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Article: Scattering-Mechanism-Based Investigation of Optimal Combinations of Polarimetric SAR Frequency Bands for Land Cover Classification
Title | Scattering-Mechanism-Based Investigation of Optimal Combinations of Polarimetric SAR Frequency Bands for Land Cover Classification |
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Authors | |
Keywords | Decision-tree algorithm Different frequency Frequency variation Land cover classification Object based image analysis |
Issue Date | 2019 |
Publisher | American Society for Photogrammetry and Remote Sensing. The Journal's web site is located at http://www.asprs.org/Photogrammetric-Engineering-and-Remote-Sensing/PE-RS-Journals.html |
Citation | Photogrammetric Engineering and Remote Sensing, 2019, v. 85 n. 11, p. 799-813 How to Cite? |
Abstract | Aiming at steering the selection of optimal combinations of polarimetric SAR (PolSAR) frequency bands for different land cover classification schemes, this study investigates the land cover classification capabilities of all the possible combinations of L-band ALOS PALSAR fully PolSAR data, C-band RADARSAT-2 fully PolSAR data, and X-band TerraSAR-X HH SAR data. A method that integrates polarimetric decomposition, object-based image analysis, decision tree algorithms, and support vector machines is used for the classification. Polarimetric decomposition theorems are used to interpret the scattering mechanisms at the different frequency bands to reveal the effect mechanisms of PolSAR frequency variation on the classification capability. This study finds that (1) X-band HH SAR is not necessary for classifying the land cover types involved in this study when C- or L-band fully PolSAR are used; (2) C-band fully PolSAR alone is adequate for classifying primitive land cover types, namely, water, bare land, vegetation, and built-up areas; and (3) L-band fully PolSAR alone is adequate for distinguishing between various vegetation types, such as crops, banana trees, and forests. |
Description | Link to Open access |
Persistent Identifier | http://hdl.handle.net/10722/288324 |
ISSN | 2021 Impact Factor: 1.469 2020 SCImago Journal Rankings: 0.483 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Qi, Z | - |
dc.contributor.author | Yeh, AGO | - |
dc.contributor.author | Li, X | - |
dc.date.accessioned | 2020-10-05T12:11:11Z | - |
dc.date.available | 2020-10-05T12:11:11Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Photogrammetric Engineering and Remote Sensing, 2019, v. 85 n. 11, p. 799-813 | - |
dc.identifier.issn | 0099-1112 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288324 | - |
dc.description | Link to Open access | - |
dc.description.abstract | Aiming at steering the selection of optimal combinations of polarimetric SAR (PolSAR) frequency bands for different land cover classification schemes, this study investigates the land cover classification capabilities of all the possible combinations of L-band ALOS PALSAR fully PolSAR data, C-band RADARSAT-2 fully PolSAR data, and X-band TerraSAR-X HH SAR data. A method that integrates polarimetric decomposition, object-based image analysis, decision tree algorithms, and support vector machines is used for the classification. Polarimetric decomposition theorems are used to interpret the scattering mechanisms at the different frequency bands to reveal the effect mechanisms of PolSAR frequency variation on the classification capability. This study finds that (1) X-band HH SAR is not necessary for classifying the land cover types involved in this study when C- or L-band fully PolSAR are used; (2) C-band fully PolSAR alone is adequate for classifying primitive land cover types, namely, water, bare land, vegetation, and built-up areas; and (3) L-band fully PolSAR alone is adequate for distinguishing between various vegetation types, such as crops, banana trees, and forests. | - |
dc.language | eng | - |
dc.publisher | American Society for Photogrammetry and Remote Sensing. The Journal's web site is located at http://www.asprs.org/Photogrammetric-Engineering-and-Remote-Sensing/PE-RS-Journals.html | - |
dc.relation.ispartof | Photogrammetric Engineering and Remote Sensing | - |
dc.subject | Decision-tree algorithm | - |
dc.subject | Different frequency | - |
dc.subject | Frequency variation | - |
dc.subject | Land cover classification | - |
dc.subject | Object based image analysis | - |
dc.title | Scattering-Mechanism-Based Investigation of Optimal Combinations of Polarimetric SAR Frequency Bands for Land Cover Classification | - |
dc.type | Article | - |
dc.identifier.email | Yeh, AGO: hdxugoy@hkucc.hku.hk | - |
dc.identifier.authority | Yeh, AGO=rp01033 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.14358/PERS.85.11.799 | - |
dc.identifier.scopus | eid_2-s2.0-85074835372 | - |
dc.identifier.hkuros | 314964 | - |
dc.identifier.volume | 85 | - |
dc.identifier.issue | 11 | - |
dc.identifier.spage | 799 | - |
dc.identifier.epage | 813 | - |
dc.identifier.isi | WOS:000492835200006 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0099-1112 | - |