{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:29:19Z","timestamp":1760243359294,"version":"build-2065373602"},"reference-count":53,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2014,9,26]],"date-time":"2014-09-26T00:00:00Z","timestamp":1411689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High-quality leaf area index (LAI) products retrieved from satellite observations are urgently needed for crop growth monitoring and yield estimation, land-surface process simulation and global change studies. In recent years, sequential assimilation methods have been increasingly used to retrieve LAI from time series remote-sensing data. However, the inherent characteristics of these sequential assimilation methods result in temporal discontinuities in the retrieved LAI profiles. In this study, a sequential assimilation method with incremental analysis update (IAU) was developed to jointly update model states and parameters and to retrieve temporally continuous LAI profiles from time series Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data. Based on the existing multi-year Global Land Surface Satellite (GLASS) LAI product, a dynamic model was constructed to evolve LAI anomalies over time. The sequential assimilation method with an IAU technique takes advantage of the Kalman filter (KF) technique to update model parameters, uses the ensemble Kalman filter (EnKF) technique to update LAI anomalies recursively from time series MODIS reflectance data and then calculates the temporally continuous LAI values by combining the LAI climatology data. The method was tested over eight Committee on Earth Observing Satellites-Benchmark Land Multisite Analysis and Intercomparison of Products (CEOS-BELMANIP) sites with different vegetation types. The results indicate that the sequential method with IAU can precisely reconstruct the seasonal variation patterns of LAI and that the LAI profiles derived from the sequential method with IAU are smooth and continuous.<\/jats:p>","DOI":"10.3390\/rs6109194","type":"journal-article","created":{"date-parts":[[2014,9,26]],"date-time":"2014-09-26T11:27:58Z","timestamp":1411730878000},"page":"9194-9212","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Sequential Method with Incremental Analysis Update to Retrieve Leaf Area Index from Time Series MODIS Reflectance Data"],"prefix":"10.3390","volume":"6","author":[{"given":"Jingyi","family":"Jiang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiqiang","family":"Xiao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4962-4888","authenticated-orcid":false,"given":"Jindi","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinling","family":"Song","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,9,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.agrformet.2003.08.027","article-title":"Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography","volume":"121","author":"Jonckheere","year":"2004","journal-title":"Agric. For. Meteorol"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.agrformet.2012.09.003","article-title":"Two separate periods of the LAI\u2013VIs relationships using in situ measurements in a deciduous broadleaf forest","volume":"169","author":"Potithep","year":"2013","journal-title":"Agric. For. Meteorol"},{"key":"ref_3","first-page":"1","article-title":"Estimating the leaf area index, height and biomass of maize using HJ-1 and RADARSAT-2","volume":"24","author":"Gao","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.rse.2004.11.017","article-title":"Use of coupled canopy structure dynamic and radiative transfer models to estimate biophysical canopy characteristics","volume":"95","author":"Koetz","year":"2005","journal-title":"Remote Sens. Environ"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1043","DOI":"10.1016\/j.rse.2010.12.009","article-title":"Estimating forest variables from top-of-atmosphere radiance satellite measurements using coupled radiative transfer models","volume":"115","author":"Laurent","year":"2011","journal-title":"Remote Sens. Environ"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.rse.2011.10.035","article-title":"Spatially constrained inversion of radiative transfer models for improved LAI mapping from future Sentinel-2 imagery","volume":"120","author":"Atzberger","year":"2012","journal-title":"Remote Sens. Environ"},{"key":"ref_7","unstructured":"Baret, F., Weiss, M., Troufleau, D., Prevot, L., Combal, B., and Bryson, R. (2000). Remote Sensing in Agriculture, Royal Agricultural College, Association of Applied Biologists."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Liang, S. (2004). Quantitative Remote Sensing of Land Surfaces, John Wiley & Sons. [1st ed.].","DOI":"10.1002\/047172372X"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1852","DOI":"10.1175\/1520-0493(2000)128<1852:AEKSFN>2.0.CO;2","article-title":"An ensemble Kalman smoother for nonlinear dynamics","volume":"128","author":"Evensen","year":"2000","journal-title":"Mon. Weather Rev"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1080\/01431161.2011.577826","article-title":"Variational retrieval of leaf area index from MODIS time series data: Examples from the Heihe river basin, north-west China","volume":"33","author":"Xiao","year":"2012","journal-title":"Int. J. Remote Sens"},{"key":"ref_11","unstructured":"European Centre for Medium-Range Weather Forecasts. Available online: http:\/\/old.ecmwf.int\/."