{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T17:30:29Z","timestamp":1773855029595,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,4,5]],"date-time":"2021-04-05T00:00:00Z","timestamp":1617580800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Nature Science Foundation of China program","award":["41901353"],"award-info":[{"award-number":["41901353"]}]},{"name":"Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan)","award":["162301202679"],"award-info":[{"award-number":["162301202679"]}]},{"DOI":"10.13039\/501100007925","name":"Huazhong Agricultural University","doi-asserted-by":"publisher","award":["2662019QD054"],"award-info":[{"award-number":["2662019QD054"]}],"id":[{"id":"10.13039\/501100007925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFC1502406-03"],"award-info":[{"award-number":["2017YFC1502406-03"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Research Fund of Guangxi Key Laboratory of Water Engineering Materials and Structures, Guangxi Institute of water resources research","award":["GXHRI-WEMS-2019-03"],"award-info":[{"award-number":["GXHRI-WEMS-2019-03"]}]},{"name":"National Key Research and Development Program of Guangxi","award":["2019AB20009"],"award-info":[{"award-number":["2019AB20009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Vegetation indices (VIs) data derived from satellite imageries play a vital role in land surface vegetation and dynamic monitoring. Due to the excessive noises (e.g., cloud cover, atmospheric contamination) in daily VI data, temporal compositing methods are commonly used to produce composite data to minimize the negative influence of noise over a given compositing time interval. However, VI time series with high temporal resolution were preferred by many applications such as vegetation phenology and land change detections. This study presents a novel strategy named DAVIR-MUTCOP (DAily Vegetation Index Reconstruction based on MUlti-Temporal COmposite Products) method for normalized difference vegetation index (NDVI) time-series reconstruction with high temporal resolution. The core of the DAVIR-MUTCOP method is a combination of the advantages of both original daily and temporally composite products, and selecting more daily observations with high quality through the temporal variation of temporally corrected composite data. The DAVIR-MUTCOP method was applied to reconstruct high-quality NDVI time-series using MODIS multi-temporal products in two study areas in the continental United States (CONUS), i.e., three field experimental sites near Mead, Nebraska from 2001 to 2012 and forty-six AmeriFlux sites evenly distributed across CONUS from 2006 to 2010. In these two study areas, the DAVIR-MUTCOP method was also compared to several commonly used methods, i.e., the Harmonic Analysis of Time-Series (HANTS) method using original daily observations, Savitzky\u2013Golay (SG) filtering using daily observations with cloud mask products as auxiliary data, and SG filtering using temporally corrected composite data. The results showed that the DAVIR-MUTCOP method significantly improved the temporal resolution of the reconstructed NDVI time series. It performed the best in reconstructing NDVI time-series across time and space (coefficient of determination (R2 = 0.93 ~ 0.94) between reconstructed NDVI and ground-observed LAI). DAVIR-MUTCOP method presented the highest robustness and accuracy with the change of the filtering parameter (R2 = 0.99 ~ 1.00, bias = 0.001, root mean square error (RMSE) = 0.020). Only MODIS data were used in this study; nevertheless, the DAVIR-MUTCOP method proposed a universal and potential way to reconstruct daily time series of other VIs or from other operational sensors, e.g., AVHRR and VIIRS.<\/jats:p>","DOI":"10.3390\/rs13071397","type":"journal-article","created":{"date-parts":[[2021,4,5]],"date-time":"2021-04-05T11:48:29Z","timestamp":1617623309000},"page":"1397","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["A Novel Strategy to Reconstruct NDVI Time-Series with High Temporal Resolution from MODIS Multi-Temporal Composite Products"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6659-2702","authenticated-orcid":false,"given":"Linglin","family":"Zeng","sequence":"first","affiliation":[{"name":"College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4767-581X","authenticated-orcid":false,"given":"Brian D.","family":"Wardlow","sequence":"additional","affiliation":[{"name":"Center for Advanced Land Management Information Technologies, University of Nebraska-Lincoln, 3310 Holdrege St, Lincoln, NE 68583, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5638-6438","authenticated-orcid":false,"given":"Shun","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Environmental Studies &amp; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1017-742X","authenticated-orcid":false,"given":"Xiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"given":"Guoqing","family":"Zhou","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China"}]},{"given":"Guozhang","family":"Peng","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China"}]},{"given":"Daxiang","family":"Xiang","sequence":"additional","affiliation":[{"name":"Changjiang River Scientific Research Institute, Changjiang River Water Resources Commission, Wuhan 430010, China"}]},{"given":"Rui","family":"Wang","sequence":"additional","affiliation":[{"name":"Changjiang Institute of Survey, Planning, Design and Research, Wuhan 430010, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4756-9934","authenticated-orcid":false,"given":"Ran","family":"Meng","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China"}]},{"given":"Weixiong","family":"Wu","sequence":"additional","affiliation":[{"name":"Guanxi Key Laboratory of Water Engineering Materials and Structures, Guanxi Institute of Water Resources Research, Nanning 530023, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2016.12.018","article-title":"Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?","volume":"191","author":"Zhang","year":"2017","journal-title":"Remote Sens. 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