The Effect of Principal Component Analysis Parameters on Solar-Induced Chlorophyll Fluorescence Signal Extraction - Archive ouverte HAL Access content directly
Journal Articles Applied Sciences Year : 2021

The Effect of Principal Component Analysis Parameters on Solar-Induced Chlorophyll Fluorescence Signal Extraction

, , , (1)
1
Zhongqiu Sun
  • Function : Author
Songxi Yang
  • Function : Author
Shuo Shi
  • Function : Author
Jian Yang

Abstract

Solar-induced chlorophyll fluorescence (SIF), one of the three main releasing pathways of vegetation-absorbed photosynthetic active radiation, has been proven as an effective monitoring implementation of leaf photosynthesis, canopy growth, and ecological diversity. There exist three categories of SIF retrieval methods, and the principal component analysis (PCA) retrieval method is obtrusively eye-catching due to its brief, data-driven characteristics. However, we still lack a lucid understanding of PCA’s parameter settings. In this study, we examined if principal component numbers and retrieval band regions could have effects on the accuracy of SIF inversion under two controlled experiments. The results revealed that the near-infrared region could remarkably boost SIF’s retrieval accuracy, whereas red and near-infrared bands caused anomalous values, which subverted a traditional view that more retrieval regions might provide more photosynthetic information. Furthermore, the results demonstrated that three principal components would benefit more in PCA-based SIF retrieval. These arguments further help elucidate the more in-depth influence of the parameters on the PCA retrieval method, which unveil the potential effects of different parameters and give a parameter-setting foundation for the PCA retrieval method, in addition to assisting retrieval achievements.

Dates and versions

hal-03236746 , version 1 (26-05-2021)

Identifiers

Cite

Zhongqiu Sun, Songxi Yang, Shuo Shi, Jian Yang. The Effect of Principal Component Analysis Parameters on Solar-Induced Chlorophyll Fluorescence Signal Extraction. Applied Sciences, 2021, 11 (11), pp.4883. ⟨10.3390/app11114883⟩. ⟨hal-03236746⟩

Collections

UNIV-AMU
12 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More