DOI: 10.1016/j.jag.2012.10.008
Scopus记录号: 2-s2.0-84880302184
论文题名: Savanna grass nitrogen to phosphorous ratio estimation using field spectroscopy and the potential for estimation with imaging spectroscopy
作者: Ramoelo A ; , Skidmore A ; K ; , Schlerf M ; , Heitkönig I ; M ; A ; , Mathieu R ; , Cho M ; A
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2013
卷: 23, 期: 1 起始页码: 334
结束页码: 343
语种: 英语
英文关键词: Estimation
; Grass
; N:P
; Nitrogen
; Phosphorus
; Savanna ecosystem
; Spectroscopy
; Water removed spectra
Scopus关键词: accuracy assessment
; grass
; least squares method
; nitrogen
; phosphorus
; remote sensing
; savanna
; spectroscopy
; vegetation mapping
英文摘要: Determining the foliar N:P ratio provides a tool for understanding nutrient limitation on plant production and consequently for the feeding patterns of herbivores. In order to understand the nutrient limitation at landscape scale, remote sensing techniques offer that opportunity. The objective of this study is to investigate the utility of field spectroscopy and a potential of hyperspectral mapper (HyMap) spectra to estimate foliar N:P ratio. Field spectral measurements were undertaken, and grass samples were collected for foliar N and P extraction. The foliar N:P ratio prediction models were developed using partial least square regression (PLSR) with original spectra and transformed spectra for field and the resampled field spectra to HyMap. Spectral transformations included the continuum removal (CR), water removal (WR), first difference derivative (FD) and log transformation (Log(1/R)). The results showed that CR and WR spectra in combination with PLSR predicted foliar N:P ratio with higher accuracy as compared to FD and R, using field spectra. For HyMap spectral analysis, addition to CR and WR, FD achieved higher estimation accuracy. The performance of FD, CR and WR spectra were attributed to their ability to minimize sensor and water effects on the fresh leaf spectra, respectively. The study demonstrated a potential to predict foliar N:P ratio using field and HyMap simulated spectra and shortwave infrared (SWIR) found to be highly sensitive to foliar N:P ratio. The study recommends the prediction of foliar N:P ratio at landscape level using airborne hyperspectral data and could be used by the resource managers, park managers, farmers and ecologists to understand the feeding patterns, resource selection and distribution of herbivores (i.e. wild and livestock). © 2012 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79825
Appears in Collections: 气候变化事实与影响
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作者单位: Earth Observation Research Group, Natural Resource and the Environment Unit, Council for Scientific and Industrial Research (CSIR), P.O. Box 395, Pretoria, 0001, South Africa; Faculty of Geoinformation Science and Earth Observation, University of Twente (UT-ITC), P.O. Box 217, Enschede, 7500 AE, Netherlands; Public Research Centre, Gabriel Lippmann, 41 rue du Brill, L-4422 Belvaux, Luxembourg; Resource Ecology Group, Wageningen University, Droevendaalsesteeg 3a, 6708 PB Wageningen, Netherlands
Recommended Citation:
Ramoelo A,, Skidmore A,K,et al. Savanna grass nitrogen to phosphorous ratio estimation using field spectroscopy and the potential for estimation with imaging spectroscopy[J]. International Journal of Applied Earth Observation and Geoinformation,2013-01-01,23(1)