{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:27:52Z","timestamp":1760243272569,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2014,7,8]],"date-time":"2014-07-08T00:00:00Z","timestamp":1404777600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper improves van Zyl\u2019s Nonnegative Eigenvalue Decomposition (NNED). Orientation angle compensation and helix scattering are introduced to the decomposition. The volume scattering parameters that explain the most cross-polarized power are selected. If volume scattering and helix scattering explain all cross-polarized power in the measured coherency matrix, then simply perform van Zyl decomposition to the remainder matrix; otherwise, the measured coherency matrix is decomposed into three components, i.e., helix scattering, volume scattering, and one ground scattering. The latter two scattering are all modeled by Neumann\u2019s adaptive depolarizing model, according to which some cross-polarized power is attributed to ground scattering hence the orientation angle randomness of volume scattering and the dominant ground scattering are obtained. In this way, all cross-polarized power could be well explained. Experiments using UAVSAR data showed that more than 99.8% of total pixels are well fitted. Negative power is avoided. Compared with van Zyl decomposition, volume scattering power is reduced by up to 8.73% on average. The given volume scattering power is often lower than that by three latest NNED.<\/jats:p>","DOI":"10.3390\/rs6076365","type":"journal-article","created":{"date-parts":[[2014,7,8]],"date-time":"2014-07-08T11:15:26Z","timestamp":1404818126000},"page":"6365-6385","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Improved van Zyl Polarimetric Decomposition Lessening the Overestimation of Volume Scattering Power"],"prefix":"10.3390","volume":"6","author":[{"given":"Xiaoguang","family":"Cheng","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan, Hubei 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9608-1690","authenticated-orcid":false,"given":"Wenli","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Jianya","family":"Gong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan, Hubei 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2014,7,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"716","DOI":"10.3390\/rs5020716","article-title":"Recent trend and advance of synthetic aperture radar with selected topics","volume":"5","author":"Ouchi","year":"2013","journal-title":"Remote Sens"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1117\/12.140618","article-title":"A three-component scattering model to describe polarimetric SAR data","volume":"1748","author":"Freeman","year":"1992","journal-title":"Proc. SPIE"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1109\/36.673687","article-title":"A three-component scattering model for polarimetric SAR data","volume":"36","author":"Freeman","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1699","DOI":"10.1109\/TGRS.2005.852084","article-title":"Four-component scattering model for polarimetric SAR image decomposition","volume":"43","author":"Yamaguchi","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2732","DOI":"10.1109\/TGRS.2010.2041242","article-title":"Three-component model-based decomposition for polarimetric SAR data","volume":"48","author":"An","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1104","DOI":"10.1109\/TGRS.2010.2076285","article-title":"Adaptive model-based decomposition of polarimetric SAR covariance matrices","volume":"49","author":"Arii","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3452","DOI":"10.1109\/TGRS.2010.2076285","article-title":"Model-based decomposition of polarimetric SAR covariance matrices constrained for nonnegative eigenvalues","volume":"49","author":"Arii","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.3390\/rs4061559","article-title":"Three-component power decomposition for polarimetric SAR data based on adaptive volume scatter modeling","volume":"4","author":"Cui","year":"2012","journal-title":"Remote Sens"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3014","DOI":"10.1109\/TGRS.2012.2212446","article-title":"General four-component scattering power decomposition with unitary transformation of coherency matrix","volume":"51","author":"Singh","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1109\/LGRS.2012.2193373","article-title":"Hybrid freeman\/eigenvalue decomposition method with extended volume scattering model","volume":"10","author":"Singh","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1843","DOI":"10.1109\/TGRS.2013.2255615","article-title":"General polarimetric model-based decomposition for coherency matrix","volume":"52","author":"Chen","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1991","DOI":"10.1109\/TGRS.2013.2257603","article-title":"On complete model-based decomposition of polarimetric SAR coherency matrix data","volume":"52","author":"Cui","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/TGRS.2013.2259177","article-title":"Comparison of nonnegative eigenvalue decompositions with and without reflection symmetry assumptions","volume":"52","author":"Wang","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2583","DOI":"10.1109\/TGRS.2007.897929","article-title":"Fitting a two-component scattering model to polarimetric SAR data from forests","volume":"45","author":"Freeman","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2474","DOI":"10.1109\/TGRS.2013.2262051","article-title":"Generalized polarimetric model-based decompositions using incoherent scattering models","volume":"52","author":"Ainsworth","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3838","DOI":"10.1109\/TGRS.2011.2138146","article-title":"Volume scattering modeling in POLSAR decompositions: Study of ALOS PALSAR data over boreal forest","volume":"49","author":"Antropov","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3101","DOI":"10.3390\/rs5063101","article-title":"Evaluation of digital classification of polarimetric SAR data for iron-mineralized laterites mapping in the amazon region","volume":"5","author":"Paradella","year":"2013","journal-title":"Remote Sens"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3652","DOI":"10.1109\/TGRS.2010.2048115","article-title":"Polarimetric SAR data in land cover mapping in boreal