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Show simple item record Gama, MJ Cho, Moses A Chirwa, P Masemola, Cecilia 2019-08-14T07:07:26Z 2019-08-14T07:07:26Z 2019-03
dc.identifier.citation Gama, M.J., Cho, M.A., Chirwa, P. & Masemola, C. 2019. Estimating mineral content of indigenous browse species using laboratory spectroscopy and sentinel-2 imagery. International Journal of Applied Earth Observation and Geoinformation, vol. 75: 141-150. doi:10.1016/j.jag.2018.10.013 en_US
dc.identifier.issn 0303-2434
dc.description Copyright: 2019 Elsevier. Due to copyright restrictions, the attached PDF file only contains the pre-print version of the full-text item. For access to the full-text item, please consult the publisher's website. en_US
dc.description.abstract Trees provide low-cost organic inputs, with the potential to improve livelihoods for rural communities. Understanding foliar nutrients of tree species is crucial for integration of trees into agroecosystems. The study explored nitrogen (N), phosphorus (P), potassium (K) and calcium (Ca) concentrations of nine browse species collected from the bushveld region of South Africa using wet analysis and laboratory spectroscopy in the region 400–2500nm, along with partial least squares (PLS) regression. We further explore the relationship between canopy reflectance of Sentinel-2 image and foliar N, P, K & Ca. Laboratory spectroscopy was significant for N estimation, while satellite imagery also revealed useful information about the estimation of nitrogen at landscape level. Nitrogen was highly correlated with spectral reflectance (R2=0.72, p<0.05) for winter and (R2=0.88, p<0.05) for summer, whilst prediction of phosphorus potassium and calcium were considered not accurate enough to be of practical use. Modelling the relationship using Sentinel-2 data showed lower correlations for nitrogen (R2=0.44, p<0.05) and the other nutrients when compared to the dried samples. The findings indicate that there is potential to assess and monitor resource quality of indigenous trees using nitrogen as key indicator. This multi-level remote sensing approach has promise for providing rapid plant nutrient analyses at different scales. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries Workflow;22473
dc.subject Continuum removal en_US
dc.subject Hyperspectral data en_US
dc.subject Laboratory spectroscopy en_US
dc.subject Leaf nitrogen en_US
dc.subject Multispectral data en_US
dc.subject Partial least squares regression en_US
dc.subject Sentinel-2 en_US
dc.subject Wet analysis en_US
dc.title Estimating mineral content of indigenous browse species using Laboratory spectroscopy and Sentinel-2 imagery en_US
dc.type Article en_US

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