Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data
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| Title: | Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data |
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| Authors: | Segl, K. segl@gfz-potsdam.de, Roessner, S.1, Heiden, U.1, Kaufmann, H.1 |
| Source: | ISPRS Journal of Photogrammetry & Remote Sensing. Jun2003, Vol. 58 Issue 1/2, p99. 14p. |
| Subjects: | Urban growth, Image processing |
| Abstract: | The urban environment is characterized by an intense multifunctional use of available spaces, where the preservation of open green spaces is of special importance. For this purpose, area-wide urban biotope mapping based on CIR aerial photographs has been carried out for the large cities in Germany during the last 10 years. Because of dynamic urban development and high mapping costs, the municipal authorities are interested in effective methods for mapping urban surface cover types, which can be used for evaluation of ecological conditions in urban structures and supporting updates of biotope maps. Against this background, airborne hyperspectral remote sensing data of the DAIS 7915 instrument have been analyzed for a test site in the city of Dresden (Germany) with regard to their potential for automated material-oriented identification of urban surface cover types. Previous investigations have shown that the high spectral and spatial variabilities of these data require the development of special methods, which are capable of dealing with the resulting mixed-pixel problem in its specific characteristics in urban areas. Earlier, methodological developments led to an approach based on a combination of spectral classification and pixel-oriented unmixing techniques to facilitate sensible endmember selection based on the reflective bands of the DAIS instrument. This approach is now extended by a shape-based classification technique including the thermal bands of the DAIS instrument to improve the detection of buildings during the process of identifying seedling pixels, which represent the starting points for linear spectral unmixing. This new approach increases the reliability of differentiation between buildings and open spaces, leading to more accurate results for the spatial distribution of surface cover types. Thus, the new approach significantly enhances the exploitation of the information potential of the hyperspectral DAIS 7915 data for an area-wide identification of urban surface cover types. [Copyright &y& Elsevier] |
| Copyright of ISPRS Journal of Photogrammetry & Remote Sensing is the property of Elsevier B.V. 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 | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 9711767 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Segl%2C+K%2E%22">Segl, K.</searchLink><i> segl@gfz-potsdam.de</i><br /><searchLink fieldCode="AR" term="%22Roessner%2C+S%2E%22">Roessner, S.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Heiden%2C+U%2E%22">Heiden, U.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kaufmann%2C+H%2E%22">Kaufmann, H.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22ISPRS+Journal+of+Photogrammetry+%26+Remote+Sensing%22">ISPRS Journal of Photogrammetry & Remote Sensing</searchLink>. Jun2003, Vol. 58 Issue 1/2, p99. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Urban+growth%22">Urban growth</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The urban environment is characterized by an intense multifunctional use of available spaces, where the preservation of open green spaces is of special importance. For this purpose, area-wide urban biotope mapping based on CIR aerial photographs has been carried out for the large cities in Germany during the last 10 years. Because of dynamic urban development and high mapping costs, the municipal authorities are interested in effective methods for mapping urban surface cover types, which can be used for evaluation of ecological conditions in urban structures and supporting updates of biotope maps. Against this background, airborne hyperspectral remote sensing data of the DAIS 7915 instrument have been analyzed for a test site in the city of Dresden (Germany) with regard to their potential for automated material-oriented identification of urban surface cover types. Previous investigations have shown that the high spectral and spatial variabilities of these data require the development of special methods, which are capable of dealing with the resulting mixed-pixel problem in its specific characteristics in urban areas. Earlier, methodological developments led to an approach based on a combination of spectral classification and pixel-oriented unmixing techniques to facilitate sensible endmember selection based on the reflective bands of the DAIS instrument. This approach is now extended by a shape-based classification technique including the thermal bands of the DAIS instrument to improve the detection of buildings during the process of identifying seedling pixels, which represent the starting points for linear spectral unmixing. This new approach increases the reliability of differentiation between buildings and open spaces, leading to more accurate results for the spatial distribution of surface cover types. Thus, the new approach significantly enhances the exploitation of the information potential of the hyperspectral DAIS 7915 data for an area-wide identification of urban surface cover types. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of ISPRS Journal of Photogrammetry & Remote Sensing is the property of Elsevier B.V. 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/S0924-2716(03)00020-0 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 99 Subjects: – SubjectFull: Urban growth Type: general – SubjectFull: Image processing Type: general Titles: – TitleFull: Fusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Segl, K. – PersonEntity: Name: NameFull: Roessner, S. – PersonEntity: Name: NameFull: Heiden, U. – PersonEntity: Name: NameFull: Kaufmann, H. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2003 Type: published Y: 2003 Identifiers: – Type: issn-print Value: 09242716 Numbering: – Type: volume Value: 58 – Type: issue Value: 1/2 Titles: – TitleFull: ISPRS Journal of Photogrammetry & Remote Sensing Type: main |
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