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dc.contributor.author Ramoelo, Abel
dc.contributor.author Skidmore, A
dc.contributor.author Schlerf, M
dc.contributor.author Heitkönig, I
dc.contributor.author Mathieu, Renaud SA
dc.contributor.author Cho, Moses A
dc.date.accessioned 2013-03-26T13:31:34Z
dc.date.available 2013-03-26T13:31:34Z
dc.date.issued 2013-08
dc.identifier.citation Ramoelo, A., Skidmore, A., Schlerf, M., Heitkönig, I., Mathieu, R. and Cho, M.A. 2013. Savanna grass nitrogen to phosphorus ratio estimation using field spectroscopy and the potential for estimation with imaging spectroscopy. International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 334-343 en_US
dc.identifier.issn 0303-2434
dc.identifier.uri http://www.sciencedirect.com/science/article/pii/S0303243412002103
dc.identifier.uri http://hdl.handle.net/10204/6631
dc.description Copyright: 2012 Elsevier. This is the preprint version of the work. The definitive version is published in International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 334-343 en_US
dc.description.abstract 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 in situ hyperspectral remote sensing 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. 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 spectra. The performance of 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). en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries Workflow;10607
dc.subject Hyperspectral remote sensing en_US
dc.subject Field spectroscopy en_US
dc.subject Imaging spectroscopy en_US
dc.subject Nitrogen en_US
dc.subject Phosphorus en_US
dc.subject Water removed spectra en_US
dc.subject Savanna ecosystem en_US
dc.title Savanna grass nitrogen to phosphorus ratio estimation using field spectroscopy and the potential for estimation with imaging spectroscopy en_US
dc.type Article en_US


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