File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.5194/isprs-archives-XLII-2-W7-919-2017
- Scopus: eid_2-s2.0-85031023613
- Find via
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: Using coupled nonnegative matrix factorization (CNMF) un-mixing for high spectral and spatial resolution data fusion to estimate urban impervious surface and urban ecological environment
Title | Using coupled nonnegative matrix factorization (CNMF) un-mixing for high spectral and spatial resolution data fusion to estimate urban impervious surface and urban ecological environment |
---|---|
Authors | |
Keywords | Data fusion Impervious surface Coupled nonnegative matrix factorization |
Issue Date | 2017 |
Citation | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 2017, v. 42, n. 2W7, p. 919-923 How to Cite? |
Abstract | © Authors 2017. CC BY 4.0 License. Remote sensing techniques have great potential in providing accurate and timely information in urban areas. Estimation of impervious surfaces has increasingly roused widely interests of researchers in monitoring urban development and determining the overall environmental health of a watershed. However, studies on the impervious surface using multi-spectral imageries is insufficient and inaccurate due to the complexity of urban infrastructures base on the need to further recognize these impervious surface materials in a finer scale. Hyperspectral imageries have been proved to be sensitive to subtle spectral differences thus capable to exquisitely discriminate these similar materials while limited to the low spatial resolution. Coupled nonnegative matrix factorization (CNMF) unmixing method is one of the most physically straightforward and easily complemented hyperspectral pan-sharpening methods that could produce fused data with both high spectral and spatial resolution. This paper aimed to exploit the latent capacity and tentative validation of CNMF on the killer application of mapping urban impervious surfaces in complexed metropolitan environments like Hong Kong. Experiments showed that the fusion of high spectral and spatial resolution image could provide more accurate and comprehensive information on urban impervious surface estimation. |
Persistent Identifier | http://hdl.handle.net/10722/277673 |
ISSN | 2023 SCImago Journal Rankings: 0.282 |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, T. | - |
dc.contributor.author | Zhang, H. | - |
dc.contributor.author | Lin, H. | - |
dc.date.accessioned | 2019-09-27T08:29:40Z | - |
dc.date.available | 2019-09-27T08:29:40Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 2017, v. 42, n. 2W7, p. 919-923 | - |
dc.identifier.issn | 1682-1750 | - |
dc.identifier.uri | http://hdl.handle.net/10722/277673 | - |
dc.description.abstract | © Authors 2017. CC BY 4.0 License. Remote sensing techniques have great potential in providing accurate and timely information in urban areas. Estimation of impervious surfaces has increasingly roused widely interests of researchers in monitoring urban development and determining the overall environmental health of a watershed. However, studies on the impervious surface using multi-spectral imageries is insufficient and inaccurate due to the complexity of urban infrastructures base on the need to further recognize these impervious surface materials in a finer scale. Hyperspectral imageries have been proved to be sensitive to subtle spectral differences thus capable to exquisitely discriminate these similar materials while limited to the low spatial resolution. Coupled nonnegative matrix factorization (CNMF) unmixing method is one of the most physically straightforward and easily complemented hyperspectral pan-sharpening methods that could produce fused data with both high spectral and spatial resolution. This paper aimed to exploit the latent capacity and tentative validation of CNMF on the killer application of mapping urban impervious surfaces in complexed metropolitan environments like Hong Kong. Experiments showed that the fusion of high spectral and spatial resolution image could provide more accurate and comprehensive information on urban impervious surface estimation. | - |
dc.language | eng | - |
dc.relation.ispartof | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Data fusion | - |
dc.subject | Impervious surface | - |
dc.subject | Coupled nonnegative matrix factorization | - |
dc.title | Using coupled nonnegative matrix factorization (CNMF) un-mixing for high spectral and spatial resolution data fusion to estimate urban impervious surface and urban ecological environment | - |
dc.type | Conference_Paper | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.5194/isprs-archives-XLII-2-W7-919-2017 | - |
dc.identifier.scopus | eid_2-s2.0-85031023613 | - |
dc.identifier.volume | 42 | - |
dc.identifier.issue | 2W7 | - |
dc.identifier.spage | 919 | - |
dc.identifier.epage | 923 | - |
dc.identifier.issnl | 1682-1750 | - |