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Location: home > People/Professors

Name: FANG Hongliang Ph.D. (University of Maryland, College Park)
Current Appointment: Professor (2009), CEOS/WGCV/LPV LAI focus area lead, Remote Sensing of Environment Editorial Board, IEEE Geoscience and Remote Sensing Letters Associate editor, Acta Geographica Sinica Editor.

Ph.D  Geography (Land surface remote sensing), 2003. University of Maryland, College Park, MD.  Dissertation: “Improving the Estimation of Leaf Area Index from Remotely Sensed Data” 
Ph.D Cartography and Geographic Information System (GIS), 1999. Institute of Geography, Chinese Academy of Sciences (CAS), Beijing, China.
M.S. Geography (Land use and land cover change), 1996.  Institute of Geography, Chinese Academy of Sciences (CAS), Beijing, China. Thesis: “Estimation of Rice Planting Area Using Remote Sensing Technique - take Jiangling County, Hubei Province as an example”
B.S. Geography, 1993.  East China Normal University, Shanghai, China.

Areas of Specialization:
*  Retrieval of land surface parameters from remotely sensed data
*  Assimilation of remotely sensed data and crop growth model for crop yield estimation
*  Regional land use/cover change and hydrological processes

Representative Publications:

Li, W., Fang, H., Wei, S., Weiss, M., and Baret F., 2021. Critical analysis of methods to estimate the fraction of absorbed or intercepted photosynthetically active radiation from ground measurements: Application to rice crops. Agricultural and Forest Meteorology, 297, 108273. https://doi.org/10.1016/j.agrformet.2020.108273.

Chen, B., Arain, M. A., Chen, J. M., Wang, S., Fang, H., Liu, Z., Mo, G., and J., Liu, 2020.  Importance of shaded leaf contribution to the total GPP of Canadian terrestrial ecosystems: evaluation of MODIS GPP. Journal of Geophysical Research: Biogeosciences, 125(10), https://doi.org/10.1029/2020JG005917.

Wang, Y., and H. Fang, 2020. Estimation of LAI with the LiDAR Technology: A Review. Remote Sensing, 12(20), 3457. https://doi.org/10.3390/rs12203457 .

Fang, H., 2020. Development and validation of satellite leaf area index (LAI) products in China (in Chinese). Remote Sensing Technology and Application, 35(5), 990-1003.

Wang Y., Fang H., Zhang Y., and Li S., 2020. Retrieval of Forest LAI Using Airborne LVIS and Spaceborne GLAS Waveform LiDAR Data (in Chinese). Remote Sensing Technology and Application, 35(5), 1004-1014. 

Zhang Y., Fang, H., Ma, L., Ye, Y., and Wang Y., 2020. Estimation of forest leaf area index and clumping index from the Global Positioning System (GPS) satellite carrier-to-noise-density ratio (C/N0).Remote Sensing Letters, 11(2): 146-155.  https://doi.org/10.1080/2150704X.2019.1692386 .

Fang, H., Baret, F., Plummer, S., and Schaepman-Strub, G. (2019). An overview of global leaf area index (LAI): Methods, products, validation, and applications. Reviews of Geophysics, https://doi.org/10.1029/2018RG000608

Fang, H., Zhang Y., Wei S., Li W., Ye Y., Sun T., and W. Liu, 2019. Validation of global moderate resolution leaf area index (LAI) products over croplands in northeastern China. Remote Sensing of Environmenthttps://doi.org/10.1016/j.rse.2019.111377  

Jiang, C., and H. Fang, 2019. GSV: a general model for hyperspectral soil reflectance simulation. International Journal of Applied Earth Observation and Geoinformation, 83, 101932, https://doi.org/10.1016/j.jag.2019.101932 .

Wei, S., Fang, H., Schaaf, C. B., He, L., and J. M. Chen, 2019. Global 500 m clumping index product derived from MODIS BRDF data (2001-2017). Remote Sensing of Environment. 232, 111296. https://doi.org/10.1016/j.rse.2019.111296

Fang, H., Liu, W., Li, W., and Wei, S., 2018. Estimation of the directional and whole apparent clumping index (ACI) from indirect optical measurements. ISPRS Journal of Photogrammetry and Remote Sensing, 144, 1-13. doi:10.1016/j.isprsjprs.2018.06.022.

