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

| Peer-Reviewed

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

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

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), 2017. Published by Science Publishing Group

Keywords

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

References

[1]	Dawson T. P., North P. R. J., Plummer S. E. 2010. Forest ecosystem chlorophyll content: Implications for remotely sensed estimates of net primary productivity. International Journal of Remote Sensing, 24(3): 611-617.
[2]	GaoYan-hua, Chen Liang-fu, Liu Qin-huo. 2008. Research on remote sensing model for FPAR absorbed by chlorophyll. Journal of Remote Sensing, 10(5), 798-803.
[3]	Gemmell F. 2008. An investigation of terrain effects on the inversion of a forest reflectance model. Remote Sensing of Environment, 65(16), 155-169.
[4]	Gong P., Wang S. X., Liang S. 2009. Inverting a canopy reflectance model using a neural network. International Journal of Remote Sensing, 20(4), 111-122.
[5]	Goward S. N., Huemmrich K. F. 2008. Vegetation canopy PAR absorptance and the normalized difference vegetation index: An assessment using the SAIL model. Remote Sensing of Environment, 39: 119-140.
[6]	Jacquemoud S., Baret F. 2006. Prospect：a model of leaf optical properties spectra. Remote Sensing of Environment, 8(6), 75-91.
[7]	Jacqumoud S., Ustin S. L., Verdebout J., Schmuck G., Andreoli G., Hos-good. 2009. Estimating leaf biochemistry using the PROSPECT leaf optical properties mode. Remote Sensing of Environment, 56(6): 194-202.
[8]	Karami A., Yazdi M., and Mercier G. 2012. Compression of hyperspectral images using discrete wavelet transform and tucker decomposition. IEEE Journal of selected topics in applied Earth observations and remote sensing. 5(2), 444-452.
[9]	Kimes, D. S. 2007. Remote sensing of Row Crop Structure and component Temperatures Using Directional Radiometric Temperatures Using Directional Radiometric Temperatures and Inversion Techniques. Remote Sensing of Environment, 6(8), 33-55.
[10]	Kimes, D. S., Kirchner J. A. 2008. Directional Radiometric Measurements of Row-crop Temperatures. International Journal of Remote sensing, 2(6), 299-311.
[11]	Kuusk A. 2007. A fast invertible canopy reflectance model. Remote Sensing of Environment, 51(12), 342-350.
[12]	Kuusk A. 2006. A multispectral canopy reflectance model. Remote Sensing of Environment, 50(10), 75-82.
[13]	Liang S., Strahler A. H. 2008. An analytic BRDF model of canopy radiative transfer and its inversion. IEEE Transactions on Geoscience and Remote Sensing, 31(5), 1081-1092.
[14]	Manevski K., Manakos I., Petropoulos G. P., and Kalaitzidis C. 2012. Spectral discrimination of Mediterranean maquis and phrygana vegetation: Results from a case study in Greece. IEEE Journal of selected topics in applied Earth observations and remote sensing. 5(2), 604-612.
[15]	Mustafa Yaseen T., Stein Alfred, Tolpekin Valentyn A., and Laake Patrick E. Van. 2012. Improving forest growth estimates using a Bayesian network approach. Photogrammetry Engineering & Remote Sensing. 78(1), 45-50.
[16]	Myneni R. B., Nemani R. R., Running S. W. 2007. Estimation of global leaf area index and absorbed par using radiative transfer models. IEEE Transactions on Geoscience and Remote Sensing, 35(6), 1380-1393.
[17]	Niemann K. O., Quinn G., Goodenough D. G., Visintini F., and Loos R. 2012. Addressing the effects of canopy structure on the remote sensing of foliar chemistry of a 3-dimensional radiometrically porous surface. IEEE Journal of selected topics in applied Earth observations and remote sensing. 5(2), 584-592.
[18]	Nilson, K. A. 2009. A reflectance model for the Homogeneous plant canopy and its inversion. Remote Sensing of Environment, 4(6), 157-167.
[19]	North P. R. J. 2006. Three-dimensional forest light interaction model using a Monte-Carlo method. IEEE Transaction on Geoscience and Remote Sensing, 12(8), 946-956.
[20]	Privette J. L., Emery W. J., & Myneni R. B. 2006. Invertibility of a 1-D discrete ordinates canopy Reflectance model. Remote Sensing of Environment, 12(6), 89-105.
[21]	Piwowar J. M. 2011. An environmental normal of vegetation vigour for the northern great plains. IEEE Journal of selected topics in applied Earth observations and remote sensing. 4(2), 292-298.
[22]	Sellers P. J. 2007. Canopy reflectance, photosynthesis, and transpiration. International Journal of Remote Sensing, 6: 335-372.
[23]	Suits G. H. 2008. The calculation of the directional reflectance of a vegetative canopy. Remote Sensing of Environment, 6(10), 117-125.
[24]	Verhoef W. 2006. Light scattering by leaf layers with application to canopy reflectance modeling：the SAIL model. Remote Sensing of Environment, 8(6), 125-141.
[25]	Veroustraete F., Patyn J., & Myneni R. B. 2006. Estimating Net Ecosystem Exchange of Carbon Using the Normalized Difference Vegetation Index and an Ecosystem Model. Remote Sensing of Environment, 10(4), 115-130.

Cite This Article

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

Copy | Download

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

Copy | Download

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

Copy | Download

@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}
}

Copy | Download

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 -

Copy | Download

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

Download PDF

Sections

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

Copy | Download

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

Copy | Download

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

Copy | Download

@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}
}

Copy | Download