DOI: 10.1016/j.jag.2015.02.012
Scopus记录号: 2-s2.0-84939454114
论文题名: Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley
作者: Bendig J ; , Yu K ; , Aasen H ; , Bolten A ; , Bennertz S ; , Broscheit J ; , Gnyp M ; L ; , Bareth G
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 39 起始页码: 79
结束页码: 87
语种: 英语
英文关键词: GnyLi
; Green red vegetation index
; NDVI
; Point cloud
; SAVI
; Structure from motion
Scopus关键词: aerial photograph
; barley
; biomass
; height
; monitoring system
; NDVI
; near infrared
; unmanned vehicle
; Germany
; Hordeum
英文摘要: In this study we combined selected vegetation indices (VIs) and plant height information to estimate biomass in a summer barley experiment. The VIs were calculated from ground-based hyperspectral data and unmanned aerial vehicle (UAV)-based red green blue (RGB) imaging. In addition, the plant height information was obtained from UAV-based multi-temporal crop surface models (CSMs). The test site is a summer barley experiment comprising 18 cultivars and two nitrogen treatments located in Western Germany. We calculated five VIs from hyperspectral data. The normalised ratio index (NRI)-based index GnyLi (Gnyp et al., 2014) showed the highest correlation (R2 = 0.83) with dry biomass. In addition, we calculated three visible band VIs: the green red vegetation index (GRVI), the modified GRVI (MGRVI) and the red green blue VI (RGBVI), where the MGRVI and the RGBVI are newly developed VI. We found that the visible band VIs have potential for biomass prediction prior to heading stage. A robust estimate for biomass was obtained from the plant height models (R2 = 0.80-0.82). In a cross validation test, we compared plant height, selected VIs and their combination with plant height information. Combining VIs and plant height information by using multiple linear regression or multiple non-linear regression models performed better than the VIs alone. The visible band GRVI and the newly developed RGBVI are promising but need further investigation. However, the relationship between plant height and biomass produced the most robust results. In summary, the results indicate that plant height is competitive with VIs for biomass estimation in summer barley. Moreover, visible band VIs might be a useful addition to biomass estimation. The main limitation is that the visible band VIs work for early growing stages only. © 2015 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79488
Appears in Collections: 气候变化事实与影响
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作者单位: Institute of Geography, GIS and RS Group, University of Cologne, Albertus-Magnus-Platz, Cologne, Germany; Research Centre Hanninghof, Yara International ASA, Hanninghof 35, Dülmen, Germany; ICASD-International Center for Agro-Informatics and Sustainable Development, College of Resources and Environmental Sciences, China Agricultural University, Beijing, China
Recommended Citation:
Bendig J,, Yu K,, Aasen H,et al. Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,39