L-band synthetic aperture radar imagery performs better than optical datasets at retrieving woody fractional cover in deciduous, dry savannahs
dc.contributor.author | Naidoo, Laven | |
dc.contributor.author | Mathieu, Renaud | |
dc.contributor.author | Main, Russell | |
dc.contributor.author | Wessels, K.J. (Konrad) | |
dc.contributor.author | Asner, Gregory P. | |
dc.date.accessioned | 2016-10-19T11:10:17Z | |
dc.date.issued | 2016-10 | |
dc.description.abstract | Woody canopy cover (CC) is the simplesttwo dimensional metric for assessing the presence ofthe woody component in savannahs, but detailed validated maps are not currently available in southern African savannahs. A number of international EO programs (including in savannah landscapes) advocate and use optical LandSAT imagery for regional to country-wide mapping of woody canopy cover. However, previous research has shown that L-band Synthetic Aperture Radar (SAR) provides good performance at retrieving woody canopy cover in southern African savannahs. This study’s objective was to evaluate, compare and use in combination L-band ALOS PALSAR and LandSAT-5 TM, in a Random Forest environment, to assess the benefits of using LandSAT compared to ALOS PALSAR. Additional objectives saw the testing of LandSAT-5 image seasonality, spectral vegetation indices and image textures for improved CC modelling. Results showed that LandSAT-5 imagery acquired in the summer and autumn seasons yielded the highest single season modelling accuracies (R2 between 0.47 and 0.65), depending on the year but the combination of multi-seasonal images yielded higher accuracies (R2 between 0.57 and 0.72). The derivation of spectral vegetation indices and image textures and their combinations with optical reflectance bands provided minimal improvement with no optical-only result exceeding the winter SAR L-band backscatter alone results (R2 of ∼0.8). The integration of seasonally appropriate LandSAT-5 image reflectance and L-band HH and HV backscatter data does provide a significant improvement for CC modelling at the higher end of the model performance (R2 between 0.83 and 0.88), but we conclude that L-band only based CC modelling be recommended for South African regions | en_ZA |
dc.description.department | Geography, Geoinformatics and Meteorology | en_ZA |
dc.description.embargo | 2017-10-31 | |
dc.description.librarian | hb2016 | en_ZA |
dc.description.uri | http://www.elsevier.com/locate/jag | en_ZA |
dc.identifier.citation | Naidoo, L, Mathieu, R, Main, R, Wessels, K & Asner, GP 2016, 'L-band synthetic aperture radar imagery performs better than optical datasets at retrieving woody fractional cover in deciduous, dry savannahs', International Journal of Applied Earth Observation and Geoinformation, vol. 52, pp. 54-64. | en_ZA |
dc.identifier.issn | 1569-8432 (print) | |
dc.identifier.issn | 1872-826X (online) | |
dc.identifier.other | 10.1016/j.jag.2016.05.006 | |
dc.identifier.uri | http://hdl.handle.net/2263/57387 | |
dc.language.iso | en | en_ZA |
dc.publisher | Elsevier | en_ZA |
dc.rights | © 2016 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in International Journal of Applied Earth Observation and Geoinformation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in International Journal of Applied Earth Observation and Geoinformation, vol. 52, pp. 54-64, 2016. doi : 10.1016/j.jag.2016.05.006. | en_ZA |
dc.subject | LandSAT-5 | en_ZA |
dc.subject | Textures | en_ZA |
dc.subject | Spectral vegetation indices | en_ZA |
dc.subject | Random forest | en_ZA |
dc.subject | Woody canopy cover (WCC) | en_ZA |
dc.subject | Synthetic aperture radar (SAR) | en_ZA |
dc.title | L-band synthetic aperture radar imagery performs better than optical datasets at retrieving woody fractional cover in deciduous, dry savannahs | en_ZA |
dc.type | Postprint Article | en_ZA |