Estimation of crop biomass using GF-3 polarization SAR data based on genetic algorithm feature selection

XU Kunpeng; ZHAO Lei; LI Kun; CHEN Erxue; ZHANG Wangfei; YANG Hao

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Estimation of crop biomass using GF-3 polarization SAR data based on genetic algorithm feature selection
Vol. 24, Issue S1, Pages: 1-9(2020)
Accepted：16 April 2020，

Published：07 June 2020
DOI：
稿件说明：

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DOI：

Xu K P,Zhao L,Li K,Chen E,Zhang W F and Yang H. 2020. Estimation of crop biomass using GF-3 polarization SAR data based on genetic algorithm feature selection. Journal of Remote Sensing(Chinese). 24(S1): 1-9 DOI：

摘要

Abstract

In recent years

Polarization SAR (PolSAR) has been widely used in the filed of crop biomass estimation. However

high dimensional features extracted from PolSAR data will lead to information redundancy which will result in low accuracy and poor transfer ability of the estimation model. Aiming at this problem

we proposed a estimation method of crop biomass based on automatic feature selection method using Genetic Algorithm (GA). Firstly

the backscattering coefficient

the polarization parameters and texture features were extracted from PolSAR data. Then

these features were automatically pre-selected by GA to obtain the optimal feature subset. Finally

based on this subset

a Support Vector Regression machine (SVR) model was applied to estimate crop biomass. The proposed method was validated using the GaoFen-3 (GF-3) QPSΙ (C-band

quad-polarization) SAR data. Based on wheat and rape biomass samples acquired from a synchronous field measurement campaign

the proposed method achieve relative high validation accuracy (over 80%) in both crop types. For further analyzing the improvement of proposed method

validation accuracies of biomass estimation models based on several different feature selection methods were compared. Compared with feature selection based on linear correlation

GA method has increased by 5.77% in wheat biomass estimation and 11.84% in rape biomass estimation. Compared with the method of Recursive Feature Elimination (RFE) selection

the proposed method has improved crops biomass estimation accuracy by 3.90% and 5.21%

respectively.

关键词

Keywords

references

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