Fang, H., Ye Y., Liu, W., Wei, S., and Ma, L., 2018. Continuous estimation of canopy leaf area index (LAI) and clumping index over broadleaf crop fields: An investigation of the PASTIS-57 instrument and smartphone applications. Agricultural and Forest Meteorology, 253-254, 48-61. doi: 10.1016/j.agrformet.2018.02.003.

Sun, T., Fang, H., Liu, W., and Ye, Y., 2017. Impact of water background on canopy reflectance anisotropy of a paddy rice field from multi-angle measurements. Agricultural and Forest Meteorology233, 143-152. doi:10.1016/j.agrformet.2016.11.010. 

Wei, S., and H. Fang, 2016. Estimation of canopy clumping index from MISR and MODIS sensors using the normalized difference hotspot and darkspot (NDHD) method: The influence of BRDF models and solar zenith angle. Remote Sensing of Environment187: 476-491. doi: 10.1016/j.rse.2016.10.039. 

Li, W., and H. Fang, 2015. Estimation of direct, diffuse, and total FPARs from Landsat surface reflectance data and ground-based estimates over six FLUXNET sites. Journal of Geophysical Research – Biogeosciences120: 96-112,doi:10.1002/2014JG002754. 

Pisek, J., Govind, A., Arndt, S.K., Hocking, D., Wardlaw, T.J., Fang, H., Matteucci, G., & Longdoz, B., 2015. Intercomparison of clumping index estimates from POLDER, MODIS, and MISR satellite data over reference sites. ISPRS Journal of Photogrammetry and Remote Sensing101: 47-56, doi: 10.1016/j.isprsjprs.2014.11.004. 

Fang, H., Li, W., Wei, S., and C. Jiang, 2014. Seasonal variation of leaf area index (LAI) over paddy rice fields in NE China: Intercomparison of destructive sampling, LAI-2200, digital hemispherical photography (DHP), and AccuPAR methods.Agricultural and Forest Meteorology198-199(0): 126-141, doi: 10.1016/j.agrformet.2014.08.005. 

Liu, Q., S. Liang, Z. Xiao, and H. Fang, 2014. Retrieval of leaf area index using temporal, spectral, and angular information from multiple satellite data. Remote Sensing of Environment145: 25-37. 

Fang, H., Jiang, C., Li, W., Wei, S., Baret, F., Chen, J.M., Garcia-Haro, J., Liang, S., Liu, R., Myneni, R.B., Pinty, B., Xiao, Z., & Zhu, Z., 2013. Characterization and intercomparison of global moderate resolution leaf area index (LAI) products: Analysis of climatologies and theoretical uncertainties. Journal of Geophysical Research – Biogeosciences118(2): 529-548, doi: 10.1002/jgrg.20051.  

Fang, H., W. Li, and R.B. Myneni, 2013. The impact of potential land cover misclassification on MODIS leaf area index (LAI)estimation: A statistical perspective. Remote Sensing5(2):830-844. 

Fang, H., S. Wei, C. Jiang, and K. Scipal, 2012. Theoretical uncertainty analysis of global MODIS, CYCLOPES and GLOBCARBON LAI products using a triple collocation method. Remote Sensing of Environment124, 610-621. 

Peng D., B. Zhang , L. Liu , H. Fang , D. Chen , Y. Hu , and L. Liu, 2012. Characteristics and drivers of global NDVI-based FPAR from 1982 to 2006. Global Biogeochemical Cycles26, GB3015, doi:10.1029/2011GB004060.   

Zhao T., D. G. Brown, H. Fang, D. M. Theobald, T. Liu, and T. Zhang, 2012. Vegetation productivity consequences of human settlement growth in the eastern United States. Landscape Ecology27(2): 1149-1165. doi:10.1007/s10980-012-9766-8. 

Fang, H., S. Wei, and S. Liang, 2012. Validation of MODIS and CYCLOPES LAI products using global field measurement data. Remote Sensing of Environment119, 43-54.  

Jiang, C., H. Fang, and S. Wei, 2012. Review of land surface roughness parameterization study (in Chinese). Advances in Earth Science27(3): 292-303.  

