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Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines
Dissertation (MSc)--University of Pretoria, 2012.
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| Format: | Thesis |
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University of Pretoria
2013
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| _version_ | 1867613482020503552 |
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| access_status_str | Open Access |
| author2 | Robertson, Mark P. |
| author_browse | Robertson, Mark P. |
| author_facet | Robertson, Mark P. |
| collection | Thesis |
| dc_rights_str_mv | © 2012, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria E12/9/51/ |
| description | Dissertation (MSc)--University of Pretoria, 2012. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/31492 |
| institution | University of Pretoria (South Africa) |
| last_indexed | 2026-06-10T12:36:50.758Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/31492 Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines Robertson, Mark P. Ismail, Riyad Atkinson, Jonathan Tom UCTD Dissertation (MSc)--University of Pretoria, 2012. The invasive plant known as bugweed (Solanum mauritianum) is a notorious invader of forestry plantations in the eastern parts of South Africa. Not only is bugweed considered to be one of five most widespread invasive alien plant (IAP) species in the summer rainfall regions of South Africa but it is also one of the worst invasive alien plants in Africa. It forms dense infestations that not only impacts upon commercial forestry activities but also causes significant ecological and environment damage within natural ecotones. Effective weed management efforts therefore require new and robust approaches to accurately detect; map and monitor weed distribution in order to mitigate the impact on forestry operations. In this regard, support vector machines (SVM) offer a promising alternative to conventional machine learning and pattern recognition approaches to weed detection and mapping using remote sensing. The main objective of this research was to determine the utility of using a recursive feature elimination support vector machine (SVM-RFE) based approach with a 272-waveband AISA Eagle image to detect and map the presence of co-occuring bugweed within mature Pinus patula compartments in KwaZulu Natal. The SVM-RFE approach required only 17 optimal bands from the original 272 band image to produce a classification accuracy of 93% and True Skills Statistic of 0.83. Results from this study indicate that (1) there is definite potential for using SVMs for accurate detection and mapping of bugweed species in commercial plantations and (2) it is not necessary to use the entire 272-band dataset to accurately detect bugweed occurrence as the SVM-RFE approach will identify an optimal subset of wavebands for weed detection enabling substantially improved data processing and analysis. Zoology and Entomology MSc Unrestricted 2013-09-09T12:19:57Z 2012-12-14 2013-09-09T12:19:57Z 2012-09-07 2012-12-14 2012-12-11 Dissertation Atkinson, JT 2012-12-14, Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/31492> E12/9/51/gm http://hdl.handle.net/2263/31492 http://upetd.up.ac.za/thesis/available/etd-12112012-151915/ © 2012, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria E12/9/51/ application/pdf University of Pretoria |
| spellingShingle | UCTD Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines |
| title | Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines |
| title_full | Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines |
| title_fullStr | Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines |
| title_full_unstemmed | Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines |
| title_short | Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines |
| title_sort | mapping bugweed solanum mauritianum infestations in pinus patula plantations using hyperspectral imagery and support vector machines |
| topic | UCTD |
| url | http://hdl.handle.net/2263/31492 http://upetd.up.ac.za/thesis/available/etd-12112012-151915/ |