Fuzzy methods for categorical mapping with image-based land cover data.
Saved in:
| Title: | Fuzzy methods for categorical mapping with image-based land cover data. |
|---|---|
| Authors: | Zhang, Jingxiong1, Stuart, Neil1 |
| Source: | International Journal of Geographical Information Science. Mar2001, Vol. 15 Issue 2, p175-195. 21p. 21 Black and White Photographs, 1 Diagram, 6 Charts, 1 Graph. |
| Subjects: | Fuzzy systems, Geography |
| Abstract: | This paper presents an approach to capturing and representing the uncertainty inherent in any attempt to classify continuously varying geographical phenomena into discrete categories. This uncertainty is captured during a visual photo-interpretation and a computerised image classification process and encoded as a series of fuzzy surfaces. These store the fuzzy membership values (FMVs) of each location to all candidate classes in a desired classification scheme. These surfaces are used to explore graphically the underlying variations in the level of certainty of assigning candidate classes to individual locations. A technique is presented that analyses these FMV surfaces by applying alpha-cuts (thresholds) to derive a series of traditional categorical maps in the form of vector polygons. The relative certainty of the attribute classification is used to determine an appropriate Epsilon band width around boundary lines separating different land cover classes on the resulting categorical map. The approach is tested on the practical problem of producing categorical maps of land cover for a suburban area. Uncertainty surfaces are derived for land cover classifications created both from photogrammetric interpretation and from satellite image classification. A series of categorical maps of land cover are derived for different minimum levels of certainty in the attribute classification. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Geographical Information Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 4273403 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Fuzzy methods for categorical mapping with image-based land cover data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Jingxiong%22">Zhang, Jingxiong</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Stuart%2C+Neil%22">Stuart, Neil</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Geographical+Information+Science%22">International Journal of Geographical Information Science</searchLink>. Mar2001, Vol. 15 Issue 2, p175-195. 21p. 21 Black and White Photographs, 1 Diagram, 6 Charts, 1 Graph. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Fuzzy+systems%22">Fuzzy systems</searchLink><br /><searchLink fieldCode="DE" term="%22Geography%22">Geography</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper presents an approach to capturing and representing the uncertainty inherent in any attempt to classify continuously varying geographical phenomena into discrete categories. This uncertainty is captured during a visual photo-interpretation and a computerised image classification process and encoded as a series of fuzzy surfaces. These store the fuzzy membership values (FMVs) of each location to all candidate classes in a desired classification scheme. These surfaces are used to explore graphically the underlying variations in the level of certainty of assigning candidate classes to individual locations. A technique is presented that analyses these FMV surfaces by applying alpha-cuts (thresholds) to derive a series of traditional categorical maps in the form of vector polygons. The relative certainty of the attribute classification is used to determine an appropriate Epsilon band width around boundary lines separating different land cover classes on the resulting categorical map. The approach is tested on the practical problem of producing categorical maps of land cover for a suburban area. Uncertainty surfaces are derived for land cover classifications created both from photogrammetric interpretation and from satellite image classification. A series of categorical maps of land cover are derived for different minimum levels of certainty in the attribute classification. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Geographical Information Science is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=4273403 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/13658810010005543 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 175 Subjects: – SubjectFull: Fuzzy systems Type: general – SubjectFull: Geography Type: general Titles: – TitleFull: Fuzzy methods for categorical mapping with image-based land cover data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhang, Jingxiong – PersonEntity: Name: NameFull: Stuart, Neil IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2001 Type: published Y: 2001 Identifiers: – Type: issn-print Value: 13658816 Numbering: – Type: volume Value: 15 – Type: issue Value: 2 Titles: – TitleFull: International Journal of Geographical Information Science Type: main |
| ResultId | 1 |
