Ramoelo, AbelSkidmore, AKSchlerf, MMathieu, Renaud SAHeitkönig, IMA2011-06-272011-06-272011Ramoelo, A., Skidmore, A.K., Schlerf, M., et al. 2011. Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations. ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 66(4), pp 408-4170924-2716http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6VF4-52959TK-1-1&_cdi=6000&_user=958262&_pii=S0924271611000232&_origin=&_coverDate=07%2F31%2F2011&_sk=999339995&view=c&wchp=dGLzVlz-zSkWA&_valck=1&md5=9bda71748ef77950871b0cceefb11518&ie=/sdarticle.pdfhttp://hdl.handle.net/10204/5070Copyright. 2011. This is a pre print version of the work. The definitive version is published in ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 66(4)Information about the distribution of grass foliar nitrogen (N) and phosphorus (P) is important for understanding rangeland vitality and for facilitating the effective management of wildlife and livestock. Water absorption effects in the near-infrared (NIR) and shortwave-infrared (SWIR) regions pose a challenge for nutrient estimation using remote sensing. The aim of this study was to test the utility of water-removed (WR) spectra in combination with partial least-squares regression (PLSR) and stepwise multiple linear regression (SMLR) to estimate foliar N and P, compared to spectral transformation techniques such as first derivative, continuum removal and log-transformed (Log(1/R)) spectra. The study was based on a greenhouse experiment with a savanna grass species (Digitariaeriantha). Spectral measurements were made using a spectrometer. The D. eriantha was cut, dried and chemically analyzed for foliar N and P concentrations. WR spectra were determined by calculating the residual from the modelled leaf water spectra using a nonlinear spectral matching technique and observed leaf spectra. Results indicated that the WR spectra yielded a higher N retrieval accuracy than a traditional first derivative transformation (R2 = 0.84, RMSE = 0.28) compared to R2 = 0.59, RMSE = 0.45 for PLSR. Similar trends were observed for SMLR. The highest P retrieval accuracy was derived from WR spectra using SMLR (R2 = 0.64, RMSE = 0.067), while the traditional first derivative and continuum removal resulted in lower accuracy. Only when using PLSR did the first derivative result in a higher P retrieval accuracy (R2 = 0.47, RMSE = 0.07) than the WR spectra (R2 = 0.43, RMSE = 0.070). It was concluded that the water removal technique is a promising technique to minimize the perturbing effect of foliar water content when estimating grass nutrient concentrations.enNitrogen concentrationPhosphorus concentrationWater removalContinuum removalBootstrappingArticleRamoelo, A., Skidmore, A., Schlerf, M., Mathieu, R. S., & Heitkönig, I. (2011). Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations. http://hdl.handle.net/10204/5070Ramoelo, Abel, AK Skidmore, M Schlerf, Renaud SA Mathieu, and IMA Heitkönig "Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations." (2011) http://hdl.handle.net/10204/5070Ramoelo A, Skidmore A, Schlerf M, Mathieu RS, Heitkönig I. Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations. 2011; http://hdl.handle.net/10204/5070.TY - Article AU - Ramoelo, Abel AU - Skidmore, AK AU - Schlerf, M AU - Mathieu, Renaud SA AU - Heitkönig, IMA AB - Information about the distribution of grass foliar nitrogen (N) and phosphorus (P) is important for understanding rangeland vitality and for facilitating the effective management of wildlife and livestock. Water absorption effects in the near-infrared (NIR) and shortwave-infrared (SWIR) regions pose a challenge for nutrient estimation using remote sensing. The aim of this study was to test the utility of water-removed (WR) spectra in combination with partial least-squares regression (PLSR) and stepwise multiple linear regression (SMLR) to estimate foliar N and P, compared to spectral transformation techniques such as first derivative, continuum removal and log-transformed (Log(1/R)) spectra. The study was based on a greenhouse experiment with a savanna grass species (Digitariaeriantha). Spectral measurements were made using a spectrometer. The D. eriantha was cut, dried and chemically analyzed for foliar N and P concentrations. WR spectra were determined by calculating the residual from the modelled leaf water spectra using a nonlinear spectral matching technique and observed leaf spectra. Results indicated that the WR spectra yielded a higher N retrieval accuracy than a traditional first derivative transformation (R2 = 0.84, RMSE = 0.28) compared to R2 = 0.59, RMSE = 0.45 for PLSR. Similar trends were observed for SMLR. The highest P retrieval accuracy was derived from WR spectra using SMLR (R2 = 0.64, RMSE = 0.067), while the traditional first derivative and continuum removal resulted in lower accuracy. Only when using PLSR did the first derivative result in a higher P retrieval accuracy (R2 = 0.47, RMSE = 0.07) than the WR spectra (R2 = 0.43, RMSE = 0.070). It was concluded that the water removal technique is a promising technique to minimize the perturbing effect of foliar water content when estimating grass nutrient concentrations. DA - 2011 DB - ResearchSpace DP - CSIR KW - Nitrogen concentration KW - Phosphorus concentration KW - Water removal KW - Continuum removal KW - Bootstrapping LK - https://researchspace.csir.co.za PY - 2011 SM - 0924-2716 T1 - Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations TI - Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations UR - http://hdl.handle.net/10204/5070 ER -