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A comparison of supervised and rule-based object-orientated classification for forest mapping
Thesis (MSc (Geography and Environmental Studies))--University of Stellenbosch, 2010.
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : University of Stellenbosch
2010
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| _version_ | 1867613915130626048 |
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| access_status_str | Open Access |
| author | Stephenson, Garth Roy |
| author2 | Van Niekerk, Adriaan |
| author_browse | Stephenson, Garth Roy Van Niekerk, Adriaan |
| author_facet | Van Niekerk, Adriaan Stephenson, Garth Roy |
| author_sort | Stephenson, Garth Roy |
| collection | Thesis |
| dc_rights_str_mv | University of Stellenbosch |
| description | Thesis (MSc (Geography and Environmental Studies))--University of Stellenbosch, 2010. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/4363 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:43:43.080Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2010 |
| publishDateRange | 2010 |
| publishDateSort | 2010 |
| publisher | Stellenbosch : University of Stellenbosch |
| publisherStr | Stellenbosch : University of Stellenbosch |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/4363 A comparison of supervised and rule-based object-orientated classification for forest mapping Stephenson, Garth Roy Van Niekerk, Adriaan University of Stellenbosch. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies. Remote sensing Supervised rule-set classification Forest mapping Dissertations -- Earth sciences Theses -- Earth sciences Thesis (MSc (Geography and Environmental Studies))--University of Stellenbosch, 2010. ENGLISH ABSTRACT: Supervised classifiers are the most popular approach for image classification due to their high accuracies, ease of use and strong theoretical grounding. Their primary disadvantage is the high level of user input required during the creation of the data needed to train the classifier. One alternative to supervised classification is an expert-system rule-based approach where expert knowledge is used to create a set of rules which can be applied to multiple images. This research compared supervised and expert-system rule-based approaches for forest mapping. For this purpose two SPOT 5 images were acquired and atmospherically corrected. Field visits, aerial photography, high resolution imagery and expert forestry knowledge were used for the compilation of the training data and the development of a rule-set. Both approaches were evaluated in an object-orientated environment. It was found that the accuracy of the resulting maps was equivalent, with both techniques returning an overall classification accuracy of 90%. This suggests that cost-effectiveness is the decisive factor for determining which method is superior. Although the development of the rule-set was time-consuming and challenging, it did not require any training data. In contrast, the supervised approach required a large number of training areas for each image classified, which was time-consuming and costly. Significantly more training areas will be required when the technique is applied to large areas, especially when multiple images are used. It was concluded that the rule-set is more cost-effective when applied at regional scale, but it is not viable for mapping small areas. AFRIKAANSE OPSOMMING: Gerigte klassifiseerders is die gewildste benadering tot beeldklassifikasie as gevolg van hulle hoë graad van akkuraatheid, maklike aanwending en kragtige teoretiese fundering. Die primere nadeel van gerigte klassifikasie is die hoë vlak van gebruikersinsette wat benodig word tydens die skepping van opleidingsdata. 'n Alternatief vir gerigte klassifikasie is 'n deskundige stelsel waarin ‘n reëlgebaseerde benadering gevolg word om deskundige kennis aan te wend vir die opstel van 'n stel reëls wat op meervoudige beelde toegepas kan word. Hierdie navorsing het gerigte en deskundige stelsel benaderings toegepas vir bosboukartering om die twee benaderings met mekaar te vergelyk. Vir dié doel is twee SPOT 5 beelde verkry en atmosferies gekorrigeer. Veldbesoeke, lugfotografie, hoë-resolusie beelde en deskundige bosboukennis is aangewend om opleidingsdata saam te stel en die stel reëls te ontwikkel. Beide benaderings is in 'n objekgeoriënteerde omgewing beoordeel. Die akkuraatheidsvlakke van die resulterende kaarte was ewe hoog vir beide tegnieke met 'n algehele klassifikasie-akkuraatheid van 90%. Dit wil dus voorkom asof koste-effektiwiteit eerder as akkuraatheid die deurslaggewende faktor is om te bepaal watter metode die beste is. Alhoewel die ontwikkeling van die stel reëls tydrowend en uitdagend was, het dit geen opleidingsdata vereis nie. In teenstelling hiermee is 'n groot aantal opleidingsgebiede geskep vir elke beeld wat met gerigte klassifikasie verwerk is – 'n tydrowende en duur opsie. Dit is duidelik dat meer opleidingsgebiede benodig sal word wanneer die tegniek op groot gebiede toegepas word, veral omdat meervoudige beelde gebruik sal word. Gevolglik sal die stel reëls meer kosteeffektief wees wanneer dit op streekskaal toegepas word. ‘n Deskundige stelsel benadering is egter nie lewensvatbaar vir die kartering van klein gebiede nie. Masters 2010-02-24T07:41:14Z 2010-08-13T15:02:02Z 2010-02-24T07:41:14Z 2010-08-13T15:02:02Z 2010-03 Thesis http://hdl.handle.net/10019.1/4363 en University of Stellenbosch 60 p. : ill., maps application/pdf Stellenbosch : University of Stellenbosch |
| spellingShingle | Remote sensing Supervised rule-set classification Forest mapping Dissertations -- Earth sciences Theses -- Earth sciences Stephenson, Garth Roy A comparison of supervised and rule-based object-orientated classification for forest mapping |
| title | A comparison of supervised and rule-based object-orientated classification for forest mapping |
| title_full | A comparison of supervised and rule-based object-orientated classification for forest mapping |
| title_fullStr | A comparison of supervised and rule-based object-orientated classification for forest mapping |
| title_full_unstemmed | A comparison of supervised and rule-based object-orientated classification for forest mapping |
| title_short | A comparison of supervised and rule-based object-orientated classification for forest mapping |
| title_sort | comparison of supervised and rule based object orientated classification for forest mapping |
| topic | Remote sensing Supervised rule-set classification Forest mapping Dissertations -- Earth sciences Theses -- Earth sciences |
| url | http://hdl.handle.net/10019.1/4363 |
| work_keys_str_mv | AT stephensongarthroy acomparisonofsupervisedandrulebasedobjectorientatedclassificationforforestmapping AT stephensongarthroy comparisonofsupervisedandrulebasedobjectorientatedclassificationforforestmapping |