{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T02:02:08Z","timestamp":1772503328236,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2017,11,4]],"date-time":"2017-11-04T00:00:00Z","timestamp":1509753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1604105"],"award-info":[{"award-number":["1604105"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Measurements of solar radiation reflected from Earth\u2019s surface are the basis for calculating albedo, vegetation indices, and other terrestrial attributes. However, the \u201cbi-directional\u201d geometry of illumination and viewing (i.e., the Bi-directional Reflectance Distribution Function (BRDF)) impacts reflectance and all variables derived or estimated based on these data. The recently released MODIS BRDF\/Albedo Model Parameters (MCD43A1 Collection 6) dataset enables retrieval of directional reflectance at arbitrary solar and viewing angles, potentially increasing precision and comparability of data collected under different illumination and observation geometries. We quantified the ability of MCD43A1 Collection 6 for retrieving directional reflectance and compared the daily Collection 6 retrievals to those of MCD43A1 Collection 5, which are retrieved on an eight-day basis. Correcting MODIS-based estimates of surface reflectance from the illumination and viewing geometry of the Terra satellite (MOD09GA) to that of the MODIS Aqua (MYD09GA) overpass, as well as MCD43A4 Collection 6 and Landsat-5 TM images show that the BRDF correction of MCD43A1 Collection 6 results in greater consistency among datasets, with higher R2 (0.63\u20130.955), regression slopes closer to unity (0.718\u20130.955), lower root mean squared difference (RMSD) (0.422\u20133.142), and lower mean absolute error (MAE) (0.282\u20131.735) compared to the Collection 5 data. Smaller levels of noise (observed as high-frequency variability within the time series) in MCD43A1 Collection 6 in comparison to Collection 5 corroborates the improvement of BRDF parameters time series. These results corroborates that the daily MCD43A1 Collection 6 product represents the anisotropy of surface features and results in more precise directional reflectance derivation at any solar and viewing geometry than did the previous Collection 5.<\/jats:p>","DOI":"10.3390\/rs9111123","type":"journal-article","created":{"date-parts":[[2017,11,6]],"date-time":"2017-11-06T11:39:38Z","timestamp":1509968378000},"page":"1123","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Assessment of MODIS BRDF\/Albedo Model Parameters (MCD43A1 Collection 6) for Directional Reflectance Retrieval"],"prefix":"10.3390","volume":"9","author":[{"given":"Xianghong","family":"Che","sequence":"first","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Global Land Cover Facility, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Min","family":"Feng","sequence":"additional","affiliation":[{"name":"Global Land Cover Facility, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Joseph","family":"Sexton","sequence":"additional","affiliation":[{"name":"Global Land Cover Facility, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Saurabh","family":"Channan","sequence":"additional","affiliation":[{"name":"Global Land Cover Facility, Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Yaping","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7221-2246","authenticated-orcid":false,"given":"Qing","family":"Sun","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,11,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.rse.2003.12.006","article-title":"Bidirectional reflectance of earth targets: Evaluation of analytical models using a large set of spaceborne measurements with emphasis on the hot spot","volume":"90","author":"Maignan","year":"2004","journal-title":"Remote Sens. 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