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1337","DOI":"10.1016\/j.rse.2007.07.007","article-title":"Use of a Kalman filter for the retrieval of surface BRDF coefficients with a time-evolving model based on the ECOCLIMAP land cover classification","volume":"112","author":"Samain","year":"2008","journal-title":"Remote Sens. Environ"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.rse.2010.08.009","article-title":"Real-time retrieval of Leaf Area Index from MODIS time series data","volume":"115","author":"Xiao","year":"2011","journal-title":"Remote Sens. Environ"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4279","DOI":"10.1109\/TGRS.2012.2191154","article-title":"Impact of assimilating passive microwave observations on root-zone soil moisture under dynamic vegetation conditions","volume":"50","author":"Nagarajan","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1111\/j.1600-0870.2008.00376.x","article-title":"Inferred variables in data assimilation: Quantifying sensitivity to inaccurate error statistics","volume":"61","author":"Juckes","year":"2009","journal-title":"Tellus A"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2066","DOI":"10.1002\/qj.1939","article-title":"A hybrid nudging-ensemble Kalman filter approach to data assimilation in WRF\/DART","volume":"138","author":"Lei","year":"2012","journal-title":"Q. J. R. Meteorol. Soc"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1729","DOI":"10.1175\/JTECH1947.1","article-title":"Incremental analysis update implementation into a sequential ocean data assimilation system","volume":"23","author":"Brankart","year":"2006","journal-title":"J. Atmos. Ocean. Technol"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1256","DOI":"10.1175\/1520-0493(1996)124<1256:DAUIAU>2.0.CO;2","article-title":"Data assimilation using incremental analysis updates","volume":"124","author":"Bloom","year":"1996","journal-title":"Mon. Weather Rev"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1175\/1520-0485(2000)030<0294:ASODAA>2.0.CO;2","article-title":"A simple ocean data assimilation analysis of the global upper ocean 1950\u201395. Part I: Methodology","volume":"30","author":"Carton","year":"2000","journal-title":"J. Phys. Oceanogr"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1256\/qj.03.25","article-title":"Sensitivity of dynamical seasonal forecasts to ocean initial conditions","volume":"130","author":"Alves","year":"2004","journal-title":"Q. J. R. Meteorol. Soc"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2055","DOI":"10.1175\/2008JTECHO537.1","article-title":"Impact of the incremental analysis updates on a real-time system of the North Atlantic Ocean","volume":"25","author":"Benkiran","year":"2008","journal-title":"J. Atmos. Ocean. Technol"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3018","DOI":"10.1175\/2008MWR2433.1","article-title":"The ECMWF ocean analysis system: ORA-S3","volume":"136","author":"Balmaseda","year":"2008","journal-title":"Mon. Weather Rev"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2129","DOI":"10.1175\/1520-0493(2003)131<2129:TGRDAS>2.0.CO;2","article-title":"The GEOS-3 retrospective data assimilation system: The 6-hour lag case","volume":"131","author":"Zhu","year":"2003","journal-title":"Mon. Weather Rev"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2495","DOI":"10.1175\/1520-0493(2004)132<2495:OTRBIA>2.0.CO;2","article-title":"On the relationship between incremental analysis updating and incremental digital filtering","volume":"132","author":"Polavarapu","year":"2004","journal-title":"Mon. Weather Rev"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.advwatres.2013.07.011","article-title":"Dual states estimation of a subsurface flow-transport coupled model using ensemble Kalman filtering","volume":"60","author":"Gharamti","year":"2013","journal-title":"Adv. Water Resour"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.advwatres.2004.09.002","article-title":"Dual state\u2013parameter estimation of hydrological models using ensemble Kalman filter","volume":"28","author":"Moradkhani","year":"2005","journal-title":"Adv. Water Resour"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2005","DOI":"10.1016\/j.atmosenv.2009.01.014","article-title":"Online update of model state and parameters of a Monte Carlo atmospheric dispersion model by using ensemble Kalman filter","volume":"43","author":"Zheng","year":"2009","journal-title":"Atmos. Environ"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Hu, X.M., Zhang, F., and Nielsen-Gammon, J.W. (2010). Ensemble-based simultaneous state and parameter estimation for treatment of mesoscale model error: A real-data study. Geophys. Res. Lett, 37.","DOI":"10.1029\/2010GL043017"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/0168-1923(94)02216-7","article-title":"A Markov chain model of canopy reflectance","volume":"76","author":"Kuusk","year":"1995","journal-title":"Agric. For. Meteorol"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0022-4073(01)00007-3","article-title":"A two-layer canopy reflectance model","volume":"71","author":"Kuusk","year":"2001","journal-title":"J. Quant. Spectrosc. Radiat. Transf"},{"key":"ref_31","unstructured":"Spitters, C. (1989). VI Symposium on the Timing of Field Production of Vegetables 267, International Society for Horticultural Science."},{"key":"ref_32","unstructured":"Boogaard, H.L., van Diepen, C.A., Rutter, R.P., Cabrera, J.M.C.A., and Laar, H.H. (1998). User\u2019s Guide for the WOFOST 7.1 Crop Growth Simulation Model and WOFOST Control Center 1.5, DLO Winand Staring Centre."