4.7 Article

WREP: A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops

Journal

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
Volume 129, Issue -, Pages 103-117

Publisher

ELSEVIER
DOI: 10.1016/j.isprsjprs.2017.04.024

Keywords

Chlorophyll content; Red edge position; Wavelet; Rice; Wheat

Funding

  1. National Natural Science Foundation of China [31470084]
  2. Fundamental Research Funds for the Central Universities [KYRC201401]
  3. National Key R&D Program from Ministry of Agriculture in China [2016YFD0300601]
  4. Jiangsu Distinguished Professor Program from Ministry of Agriculture in China
  5. Jiangsu Entrepreneurship and Innovation Doctor Program from Ministry of Agriculture in China
  6. Special Program for Agriculture Science and Technology from Ministry of Agriculture in China [201303109]
  7. Jiangsu Collaborative Innovation Center for Modern Crop Production
  8. Academic Program Development of Jiangsu Higher Education Institutions (PAPD)

Ask authors/readers for more resources

Red edge position (REP), defined as the wavelength of the inflexion point in the red edge region (680760 nm) of the reflectance spectrum, has been widely used to estimate foliar chlorophyll content from reflectance spectra. A number of techniques have been developed for REP extraction in the past three decades, but most of them require data-specific parameterization and the consistence of their performance from leaf to canopy levels remains poorly understood. In this study, we propose a new technique (WREP) to extract REPs based on the application of continuous wavelet transform to reflectance spectra. The REP is determined by the zero-crossing wavelength in the red edge region of a wavelet transformed spectrum for a number of scales of wavelet decomposition. The new technique is simple to implement and requires no parameterization from the user as long as continuous wavelet transforms are applied to reflectance spectra. Its performance was evaluated for estimating leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC) of cereal crops (i.e. rice and wheat) and compared with traditional techniques including linear interpolation, linear extrapolation, polynomial fitting and inverted Gaussian. Our results demonstrated that WREP obtained the best estimation accuracy for both LCC and CCC as compared to traditional techniques. High scales of wavelet decomposition were favorable for the estimation of CCC and low scales for the estimation of LCC. The difference in optimal scale reveals the underlying mechanism of signature transfer from leaf to canopy levels. In addition, crop-specific models were required for the estimation of CCC over the full range. However, a common model could be built with the REPs extracted with Scale 5 of the WREP technique for wheat and rice crops when CCC was less than 2 g/m(2) (R-2 = 0.73, RMSE = 0.26 g/m(2)). This insensitivity of WREP to crop type indicates the potential for aerial mapping of chlorophyll content between growth seasons of cereal crops. The new REP extraction technique provides us a new insight for understanding the spectral changes in the red edge region in response to chlorophyll variation from leaf to canopy levels. (C) 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available