Yang, F., J. Sun, H. Fang, Z. Yao, J. Zhang, Y. Zhua, K. Song, Z. Wang, M. Hua, 2012. Comparison of Different Methods for Corn LAI Estimation over Northeastern China. International Journal of Applied Earth Observation and Geoinformation. 18, 462-471. 

Peng, D., B. Zhang , L. Liu , D. Chen , H. Fang , and Y. Hu, 2012. Seasonal dynamic pattern analysis on global FPAR derived from AVHRR GIMMS NDVI. International Journal of Digital Earth5(5): 439-455.doi:10.1080/17538947.2011.596579. 

Fang, H., S. Liang, G. Hoogenboom, 2011. Integration of MODIS LAI and vegetation index products with the CSM-CERES-Maize model for corn yield estimation. International Journal of Remote Sensing, 32(4): 1039-1065. 

Fang, H., S. Liang, G. Hoogenboom, J. Teasdale, and M. Cavigelli, 2008. Corn yield estimation through assimilation of remotely sensed data into the CSM-CERES-Maize model. International Journal of Remote Sensing29(10): 3011-3032. 

Fang, H., S. Liang, J. R. Townshend, and R. E. Dickinson, 2008. Spatially and temporally continuous LAI data sets based on an integrated filtering method: Examples from North America. Remote Sensing of Environment112(1): 75-93. 

Sun, W., S. Liang, G. Xu, H. Fang, and R. Dickinson, (2007), Mapping Plant Functional Types from MODIS Data UsingMultisource Evidential Reasoning, Remote Sensing of Environment, 112(3): 1010-1024. 

Fang, H., S. Liang, H.-Y. Kim, J. R. Townshend, C. L. Schaaf, A. H. Strahler, and R. E. Dickinson, 2007. Developing a spatially continuous 1 km surface albedo data set over North America from Terra MODIS products. Journal of Geophysical Research – Atmospheres, 112, D20206, doi: 10.1029/2006JD008377. 

Liang, S., B. Zhong and H. Fang, 2006. Improved estimation of aerosol optical depth from MODIS imagery over land surfaces.Remote Sensing of Environment, 104(4): 409-415. 

Liang S., T. Zheng, R. Liu, H. Fang, S.C. Tsay, and S. Running, 2006. Estimation of incident photosynthetically active radiation from Moderate Resolution Imaging Spectrometer data. Journal of Geophysical Research - Atmosphere111, D15208, doi:10.1029/2005JD006730. 

Fang, H., S. Liang, M. P. McClaran, W. van Leeuwen, S. Drake, S. E. Marsh, A. Thomson, R. C. Izaurralde, and N. J. Rosenberg, 2005. Biophysical Characteristics and management effects on semiarid rangeland observed from Landsat ETM+ data. IEEE Transactions on Geosciences and Remote Sensing43(1): 125-134. 

Fang, H. and S. Liang, 2005. A hybrid inversion method for mapping leaf area index from MODIS data: experiments and application to broadleaf and needleleaf canopies. Remote Sensing of Environment94(3): 405-424. 

Fang, H., G. Liu, and M. Kearney, 2005. Geo-relational analysis of soil type, soil salt content, landform, and land use in the Yellow River Delta, China. Environmental Management35(1): 1-13. 

Walthall, C. L., W. P.Dulaney, M. C. Anderson, J. M. Norman, H. Fang and S. Liang, 2004. A comparison of empirical and neural network approaches for estimating corn and soybean leaf area index from Landsat ETM+ imagery. Remote Sensing of Environment92(4): 465-474. 

Fang, H., S. Liang, M. Chen, C. Walthall, and C. Daughtry, 2004. Statistical comparison of MISR, ETM+ and MODIS land surface reflectance and albedo products of the BARC Land Validation Core Site, USA. International Journal of Remote Sensing25(2): 409-422. 

Liang, S., H. Fang, 2004. An improved atmospheric correction algorithm for hyperspectral remotely sensed imagery. IEEE Geosciences and Remote Sensing Letters1(2): 112-117. 

Fang, H. and S. Liang, 2003. Retrieving leaf area index with a neural network method: Simulation and validation. IEEE Transactions on Geosciences and Remote Sensing, 41(9): 2052-2062. 

