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Morphological characterization of Maize (Zea mays.) utilising the stage-wise structural and architectural perspective from temporal fully-polarimetric SAR.

Authors :
Haldar, Dipanwita
Suriya, E.
Danodia, Abhishek
Singh, R.P.
Source :
Egyptian Journal of Remote Sensing & Space Sciences; Jun2024, Vol. 27 Issue 2, p242-254, 13p
Publication Year :
2024

Abstract

The morphological shape and structure of the crop vary with phenological stages. Model and eigen based decomposition model parameters extracted from the Radarsat-2 data and the trend with respect to ground truth crop phenology were analysed. Sensitive parameters were devised through stepwise approach under 7 combinations of polarimetric variables of increasing complexity were assessed. Compared under the three machine learning algorithms (ANN, RF and SVM) where ANN rendered the maximum correlation with 0.92 with a MAE of 4 days which was implemented on a large parcel of maize mask in the study area. SVM performed poorly with highly overlapping parameters such as backscatter but performed well (r = 0.85). For assessing the crop biophysical parameters, the three algorithms were evaluated and sensitivity analysis for statistically significant polarimetric variables for biophysical parameters was performed. The assessment was performed on Multi-Layer Perception (MLP) neural network. The networks were trained with algorithms and hidden layer nodes until the MAE achieved permissible limits. Plant height could be estimated more profoundly with an r = 0.8 with a considerably good MAE of 24.9 cm but other parameters (WB, DB and LAI) were estimated in moderate correlation of 0.6–0.65 where the MAE of WB, DB and LAI were found to be 1317gm<superscript>−2</superscript>, 553 gm<superscript>−2</superscript> and 0.78 respectively. This is the first step towards understanding the complex scattering mechanisms in Indian maize scenario assessing the growth parameters from polarimetric data. Thus, the analytical findings brought out possess the potential to serve as the reference for the future research initiatives. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
11109823
Volume :
27
Issue :
2
Database :
Supplemental Index
Journal :
Egyptian Journal of Remote Sensing & Space Sciences
Publication Type :
Academic Journal
Accession number :
177454408
Full Text :
https://doi.org/10.1016/j.ejrs.2024.02.007