Derivative analysis to improve rice biomass estimation at early growth stages
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| Title: | Main Title: Derivative analysis to improve rice biomass estimation at early growth stages |
| Description: | Abstract: Aboveground biomass (AGB) plays an important role in agriculture for assessing the production of foods, forage and renewable energy. Hyperspectral field measurements are an efficient method for nondestructive monitoring of AGB. Recent studies have confirmed the benefit of using different types of reflectance such as raw reflectance and its derivatives in the non-destructive methods. The objective of this study was to improve the estimation of rice (Oryza sativa L.) AGB with Optimum Multiple Narrow Band Reflectance (OMNBR) models based on raw reflectance (RR) and its first derivative of reflectance (FDR). Experiments with different nitrogen rates were conducted in experimental and farmers fields from 2007 through 2009 in Jiansanjiang, Northeast China. Hyperspectral data and AGB were collected at two growth stages - tillering and stem elongation. OMNBR models with 1-4 bands based on RR and FDR were performed. The results indicated that FDR-based OMNBR models were more accurate than RR-based ones, with the highest improvement found in FDR-based 1-2 band models. At the tillering stage, red and near infrared bands were selected, while the near infrared and shortwave infrared bands were applied at the stem elongation stage. Across both stages, FDR-based OMNBR models performed better than RR-based OMNBR models. These findings imply that derivative analysis may help to reduce the background influence of soil and water as well as the effects of illumination variations at early growth stages. More studies are needed to further explore the potential of derivative analysis. |
| Identifier: | 10.5880/TR32DB.KGA94.7 (DOI) |
Responsible Party
| Creators: | Martin Leon Gnyp (Author), Yuxin Miao (Author), Fei Yuan (Author), Kang Yu (Author), Yinkun Yao (Author), S. Huang (Author), Georg Bareth (Author) |
| Contributors: | Juliane Bendig (Editor), Georg Bareth (Editor), Transregional Collaborative Research Centre 32 (Meteorological Institute, University of Bonn) (Data Manager), University of Cologne (Regional Computing Centre (RRZK)) (Hosting Institution) |
| Publisher: | Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten |
| Publication Year: | 2014 |
Topic
| Subjects: | Keywords: Biomass, Agriculture, Hyperspectral, UAV, Airborne Measurements DDC: 550 Earth sciences |
File Details
| Filename: | Gnyp_et_al_2013_KGA94.pdf |
| Data Type: | Text - Book Section |
| Sizes: | 8 Pages 2256 Kilobytes |
| File Size: | 2.2 MB |
| Date: | Issued: 14.04.2014 |
| Mime Type: | application/pdf |
| Language: | English |
Constraints
| Download Permission: | Free |
| Licence: | [Creative Commons] Attribution 4.0 International (CC BY 4.0) |
Geographic
Metadata Details
| Metadata Creator: | Constanze Curdt |
| Metadata Created: | 17.04.2014 |
| Metadata Last Updated: | 17.04.2014 |
| Subproject: | Z1 |
| Funding Phase: | 2 |
| Metadata Language: | English |
| Metadata Version: | V50 |
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| Page Visits: | 489 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 53 |
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