{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T17:30:18Z","timestamp":1791048618559,"version":"4.1.0"},"reference-count":50,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T00:00:00Z","timestamp":1677110400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Major Projects on High-Resolution Earth Observation System under Grant 21-Y20B01-9001-19\/22","award":["U2244216"],"award-info":[{"award-number":["U2244216"]}]},{"name":"National Major Projects on High-Resolution Earth Observation System under Grant 21-Y20B01-9001-19\/22","award":["U2244216"],"award-info":[{"award-number":["U2244216"]}]},{"name":"National Major Projects on High-Resolution Earth Observation System under Grant 21-Y20B01-9001-19\/22","award":["41830648"],"award-info":[{"award-number":["41830648"]}]},{"name":"National Natural Science Foundation of China projects","award":["U2244216"],"award-info":[{"award-number":["U2244216"]}]},{"name":"National Natural Science Foundation of China projects","award":["U2244216"],"award-info":[{"award-number":["U2244216"]}]},{"name":"National Natural Science Foundation of China projects","award":["41830648"],"award-info":[{"award-number":["41830648"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent years, the retrieval and validation of remotely-sensed leaf area index (LAI) products over complex land surfaces have received much attention due to the high-precision land surface model simulations and applications in global climate change. However, most of these related researches mainly focus on coarse resolution products. This is because few products have been specifically designed for solving the problems derived from complex land surfaces in mountain areas until now. MuSyQ LAI is a new product derived from Gaofen-1 (GF-1) satellite data. This product is characterized with a temporal resolution of 10 days and a spatial resolution of 16 m. As is well known, high-resolution products have less uncertainties because of the homogeneities of sub-pixel. Therefore, to evaluate the precision and uncertainty of MuSyQ LAI, an up-scaling strategy was employed here to validate MuSyQ LAI for three mountain regions in Southwest China. The validation strategy can be divided into three parts. First, a regression model was built by in situ LAI measured by LAI-2200 and the normalized difference vegetation index (NDVI) from unmanned aerial vehicle (UAV) images to obtain a 0.5 m resolution LAI map. Second, an up-scaled LAI map with a spatial resolution consistent with MuSyQ LAI was calculated by the pixel-averaging method from the UAV-based LAI map. Third, the MuSyQ LAI was validated by the up-scaled UAV-based LAI in pixel scale. Simultaneously, the sources of uncertainty were analyzed and compared from the view of data source, retrieval model, and scale effects. The results suggested that MuSyQ LAI in the study areas are significantly underestimated by 53.69% due to the complex terrain and heterogeneous land cover. There are three main reasons for the underestimation. The differences between GF-1 reflectance and UAV-based reflectance employed to estimate LAI are the largest factors for the validation results, even accounting for 61.47% of the total bias. Subsequently, the scale effects led to about 28.44% bias. Last but not least, the models employed to retrieve LAI contributed merely 10.09% uncertainties to the total bias. In conclusion, the accuracy of MuSyQ LAI still has a large space to be improved from the view of reflectance over complex terrain. This study is quite important for applications of MuSyQ LAI products and also provides a reference for the improvement and application of other high-resolution remotely sensed LAI products.<\/jats:p>","DOI":"10.3390\/rs15051238","type":"journal-article","created":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T01:37:52Z","timestamp":1677202672000},"page":"1238","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Evaluation of the High-Resolution MuSyQ LAI Product over Heterogeneous Land Surfaces"],"prefix":"10.3390","volume":"15","author":[{"given":"Dandan","family":"Li","sequence":"first","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yajun","family":"Huang","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9071-7819","authenticated-orcid":false,"given":"Yao","family":"Xiao","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"He","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, China University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianguang","family":"Wen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8283-7116","authenticated-orcid":false,"given":"Yuanqing","family":"Li","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3783-8363","authenticated-orcid":false,"given":"Mingguo","family":"Ma","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/S0034-4257(01)00300-5","article-title":"Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements","volume":"80","author":"Chen","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/S0034-4257(97)00139-9","article-title":"Ecological Research Needs from Multiangle Remote Sensing Data","volume":"63","author":"Asner","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"D24117","DOI":"10.1029\/2007JD009370","article-title":"Analysis of leaf area index in the ECMWF land surface model and impact on latent heat and carbon fluxes: Application to West Africa","volume":"113","author":"Jarlan","year":"2008","journal-title":"J. Geophys. Res."},{"key":"ref_4","unstructured":"GCOS (2016). The Global Observing System for Climate: Implementation Needs (GCOS-200), World Meteorological Organization."