PANGAEA_973635 A detailed snow POLDER bidirectional reflectance distribution function (BRDF) database in Arctic, version 2 Guo, Jing; Jiao, Ziti A detailed snow POLDER bidirectional reflectance distribution function (BRDF) database in Arctic, version 2 2024-11-22 PANGAEA Dataset https://doi.pangaea.de/10.1594/PANGAEA.973635 Earth Science geoscientificInformation Arctic multiangular database POLDER snow BRDF terrain effection vegetation and mountain complex Complete 90.0 90.0 0.0 0.0 unrestricted CC-BY-4.0: Creative Commons Attribution 4.0 International English PANGAEA Data Publisher for Earth & Environmental Science https://www.pangaea.de/ Data Center Contact Michael Diepenbroek info@pangaea.de

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Bremen Bremen 28359 Germany online 11.9 MBytes application/zip Bréon, François-Marie (2016): A BRDF-BPDF database for the analysis of Earth targets reflectances [dataset]. Laboratoire des Sciences du Climat et de l'Environnement, Saclay, PANGAEA, https://doi.org/10.1594/PANGAEA.864090 Bréon, François-Marie; Maignan, Fabienne (2016): A BRDF-BPDF database for the analysis of Earth targets reflectances. Earth System Science Data, 9, 31-45, https://doi.org/10.5194/essd-9-31-2017 Jiao, Ziti; Ding, Anxin; Kokhanovsky, Alexander A; Schaaf, Crystal B; Bréon, François-Marie; Dong, Yadong; Wang, Zhuosen; Liu, Yan; Zhang, Xiaoning; Yin, Siyang; Cui, Lei; Mei, Linlu; Chang, Yaxuan (2019): Development of a snow kernel to better model the anisotropic reflectance of pure snow in a kernel-driven BRDF model framework. Remote Sensing of Environment, 221, 198-209, https://doi.org/10.1016/j.rse.2018.11.001 A detailed snow POLDER BRDF database in Arctic: Format of the files (URI: https://download.pangaea.de/reference/126800/attachments/Format_of_the_files.pdf)

The POLDER multi-angle dataset stands as one of the most significant datasets in multi-angle quantitative remote sensing, with previous applications primarily focusing on non-snow-covered surfaces. This dataset provides a more detailed classification of POLDER snow Bidirectional Reflectance Distribution Function (BRDF) data located within the Arctic Circle in 2008 based on the previous database (Breon and Maignan, 2017). Initially, constraints were applied to the angular sampling distribution, retaining pixels only with observations present in both forward and backward scattering directions on the principal plane. Subsequently, the high-precision snow BRDF model RossThick-LiSparse Reciprocal Snow model (RTLSRS) (Jiao et.al, 2019) was employed to constrain the data uncertainty, removing pixels with RMSE greater than 0.04 in red band. After screening, a total of 153 pixels were retained, followed by further detailed classification, validation using corresponding MOD10A2 products, supplemented by ArcticDEM and vegetation distribution maps within the Arctic Circle. Ultimately, these datasets were categorized into snow (shady slope, sunny slope) and non-snow (vegetation-dominated, mountain complex-dominated) categories. Such datasets hold significant importance for future applications of multi-angle data on snow-covered surfaces and represent further analysis and optimization of existing snow databases. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.973635"!

https://doi.org/10.1016/j.rse.2018.11.001 Development of a snow kernel to better model the anisotropic reflectance of pure snow in a kernel-driven BRDF model framework https://doi.org/10.5194/essd-9-31-2017 A BRDF-BPDF database for the analysis of Earth targets reflectances https://doi.pangaea.de/10.1594/PANGAEA.864090 A BRDF-BPDF database for the analysis of Earth targets reflectances DIF 9.4 2024-11-22 2026-04-30