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/S1161-0301(02)00110-7","article-title":"An overview of the crop model STICS","volume":"18","author":"Brisson","year":"2003","journal-title":"Eur. J. Agron"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/S1161-0301(02)00107-7","article-title":"The DSSAT cropping system model","volume":"18","author":"Jones","year":"2003","journal-title":"Eur. J. Agron"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Williams, J., Jones, C., Kiniry, J., and Spanel, D.A. (1989). The EPIC crop growth model. Trans. ASAE, 32.","DOI":"10.13031\/2013.31032"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"394","DOI":"10.5194\/hess-9-394-2005","article-title":"Assessing the performance of eight real-time updating models and procedures for the Brosna River","volume":"9","author":"Goswami","year":"2005","journal-title":"Hydrol. Earth Syst. Sci"},{"key":"ref_37","unstructured":"Schl\u00f6gl, A. (2000). The Electroencephalogram and the Adaptive Autoregressive Model: Theory and Applications, Shaker Verlag GmbH."},{"key":"ref_38","unstructured":"Penny, W.D., and Roberts, S.J. (1998). Dynamic Linear Models, Recursive Least Squares and Steepest Descent Learning, Department of Electrical Engineering, Imperial College. Technical Report."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1109\/51.620497","article-title":"Continuous monitoring of the sympatho-vagal balance through spectral analysis","volume":"16","author":"Bianchi","year":"1997","journal-title":"IEEE Eng. Med. Biol. Mag"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1115\/1.3662552","article-title":"A new approach to linear filtering and prediction problems","volume":"82","author":"Kalman","year":"1960","journal-title":"J. Basic Eng"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1115\/1.3658902","article-title":"New results in linear filtering and prediction theory","volume":"83","author":"Kalman","year":"1961","journal-title":"J. Basic Eng"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1016\/0005-1098(69)90109-5","article-title":"Adaptive filtering","volume":"5","author":"Jazwinski","year":"1969","journal-title":"Automatica"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/0167-2789(94)90130-9","article-title":"Inverse methods and data assimilation in nonlinear ocean models","volume":"77","author":"Evensen","year":"1994","journal-title":"Phys. D Nonlinear Phenom"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/s10236-003-0036-9","article-title":"The ensemble Kalman filter: Theoretical formulation and practical implementation","volume":"53","author":"Evensen","year":"2003","journal-title":"Ocean Dyn"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1794","DOI":"10.1109\/TGRS.2006.876030","article-title":"Evaluation of the representativeness of networks of sites for the global validation and intercomparison of land biophysical products: Proposition of the CEOS-BELMANIP","volume":"44","author":"Baret","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.agrformet.2004.03.001","article-title":"An assessment of storage terms in the surface energy balance of maize and soybean","volume":"125","author":"Meyers","year":"2004","journal-title":"Agric. For. Meteorol"},{"key":"ref_47","unstructured":"Validation of Land European Remote sensing Instruments. Available online: http:\/\/w3.avignon.inra.fr\/valeri\/."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.rse.2012.04.014","article-title":"First evaluation of the simultaneous SMOS and ELBARA-II observations in the Mediterranean region","volume":"124","author":"Wigneron","year":"2012","journal-title":"Remote Sens. Environ"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/S0034-4257(99)00056-5","article-title":"Direct and indirect estimation of leaf area index, fAPAR, and net primary production of terrestrial ecosystems","volume":"70","author":"Gower","year":"1999","journal-title":"Remote Sens. Environ"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/0168-1923(86)90033-X","article-title":"Estimation of leaf area index from transmission of direct sunlight in discontinuous canopies","volume":"37","author":"Lang","year":"1986","journal-title":"Agric. For. Meteorol"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/TGRS.2013.2237780","article-title":"Use of general regression neural networks for generating the GLASS leaf area index product from time-series MODIS surface reflectance","volume":"52","author":"Xiao","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Garrigues, S., Lacaze, R., Baret, F., Morisette, J., Weiss, M., Nickeson, J., Fernandes, R., Plummer, S., Shabanov, N., and Myneni, R. (2008). Validation and intercomparison of global leaf area index products derived from remote sensing data. J. Geophys. Res, 113.","DOI":"10.1029\/2007JG000635"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.rse.2006.12.004","article-title":"Comparison and validation of MODIS and VEGETATION global LAI products over four BigFoot sites in North America","volume":"109","author":"Pisek","year":"2007","journal-title":"Remote Sens. Environ"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/10\/9194\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:16:20Z","timestamp":1760217380000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/10\/9194"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,9,26]]},"references-count":53,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2014,10]]}},"alternative-id":["rs6109194"],"URL":"https:\/\/doi.org\/10.3390\/rs6109194","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2014,9,26]]}}}