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1829","DOI":"10.1109\/TGRS.2006.871214","article-title":"Analysis of leaf area index and fraction of PAR absorbed by vegetation products from the terra MODIS sensor: 2000-2005","volume":"44","author":"Yang","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"112985","DOI":"10.1016\/j.rse.2022.112985","article-title":"Development of the GLASS 250-m leaf area index product (version 6) from MODIS data using the bidirectional LSTM deep learning model","volume":"273","author":"Ma","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.rse.2007.02.018","article-title":"LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION\u2014Part 1: Principles of the algorithm","volume":"110","author":"Baret","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.rse.2006.06.020","article-title":"Analysis of the MISR LA\/FPAR product for spatial and temporal coverage, accuracy and consistency","volume":"107","author":"Hu","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"9753","DOI":"10.1002\/jgrd.50771","article-title":"Land and cryosphere products from Suomi NPP VIIRS: Overview and status","volume":"118","author":"Justice","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"109350","DOI":"10.1016\/j.agrformet.2023.109350","article-title":"Asymmetric response of primary productivity to precipitation anomalies in Southwest China","volume":"331","author":"Dong","year":"2023","journal-title":"Agric. For. Meteorol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1601","DOI":"10.1111\/gcb.12795","article-title":"Detection and attribution of vegetation greening trend in China over the last 30 years","volume":"21","author":"Piao","year":"2015","journal-title":"Glob. Change Biol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Chen, X., Chen, T.X., Yan, Q.Y., Cai, J.T., Guo, R.J., Gao, M.N., Wei, X.Q., Zhou, S.J., Li, C.F., and Xie, Y. (2021). The Ongoing Greening in Southwest China despite Severe Droughts and Drying Trends. Remote Sens., 13.","DOI":"10.3390\/rs13173374"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.rse.2015.04.027","article-title":"Retrieval of Leaf Area Index in mountain grasslands in the Alps from MODIS satellite imagery","volume":"165","author":"Pasolli","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3625","DOI":"10.1016\/j.rse.2011.08.023","article-title":"Evaluation of the MODIS LAI product using independent lidar-derived LAI: A case study in mixed conifer forest","volume":"115","author":"Jensen","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_15","first-page":"52","article-title":"Intercomparison and validation of MODIS and GLASS leaf area index (LAI) products over mountain areas: A case study in southwestern China","volume":"55","author":"Jin","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_16","first-page":"438","article-title":"Intercomparison Among GEOV1,GLASS and MODIS LAI Products over Mountainous Area in Southwestern China","volume":"31","author":"Yang","year":"2016","journal-title":"Remote Sens. Technol. Appl."},{"key":"ref_17","first-page":"400","article-title":"Intercomparison and evaluation of influencing factors among different LAl products over mountainous areas","volume":"34","author":"Jing","year":"2019","journal-title":"J. Nat. Resour."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/0034-4257(93)90072-6","article-title":"Importance of leaf area index and forest type when estimating photosynthesis in boreal forests","volume":"43","author":"Bonan","year":"1993","journal-title":"Remote Sens. Environ."},{"key":"ref_19","first-page":"5","article-title":"Technical characteristics of GF-1 satellite","volume":"8","author":"Bai","year":"2013","journal-title":"Aerosp. China"},{"key":"ref_20","unstructured":"Zhang, H., Li, J., Zhang, Z.X., Wu, S.L., Zhong, B., and Liu, Q.H. A dataset of 16m\/10-day leaf area indices of MuSyQ GF-series (2018\u20132020, China, Version 01). Sci. Data Bank, 2021."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"8958","DOI":"10.1109\/JSTARS.2022.3214224","article-title":"Revisit the Performance of MODIS and VIIRS Leaf Area Index Products from the Perspective of Time-Series Stability","volume":"15","author":"Zou","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.agrformet.2017.06.016","article-title":"Evaluation of four long time-series global leaf area index products","volume":"246","author":"Xiao","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.rse.2011.12.006","article-title":"Validation of MODIS and CYCLOPES LAI products using global field measurement data","volume":"119","author":"Fang","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_24","first-page":"76","article-title":"CEOS Global LAI Product Validation Good Practices","volume":"2","author":"Fernandes","year":"2014","journal-title":"Best Pract. Satell. Deriv. Land Prod. Valid."},{"key":"ref_25","first-page":"36","article-title":"DJI Genie 4 officially released the most intelligent drone is here","volume":"42","author":"Wu","year":"2016","journal-title":"Comput. Netw."