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Subsequently, this work sought to explore the robustness of integrating texture metrics and red-edge in predicting the above-ground biomass of grass growing under different levels of mowing and burning in grassland management treatments. Based on the sparse partial least squares regression algorithm, the results of this study showed that red-edge vegetation indices improved above-ground grass biomass from a root mean square error of perdition (RMSEP) of 0.83 kg\/m2 to an RMSEP of 0.55 kg\/m2. Texture models further improved the accuracy of grass biomass estimation to an RMSEP of 0.35 kg\/m2. The combination of texture models and red-edge derivatives (red-edge-derived vegetation indices) resulted in an optimal prediction accuracy of RMSEP 0.2 kg\/m2 across all grassland management treatments. These results illustrate the prospect of combining texture metrics with the red-edge in predicting grass biomass across complex grassland management treatments. This offers the detailed spatial information required for grassland policy-making and sustainable grassland management in data-scarce regions such as southern Africa.<\/jats:p>","DOI":"10.3390\/rs9010055","type":"journal-article","created":{"date-parts":[[2017,1,11]],"date-time":"2017-01-11T10:36:49Z","timestamp":1484131009000},"page":"55","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":77,"title":["Estimating Biomass of Native Grass Grown under Complex Management Treatments Using WorldView-3 Spectral Derivatives"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4589-7099","authenticated-orcid":false,"given":"Mbulisi","family":"Sibanda","sequence":"first","affiliation":[{"name":"School of Agriculture, Earth and Environmental Science, University of KwaZulu-Natal, P. Bag X01, Scottsville, Pietermaritzburg 3209, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Onisimo","family":"Mutanga","sequence":"additional","affiliation":[{"name":"School of Agriculture, Earth and Environmental Science, University of KwaZulu-Natal, P. Bag X01, Scottsville, Pietermaritzburg 3209, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mathieu","family":"Rouget","sequence":"additional","affiliation":[{"name":"School of Agriculture, Earth and Environmental Science, University of KwaZulu-Natal, P. Bag X01, Scottsville, Pietermaritzburg 3209, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9205-756X","authenticated-orcid":false,"given":"Lalit","family":"Kumar","sequence":"additional","affiliation":[{"name":"School of Environmental &amp; Rural Science, University of New England, Armidale NSW 2351, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,1,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"097696","DOI":"10.1117\/1.JRS.9.097696","article-title":"Review of the use of remote sensing for biomass estimation to support renewable energy generation","volume":"9","author":"Kumar","year":"2015","journal-title":"J. Appl. 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