{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T13:56:13Z","timestamp":1772718973643,"version":"3.50.1"},"reference-count":74,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T00:00:00Z","timestamp":1697760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Guangdong Science and Technology plan project, the construction of Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology","award":["2022B1212040001"],"award-info":[{"award-number":["2022B1212040001"]}]},{"name":"Guangdong Science and Technology plan project, the construction of Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology","award":["2018YFA0606500"],"award-info":[{"award-number":["2018YFA0606500"]}]},{"DOI":"10.13039\/501100009950","name":"National Key R&amp;D Program of China Climate Change Impact and Adaptation in Major Countries along the Belt and Road","doi-asserted-by":"publisher","award":["2022B1212040001"],"award-info":[{"award-number":["2022B1212040001"]}],"id":[{"id":"10.13039\/501100009950","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009950","name":"National Key R&amp;D Program of China Climate Change Impact and Adaptation in Major Countries along the Belt and Road","doi-asserted-by":"publisher","award":["2018YFA0606500"],"award-info":[{"award-number":["2018YFA0606500"]}],"id":[{"id":"10.13039\/501100009950","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The moderate resolution imaging spectroradiometer (MODIS) calculates the leaf area index (LAI) for each pixel without incorporating the temporal correlation information, leading to a higher sensitivity for the LAI that produces uncertainties in observed reflectance. As a result, an increased noise level is observed in the timeseries, making the data discontinuous and inconsistent in space and time. Therefore, it is important to identify and handle the outliers during the post-processing of MODIS data. This study proposed a method to identify the MODIS LAI outliers based on the analyses of temporal patterns, including the interannual and seasonal changes in the LAI. The analysis was carried out utilizing the data from 278 global MODIS LAI sites and the results were verified against the measurement obtained from 52 ground stations. The results from the analyses detected 50 and 92 outliers based on 1.5\u03c3 and 1.0\u03c3 standard deviations, respectively, of the difference between the MODIS LAI and ground measurements; correspondingly, 46 and 65 outliers, respectively, were identified by incorporating temporal patterns during the post-processing of the data. The validation results exhibited improved values of the coefficient of determination (R2) after eliminating the MODIS LAI outliers identified through the interannual and seasonal patterns. Specifically, the R2 between the ground measurement LAI and MODIS LAI increased from 0.51 to 0.54, 0.88, and 0.90 after eliminating MODIS LAI outliers when considering the interannual patterns, seasonal patterns, and both the interannual and seasonal patterns, respectively. The results from the study provided valuable information and theoretical support to improve MODIS LAI post-processing.<\/jats:p>","DOI":"10.3390\/rs15205042","type":"journal-article","created":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T07:25:22Z","timestamp":1697786722000},"page":"5042","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Identifying Outliers of the MODIS Leaf Area Index Data by Including Temporal Patterns in Post-Processing"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4181-9536","authenticated-orcid":false,"given":"Baibing","family":"Ma","sequence":"first","affiliation":[{"name":"Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology, Jiangmen 529199, China"}]},{"given":"Ming","family":"Xu","sequence":"additional","affiliation":[{"name":"Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology, Jiangmen 529199, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1111\/j.1365-3040.1992.tb00992.x","article-title":"Defining leaf area index for non-flat leaves","volume":"15","author":"Chen","year":"1992","journal-title":"Plant Cell Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1111\/j.1600-0889.2007.00330.x","article-title":"Leaf area index is the principal scaling parameter for both gross photosynthesis and ecosystem respiration of Northern deciduous and coniferous forests","volume":"60","author":"Lindroth","year":"2008","journal-title":"Tellus B Chem. 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