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Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park

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dc.contributor.author Debba, Pravesh
dc.date.accessioned 2009-08-28T12:33:14Z
dc.date.available 2009-08-28T12:33:14Z
dc.date.issued 2009-07
dc.identifier.citation Debba, P. 2009. Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park. Rhodes University, South Africa, July 2009. pp 1-51 en
dc.identifier.uri http://hdl.handle.net/10204/3554
dc.description This presentation was presented at Rhodes University en
dc.description.abstract This presentation to the SASA Eastern Cape Chapter at Rhodes University studies the variability within a species class and the variability between the species classes of seven spectrally similar tree species and presents ways in which the within-species class variability can be reduced compared to the between-species class variability. Furthermore, two classification approaches with spectral angle mapper: (i) using a spectral library composed of one spectrum (endmember) per species and (ii) a multiple endmember approach is presented, conventionally called K-nearest neighbour classifier. en
dc.language.iso en en
dc.subject Tree classification en
dc.subject Spectral matching en
dc.subject Kruger national park en
dc.subject Classification techniques en
dc.subject Hyperspectral remote sensing en
dc.subject Iterated conditional modes en
dc.subject ICM en
dc.subject Spectral angle mapper classifier en
dc.subject SAM en
dc.subject Species variability en
dc.subject Tree species en
dc.subject K-nearest neighbour classifier en
dc.title Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park en
dc.type Conference Presentation en
dc.identifier.apacitation Debba, P. (2009). Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park. http://hdl.handle.net/10204/3554 en_ZA
dc.identifier.chicagocitation Debba, Pravesh. "Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park." (2009): http://hdl.handle.net/10204/3554 en_ZA
dc.identifier.vancouvercitation Debba P, Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park; 2009. http://hdl.handle.net/10204/3554 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Debba, Pravesh AB - This presentation to the SASA Eastern Cape Chapter at Rhodes University studies the variability within a species class and the variability between the species classes of seven spectrally similar tree species and presents ways in which the within-species class variability can be reduced compared to the between-species class variability. Furthermore, two classification approaches with spectral angle mapper: (i) using a spectral library composed of one spectrum (endmember) per species and (ii) a multiple endmember approach is presented, conventionally called K-nearest neighbour classifier. DA - 2009-07 DB - ResearchSpace DP - CSIR KW - Tree classification KW - Spectral matching KW - Kruger national park KW - Classification techniques KW - Hyperspectral remote sensing KW - Iterated conditional modes KW - ICM KW - Spectral angle mapper classifier KW - SAM KW - Species variability KW - Tree species KW - K-nearest neighbour classifier LK - https://researchspace.csir.co.za PY - 2009 T1 - Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park TI - Improving classification accuracy of spectrally similar tree species: a complex case study in the Kruger National Park UR - http://hdl.handle.net/10204/3554 ER - en_ZA


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