The article discusses ERTM model for electromagenetic wave radiative transfer mechanism of vegetation canopies. (3) This text achieves LAI inversion with the help of RS multi-spectral data and biophysical component data of vegetation canopies supplied by MOD15A2. The experimental results demonstrate the validity and reliability of the model inversion of LAIby making use of DAGS. The proposed algorithm exploits a novel algorithmic pathway for the model inversion of LAI by means of RS multi-spectral data and biophysical component data of vegetation canopies.},
 year = {2017}
}

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