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Di Gennaro, S.F., Toscano, P., Gatti, M., Poni, S., Berton, A., and Matese, A. (2022). Spectral Comparison of UAV-Based Hyper and Multispectral Cameras for Precision Viticulture. Remote Sens., 14.","DOI":"10.3390\/rs14030449"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/0034-4257(88)90021-1","article-title":"The semivariogram in remote sensing: An introduction","volume":"24","author":"Curran","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1109\/TGRS.2007.894019","article-title":"Use of semivariograms to identify earthquake damage in an urban area","volume":"45","author":"Sertel","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2476","DOI":"10.1016\/j.rse.2009.07.009","article-title":"The MODIS (Collection V005) BRDF\/albedo product: Assessment of spatial representativeness over forested landscapes","volume":"113","author":"Roman","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.rse.2007.04.017","article-title":"Multivariate quantification of landscape spatial heterogeneity using variogram models","volume":"112","author":"Garrigues","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.rse.2006.03.013","article-title":"Quantifying spatial heterogeneity at the landscape scale using variograrn models","volume":"103","author":"Garrigues","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"174","DOI":"10.2307\/1468250","article-title":"Quantifying spatial heterogeneity in streams","volume":"16","author":"Cooper","year":"1997","journal-title":"J. North Am. Benthol. Soc."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3267","DOI":"10.1109\/JSTARS.2016.2560878","article-title":"Evaluating Spatial Representativeness of Station Observations for Remotely Sensed Leaf Area Index Products","volume":"9","author":"Xu","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/j.rse.2006.07.013","article-title":"Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data","volume":"105","author":"Garrigues","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_35","first-page":"1158","article-title":"Simulation and correction of spatialscaling effects for leaf area index","volume":"18","author":"Liu","year":"2014","journal-title":"J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/S0034-4257(02)00074-3","article-title":"Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data","volume":"83","author":"Myneni","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0034-4257(01)00328-5","article-title":"Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors","volume":"81","author":"Trishchenko","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Zhong, B., Yang, A.X., Liu, Q.H., Wu, S.L., Shan, X.J., Mu, X.H., Hu, L.F., and Wu, J.J. (2021). Analysis Ready Data of the Chinese GaoFen Satellite Data. Remote Sens., 13.","DOI":"10.3390\/rs13091709"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Zhong, B., Wu, S.L., Yang, A.X., and Liu, Q.H. (2017). An Improved Aerosol Optical Depth Retrieval Algorithm for Moderate to High Spatial Resolution Optical Remotely Sensed Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9060555"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/S0034-4257(02)00102-5","article-title":"Radiative transfer based scaling of LAI retrievals from reflectance data of different resolutions","volume":"84","author":"Tian","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_41","first-page":"183","article-title":"Comparison and analysis of two universal scaling methods","volume":"13","author":"Wu","year":"2009","journal-title":"J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2022JD036779","article-title":"Characterizing the Effect of Spatial Heterogeneity and the Deployment of Sampled Plots on the Uncertainty of Ground \u201cTruth\u201d on a Coarse Grid Scale: Case Study for Near-Infrared (NIR) Surface Reflectance","volume":"127","author":"Wen","year":"2022","journal-title":"J. Geophys. Res.-Atmos."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1109\/JSTARS.2013.2280466","article-title":"Inter-comparison and validation of the FY-3A\/MERSI LAI product over mainland China","volume":"7","author":"Zhu","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/j.rse.2006.01.010","article-title":"Assessment of the MODIS LAI product for Australian ecosystems","volume":"101","author":"Hill","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1625","DOI":"10.5194\/essd-12-1625-2020","article-title":"Development of a global 30 m impervious surface map using multisource and multitemporal remote sensing datasets with the Google Earth Engine platform","volume":"12","author":"Zhang","year":"2020","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.isprsjprs.2011.10.008","article-title":"Combining the matter element model with the associated function of probability transformation for multi-source remote sensing data classification in mountainous regions","volume":"67","author":"Li","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"830","DOI":"10.3390\/rs5020830","article-title":"The Impact of Potential Land Cover Misclassification on MODIS Leaf Area Index (LAI) Estimation: A Statistical Perspective","volume":"5","author":"Fang","year":"2013","journal-title":"Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.agrformet.2003.08.001","article-title":"Review of methods for in situ leaf area index (LAI) determination: Part II. Estimation of LAI, errors and sampling","volume":"121","author":"Weiss","year":"2004","journal-title":"Agric. For. Meteorol."},{"key":"ref_49","first-page":"67","article-title":"A comparison of different methods for assessing leaf area index in four canopy types","volume":"65","author":"Roland","year":"2019","journal-title":"Cent. Eur. For. J."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41597-021-01024-4","article-title":"ValLAI_Crop, a validation dataset for coarse-resolution satellite LAI products over Chinese cropland","volume":"8","author":"Song","year":"2021","journal-title":"Sci. Data"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/5\/1238\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:40:47Z","timestamp":1760121647000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/5\/1238"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,23]]},"references-count":50,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["rs15051238"],"URL":"https:\/\/doi.org\/10.3390\/rs15051238","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,23]]}}}