Utility of texture combinations computed from fused WorldView-2 imagery in discriminating commercial forest species. Issue 23 (2nd December 2022)

• Record Type: Journal Article
• Authors: Sibiya, Bongokuhle; Lottering, Romano; Odindi, John
• Is Part Of: Geocarto international. Volume 37:Issue 23(2023)
• Page Start: 6915
• Page End: 6931
• Publication Date: 2022-12-02
• Subjects: Texture combinations -- species discrimination -- PLS-DA -- SPLS-DA -- WorldView-2; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2021.1952316
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: Commercial forest species discrimination is valuable for optimal management of commercial forests. Therefore, second-order image texture combinations computed from a 0.5 m WorldView-2 pan-sharpened image integrated with sparse partial least squares discriminant analysis (SPLS-DA) and partial least squares discriminant analysis (PLS-DA) were used to discriminate commercial forest species. The findings show that the SPLS-DA model, which is characterised by concurrent variable selection and reduction of data dimensionality, produced an overall classification accuracy of 86%, with an allocation disagreement of 9 and a quantity disagreement of 5. Conversely, the PLS-DA model with variable importance in projection (VIP) produced an overall classification accuracy of 81%, with an allocation disagreement of 12 and a quantity disagreement of 7. Overall, this study demonstrates the value of second-order image texture combinations in discriminating commercial forest species and presents an opportunity for improved commercial forest species delineation.