Retrieval of Leaf Area Index Using Inversion Algorithm

With the development in sensor technology, there is a spectroradiometer with resolution as high as 1nm and data capture extending from 350nm-2500nm; it helps in viewing spectral variability of the subject of interest. The advantage of such instruments opens up many opportunities for the development...

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Published in:Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing pp. 1 - 4
Main Authors: Verma, Bhagyashree, Prasad, Rajendra, Srivastava, Prashant K., Singh, Prachi
Format: Conference Proceeding
Language:English
Published: IEEE 13.09.2022
Subjects:
Correlation
Estimation
Generalized Linear Model (GLM)
Hyperspectral indices
Instruments
Leaf Area Index (LAI)
Signal processing
Signal processing algorithms
Spectroradiometer
Spectroradiometers
Vegetation mapping
ISSN:2158-6276
Online Access:Get full text
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Abstract With the development in sensor technology, there is a spectroradiometer with resolution as high as 1nm and data capture extending from 350nm-2500nm; it helps in viewing spectral variability of the subject of interest. The advantage of such instruments opens up many opportunities for the development of hyperspectral data analysis in precision agriculture. In the presented work, estimation of Leaf Area Index (LAI) is done with inversion technique using Transformed Vegetation Index (TVI), SR (Simple Ratio), NDVI (Normalized difference ratio index) vegetation indices as input parameters, and modeled LAI separately for these three indices. The estimation was done for different growth stages of Maize (Zea mays), Mustard (Brassica), pink Lentils (Lens esculenta), and Wheat (Triticum). A comprehensive comparative analysis was done based on the value of R 2 . For the variation in LAI, the SR index gave the highest correlation for lentils (R 2 =0.9329), Mustard (R 2 =0.893), and wheat (R 2 =0.9712) whereas, for Maize, NDVI was found to be the best estimator with a correlation of (R 2 =0.7781).
AbstractList With the development in sensor technology, there is a spectroradiometer with resolution as high as 1nm and data capture extending from 350nm-2500nm; it helps in viewing spectral variability of the subject of interest. The advantage of such instruments opens up many opportunities for the development of hyperspectral data analysis in precision agriculture. In the presented work, estimation of Leaf Area Index (LAI) is done with inversion technique using Transformed Vegetation Index (TVI), SR (Simple Ratio), NDVI (Normalized difference ratio index) vegetation indices as input parameters, and modeled LAI separately for these three indices. The estimation was done for different growth stages of Maize (Zea mays), Mustard (Brassica), pink Lentils (Lens esculenta), and Wheat (Triticum). A comprehensive comparative analysis was done based on the value of R 2 . For the variation in LAI, the SR index gave the highest correlation for lentils (R 2 =0.9329), Mustard (R 2 =0.893), and wheat (R 2 =0.9712) whereas, for Maize, NDVI was found to be the best estimator with a correlation of (R 2 =0.7781).
Author Srivastava, Prashant K.
Singh, Prachi
Verma, Bhagyashree
Prasad, Rajendra
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  givenname: Bhagyashree
  surname: Verma
  fullname: Verma, Bhagyashree
  organization: Indian Institute of Technology BHU,Department of Physics,Varanasi,India,221005
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  givenname: Rajendra
  surname: Prasad
  fullname: Prasad, Rajendra
  organization: Indian Institute of Technology BHU,Department of Physics,Varanasi,India,221005
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  givenname: Prashant K.
  surname: Srivastava
  fullname: Srivastava, Prashant K.
  organization: Institute of Environment and Sustainable Development, Banaras Hindu University,Remote sensing laboratory,Varanasi,India,221005
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  givenname: Prachi
  surname: Singh
  fullname: Singh, Prachi
  organization: Institute of Environment and Sustainable Development, Banaras Hindu University,Remote sensing laboratory,Varanasi,India,221005
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Snippet With the development in sensor technology, there is a spectroradiometer with resolution as high as 1nm and data capture extending from 350nm-2500nm; it helps...
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StartPage 1
SubjectTerms Correlation
Estimation
Generalized Linear Model (GLM)
Hyperspectral indices
Instruments
Leaf Area Index (LAI)
Signal processing
Signal processing algorithms
Spectroradiometer
Spectroradiometers
Vegetation mapping
Title Retrieval of Leaf Area Index Using Inversion Algorithm
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