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The impacts of spatial baseline on forest canopy height model and digital terrain model retrieval using P-band PolInSAR data

dc.contributor.authorLiao, Zhanmangen
dc.contributor.authorHe, Binbinen
dc.contributor.authorvan Dijk, Albert I.J.M.en
dc.contributor.authorBai, Xiaojingen
dc.contributor.authorQuan, Xingwenen
dc.date.accessioned2025-03-17T02:18:28Z
dc.date.available2025-03-17T02:18:28Z
dc.date.issued2018-06-01en
dc.description.abstractPolarimetric Synthetic Aperture Radar Interferometry (PolInSAR) has shown potential for the retrieval of a forest canopy height model (CHM) and the underlying solid earth digital terrain model (DTM). However, because of non-volume decorrelation and other unavoidable errors, the robustness of retrieval heights is sensitive to the spatial baseline of the selected InSAR pairs, which relates forest parameters to measured coherence. Within the context of the random volume over ground (RVoG) model and the three-stage inversion method, we aimed to quantify the influence of spatial baseline on the inversions at P-band, which are distinct from the inversions at higher frequency due to the non-negligible ground contributions. This information assists in optimal baseline selection and the development of robust inversion schemes. Assumptions about the extinction coefficient and additional DTM or DEM were used to reduce the influence of ground contribution on CHM and DTM inversion, respectively. Inversions from published airborne repeat-pass P-band PolInSAR data with four different spatial baselines were validated against LiDAR-derived DTM and CHM data. The results show that a longer spatial baseline performed better in DTM inversion. The longest baseline produced the best R2 of 0.995 and RMSE of 0.555 m, much better than the smallest baseline with an R2 of 0.794 and RMSE of 3.74 m. A threshold height could be identified that determines the overestimation and underestimation of CHM inversion due to the non-volume decorrelation. Different baselines produced different threshold heights, making CHM inversion only accurate for a limited range of forest height around the threshold. The optimal baseline produced a CHM with R2 of 0.605 and RMSE of 2.67 m. Additionally, we found that using multiple baselines has the potential to improve CHM inversion, improving the R2 to 0.827 and RMSE to 0.876 m in our study.en
dc.description.sponsorshipThe authors would like to thank the ONERA, ESA, and TropiSAR team for providing the TropiSAR datasets of excellent quality, and the European Regional Development Fund (ERDF contract no. 2907 dated 04/11/08) for providing accurate LiDAR-derived data. This work was supported by the National Natural Science Foundation of China (Contract No. 41471293 & No. 41671361 ) and the Fundamental Research Fund for the Central Universities (Contract No. ZYGX2012Z005 ).en
dc.description.statustrueen
dc.format.extent19en
dc.identifier.otherresearchoutputwizard:u4485658xPUB1988en
dc.identifier.otherScopus:85044634454en
dc.identifier.otherWOS:WOS:000431164300029en
dc.identifier.urihttps://dspace-test.anu.edu.au/handle/1885/733719897
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85044634454&partnerID=8YFLogxKen
dc.language.isoEnglishen
dc.rightsPublisher Copyright: © 2018 Elsevier Inc.en
dc.sourceRemote Sensing of Environmenten
dc.subjectCHMen
dc.subjectDTMen
dc.subjectP-banden
dc.subjectPolInSARen
dc.subjectSpatial baselineen
dc.titleThe impacts of spatial baseline on forest canopy height model and digital terrain model retrieval using P-band PolInSAR dataen
dc.typeArticleen
local.bibliographicCitation.lastpage421en
local.bibliographicCitation.startpage403en
local.contributor.affiliationLiao, Zhanmang; University of Electronic Science and Technology of Chinaen
local.contributor.affiliationHe, Binbin; University of Electronic Science and Technology of Chinaen
local.contributor.affiliationvan Dijk, Albert I.J.M.; Fenner School of Environment & Society Special Projects, Fenner School of Environment & Society, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationBai, Xiaojing; Nanjing University of Information Science & Technologyen
local.contributor.affiliationQuan, Xingwen; University of Electronic Science and Technology of Chinaen
local.identifier.citationvolume210en
local.identifier.doi10.1016/j.rse.2018.03.033en
local.identifier.puree024a9ce-a415-46e3-a9ea-944ee7eb88c1en
local.type.statusPublisheden

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