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Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data

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dc.contributor.author Malahlela, OE
dc.contributor.author Cho, Moses A
dc.contributor.author Mutanga, O
dc.date.accessioned 2016-01-20T09:42:26Z
dc.date.available 2016-01-20T09:42:26Z
dc.date.issued 2015-07
dc.identifier.citation Malahlela, O.E., Cho, M.A. and Mutanga, O. 2015. Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data. Biological Invasions, Vol. 17(7), pp. 2027-2042 en_US
dc.identifier.issn 1387-3547
dc.identifier.uri http://link.springer.com/article/10.1007%2Fs10530-015-0858-7
dc.identifier.uri http://hdl.handle.net/10204/8343
dc.description Copyright: 2015 Springer Verlag. Due to copyright restrictions, the attached PDF file only contains an abstract of the full text item. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in Biological Invasions, Vol. 17(7), pp. 2027-2042 en_US
dc.description.abstract Globally, subtropical forests are rich in biodiversity. However, the native biodiversity in these forests is threatened by the presence of invasive species such as Chromolaena odorata (L.) King and Robinson, which thrives in forest canopy gaps. Our study explored the utility of WorldView-2 data, an 8-band high resolution (2 m) imagery for mapping the probability of C. odorata occurrence (presence/absence) in canopy gaps of a subtropical forest patch, the Dukuduku forest, South Africa. An integrated modelling approach involving the WorldView-2 vegetation indices and ancillary environmental data was also assessed. The results showed a higher performance of the environmental data only model (deviance or D2 = 0.52, p\0.05, n = 77) when compared to modelling with WorldView-2 vegetation indices such as the enhanced vegetation index, simple ratio indices and red edge normalized difference vegetation index (D2 = 0.30, p\0.05, n = 77). The integrated model explained the highest presence/absence variance of C. odorata (D2 = 0.71, i.e. 71 %). This model was used to derive a probability map indicating the occurrence of invasive species in forest gaps. A 2 9 2 error matrix table and the receiver operating characteristic curve derived from an independent validation dataset (n = 38) were used to assess the model accuracy. Approximately 87 % of canopy gaps containing C. odorata were correctly predicted at probability threshold of 0.3. The derived probability map of C. odorata occurrence could assist management in prioritizing target areas for eradication of the species. en_US
dc.language.iso en en_US
dc.publisher Springer Verlag en_US
dc.relation.ispartofseries Workflow;15445
dc.subject Forest management en_US
dc.subject Remote sensing en_US
dc.subject Invasive species en_US
dc.subject ROC curve en_US
dc.title Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data en_US
dc.type Article en_US
dc.identifier.apacitation Malahlela, O., Cho, M. A., & Mutanga, O. (2015). Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data. http://hdl.handle.net/10204/8343 en_ZA
dc.identifier.chicagocitation Malahlela, OE, Moses A Cho, and O Mutanga "Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data." (2015) http://hdl.handle.net/10204/8343 en_ZA
dc.identifier.vancouvercitation Malahlela O, Cho MA, Mutanga O. Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data. 2015; http://hdl.handle.net/10204/8343. en_ZA
dc.identifier.ris TY - Article AU - Malahlela, OE AU - Cho, Moses A AU - Mutanga, O AB - Globally, subtropical forests are rich in biodiversity. However, the native biodiversity in these forests is threatened by the presence of invasive species such as Chromolaena odorata (L.) King and Robinson, which thrives in forest canopy gaps. Our study explored the utility of WorldView-2 data, an 8-band high resolution (2 m) imagery for mapping the probability of C. odorata occurrence (presence/absence) in canopy gaps of a subtropical forest patch, the Dukuduku forest, South Africa. An integrated modelling approach involving the WorldView-2 vegetation indices and ancillary environmental data was also assessed. The results showed a higher performance of the environmental data only model (deviance or D2 = 0.52, p\0.05, n = 77) when compared to modelling with WorldView-2 vegetation indices such as the enhanced vegetation index, simple ratio indices and red edge normalized difference vegetation index (D2 = 0.30, p\0.05, n = 77). The integrated model explained the highest presence/absence variance of C. odorata (D2 = 0.71, i.e. 71 %). This model was used to derive a probability map indicating the occurrence of invasive species in forest gaps. A 2 9 2 error matrix table and the receiver operating characteristic curve derived from an independent validation dataset (n = 38) were used to assess the model accuracy. Approximately 87 % of canopy gaps containing C. odorata were correctly predicted at probability threshold of 0.3. The derived probability map of C. odorata occurrence could assist management in prioritizing target areas for eradication of the species. DA - 2015-07 DB - ResearchSpace DP - CSIR KW - Forest management KW - Remote sensing KW - Invasive species KW - ROC curve LK - https://researchspace.csir.co.za PY - 2015 SM - 1387-3547 T1 - Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data TI - Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data UR - http://hdl.handle.net/10204/8343 ER - en_ZA


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