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dc.contributor.author Ullah, S
dc.contributor.author Skidmore, AK
dc.contributor.author Ramoelo, Abel
dc.contributor.author Groen, TA
dc.contributor.author Naeem, M
dc.contributor.author Ali, A
dc.date.accessioned 2014-07-18T10:02:21Z
dc.date.available 2014-07-18T10:02:21Z
dc.date.issued 2014-05
dc.identifier.citation Ullah, S, Skidmore, A.K, Ramoelo, A, Groen, T.A, Naeem, M and Ali, A. 2014. Retrieval of leaf water content spanning the visible to thermal infrared spectra. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 93, pp 56-64 en_US
dc.identifier.issn 0924-2716
dc.identifier.uri http://ac.els-cdn.com/S0924271614000926/1-s2.0-S0924271614000926-main.pdf?_tid=49360422-06a5-11e4-8783-00000aacb35d&acdnat=1404826949_a3a5389467b15d18c2d97d38bcf24126
dc.identifier.uri http://hdl.handle.net/10204/7512
dc.description Copyright: 2014 Elsevier. This is the pre print version of the work. The definitive version is published in ISPRS Journal of Photogrammetry and Remote Sensing, vol. 93, pp 56-64 en_US
dc.description.abstract The objective of this study was to investigate the entire spectra (from visible to the thermal infrared; 0.390 µm -14.0 µm) to retrieve leaf water content in a consistent manner. Narrow-band spectral indices (calculated from all possible two band combinations) and a partial least square regression (PLSR) were used to assess the strength of each spectral region. The coefficient of determination (R(sup2) and root mean square error (RMSE) were used to report the prediction accuracy of spectral indices and PLSR models. In the visible-near infrared and shortwave infrared (VNIR-SWIR), the most accurate spectral index yielded R(sup2) of 0.89 and RMSE of 7.60%, whereas in the mid infrared (MIR) the highest R(sup2) was 0.93 and RMSE of 5.97%. Leaf water content was poorly predicted using two-band indices developed from the thermal infrared (R(sup2)=0.33). The most accurate PLSR model resulted from MIR reflectance spectra (R(sup2)=0.96, RMSE=4.74% and RMSE(subCV)=6.17%) followed by VNIR-SWIR reflectance spectra (R(sup2)=0.91, RMSE=6.90% and RMSE(subCV)=7.32%). Using thermal infrared (TIR) spectra, the PLSR model yielded a moderate retrieval accuracy (R(sup2)=0.67, RMSE=13.27% and RMSE(subCV)=16.39%). This study demonstrated that the MIR and SWIR domains were the most sensitive spectral region for the retrieval of leaf water content. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries Workflow;12976
dc.subject Water stress en_US
dc.subject Statistical models en_US
dc.subject Leaf water content en_US
dc.subject Remote sensing en_US
dc.title Retrieval of leaf water content spanning the visible to thermal infrared spectra en_US
dc.type Article en_US


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