zone","volume":"48","author":"Rauste","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"4143","DOI":"10.1109\/TGRS.2009.2023908","article-title":"Support vector machine for multifrequency SAR polarimetric data classification","volume":"47","author":"Lardeux","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/TGRS.2003.819883","article-title":"Unsupervised terrain classification preserving polarimetric scattering characteristics","volume":"42","author":"Lee","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.rse.2011.11.001","article-title":"A novel algorithm for land use and land cover classification using RADARSAT-2 polarimetric SAR data","volume":"118","author":"Qi","year":"2012","journal-title":"Remote Sens. Environ"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1109\/TGRS.2005.859338","article-title":"Scattering-model-based speckle filtering of polarimetric SAR data","volume":"44","author":"Lee","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1109\/TGRS.2009.2024304","article-title":"Applying the freeman-durden decomposition concept to polarimetric SAR interferometry","volume":"48","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1667","DOI":"10.1109\/TGRS.2008.916326","article-title":"Polsar image analysis of wetlands using a modified four-component scattering power decomposition","volume":"46","author":"Yajima","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_25","unstructured":"Shi, J., Lee, J.-S., Chen, K., and Sun, Q. (2000, January 25\u201330). Evaluate usage of decomposition technique in estimation of soil moisture with vegetated surface by multi-temporal measurements. Honolulu, HI, USA."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1109\/TGRS.2008.2009642","article-title":"Potential of estimating soil moisture under vegetation cover by means of POLSAR","volume":"47","author":"Hajnsek","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_27","unstructured":"Jagdhuber, T., Sch\u00f6n, H., Hajnsek, I., and Papathanassiou, K.P. (2009, January 26\u201330). Soil moisture estimation under vegetation applying polarimetric decomposition techniques. Frascati, Italy. ESA: Frascati, Italy, 2009."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1109\/LGRS.2005.845033","article-title":"A novel algorithm for ship detection in SAR imagery based on the wavelet transform","volume":"2","author":"Tello","year":"2005","journal-title":"IEEE Geosci. Remote Sens. Lett"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Sato, R., Takahashi, Y., Yamaguchi, Y., and Yamada, H. (2012, January 22\u201327). stricken man-made object detection using scattering power decomposition with NNED and rotation of the covariance matrix. Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6352458"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2314","DOI":"10.3390\/rs4082314","article-title":"Polarimetric decomposition analysis of ALOS PALSAR observation data before and after a landslide event","volume":"4","author":"Yonezawa","year":"2012","journal-title":"Remote Sens"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3349","DOI":"10.1109\/TGRS.2010.2046331","article-title":"A general characterization for polarimetric scattering from vegetation canopies","volume":"48","author":"Arii","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_32","unstructured":"Neumann, M. Remote Sensing of Vegetation Using Multi-Baseline Polarimetric Sar Interferometry: Theoretical Modeling and Physical Parameter Retrieval. Ph.D. Thesis, Universit\u00e9 de Rennes 1, Rennes, France, 2009."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/TGRS.2010.2048333","article-title":"The effect of orientation angle compensation on coherency matrix and polarimetric target decompositions","volume":"49","author":"Lee","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1109\/LGRS.2012.2203577","article-title":"Deorientation effect investigation for model-based decomposition over oriented built-up areas","volume":"10","author":"Chen","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett"},{"key":"ref_35","unstructured":"Neumann, M., Ferro-Famil, L., and Pottier, E. A (2009, January 26\u201330). General model based polarimetric decomposition scheme for vegetated areas. Frascati, Italy."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1677","DOI":"10.1109\/LGRS.2014.2305655","article-title":"An unsupervised scattering mechanism classification method for polsar images","volume":"11","author":"Cheng","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1080\/2150704X.2013.858840","article-title":"A decomposition-free scattering mechanism classification method for PoLSAR images with Neumann\u2019s model","volume":"4","author":"Cheng","year":"2013","journal-title":"Remote Sens. Lett"},{"key":"ref_38","unstructured":"Cheng, X. Research of Model-Based Polarimetric Sar Decomposition Constrained for Nonnegative Eigenvalues. Ph.D. Thesis, Wuhan University, Wuhan, China, 2014."},{"key":"ref_39","unstructured":"Rosen, P.A., Hensley, S., Wheeler, K., Sadowy, G., Miller, T., Shaffer, S., Muellerschoen, R., Jones, C., Zebker, H., and Madsen, S. (2006, January 24\u201327). UAVSAR: A new NASA Airborne SAR system for science and technology research. Verona, NY, USA."},{"key":"ref_40","unstructured":"UAVSAR-Home. Available online: http:\/\/uavsar.jpl.nasa.gov\/instrument.html."},{"key":"ref_41","unstructured":"Vertex: ASF\u2019s Data Portal. Available online: https:\/\/vertex.daac.asf.alaska.edu."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1109\/TGRS.2008.2002881","article-title":"Improved sigma filter for speckle filtering of SAR imagery","volume":"47","author":"Lee","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1080\/10095020.2012.745050","article-title":"Terrain radiometric calibration of airborne UAVSAR for forested area","volume":"15","author":"Cheng","year":"2012","journal-title":"Geo-Spat. Inf. Sci"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/7\/6365\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:13:24Z","timestamp":1760217204000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/7\/6365"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,7,8]]},"references-count":43,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2014,7]]}},"alternative-id":["rs6076365"],"URL":"https:\/\/doi.org\/10.3390\/rs6076365","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2014,7,8]]}}}