Fang, H., S. Liang and A. Kuusk, 2003. Retrieving leaf area index using a genetic algorithm with a canopy radiative transfer model. Remote Sensing of Environment, 85(3): 257-270. 

Liang, S. , H. Fang, L. Thorp, M. Kaul, T.G. Van Niel, T. R. McVicar, J. Pearlman, C. Walthall, C. Daughtry, F. Huemmrich, and D. L. B. Jupp, 2003. Estimation and validation of land surface broadband albedos and leaf area index from EO-1 ALI data. IEEE Transactions on Geosciences and Remote Sensing, 41(6): 1260-1267. 

Van Niel, T. G., T. R. McVicar, H. Fang, and S. Liang, 2003. Environmental moisture mapping for per-field discrimination of rice. International Journal of Remote Sensing, 24(4): 885-890. 

Liang, S., H. Fang, M. Chen, C. Walthall, C. Daughtry, J. Morisette, C. Schaff, and A. Strahler, 2002. Validating MODIS land surface reflectance and albedo products: Methods and preliminary results. Remote Sensing of Environment83(1-2): 149-162. 

Liang, S., C. Shuey, A. Russ, H. Fang, M. Chen, C. Walthall, and C. Daughtry, 2002. Narrowband to Broadband Conversions of Land Surface Albedo: II. Validation. Remote Sensing of Environment, 84(1): 25-41. 

Liang, S., H. Fang, J. Morisette, M. Chen, C. Walthall, C. Daughtry, and C. Shuey, 2002. Atmospheric Correction of Landsat ETM+ Land Surface Imagery: II. Validation and Applications. IEEE Transactions on Geosciences and Remote Sensing,40(12): 2736-2746. 

Liang, S., H. Fang, M. Chen, 2001. Atmospheric Correction of Landsat ETM+ Land Surface Imagery: I. Methods. IEEE Transactions on Geosciences and Remote Sensing, 39(11): 2490-2498. 

Fang H. and J. Xu, 2000. Land Cover and Vegetation Change in the Yellow River Delta Nature Reserve Analyzed with Landsat Thematic Mapper Data. Geocarto International, 15(4): 41-47. 

Fang H., 1999. The Distribution of Physicians and Hospital Beds in Kansas. Papers and Proceedings of the Applied Geography Conferences. F. Schoolmaster (ed.). pp. 360-365. Charlotte, North Carolina. October 13-16, 1999. 

Xu J., H. Fang, S. Fu, X. Huang, 1999. SPOT Image used in River Water Suspended Sediment and Its Environmental Background Analysis. The Journal of Chinese Geography9(4): 402-409. 

Xu J., H. Fang, S. Fu, X. Huang, 1999. Estimating Suspended Sediment Concentrations from SPOT Image: A Case Study inDanshuihe, Taiwan (in Chinese). Remote Sensing Technology and Application14(4): 17-22. 

Fang H., 1998. Rice Crop Area Estimation of an Administrative Division in China Using Remote Sensing. International Journal of Remote Sensing19(17): 3411-3419. 

Zhang J., D. Guo, H. Fang, 1998. Geospatial Data Ming and Knowledge Discovery using Decision Tree Algorithm-A Case Study of Soil Data Set of Yellow River Delta (YRD) (in Chinese). Geographical Research17,Supplement, 43-49. 

Fang H., B. Wu, H. Liu and X. Huang, 1998. Using NOAA AVHRR and Landsat TM Data to Estimate Rice Planting Area Year-by-Year. International Journal of Remote Sensing. 19(3):521-525. 

Fang H., J. Li, F. Huang, 1998. Integrated Database Development in Large Scale Remote Sensing Application Project (in Chinese). Remote Sensing Information. 1998-4, pp.10-13. 

Liu W., J. Gong and H. Fang, 1998. Knowledge Extraction from GIS Database and its Application in Vegetation Classification (in Chinese). The Journal of Remote Sensing, 2(3):1-7. 

Fang H., and G. Liu, 1998. YRDGIS and the Yellow River Delta. GIS Asia/PacificApril/May, 26-30. 

Fang H., 1998. An Discussion On Two Strategies Applied to Estimate Rice planting Area of an Administrative Division Using Remote Sensing Technique (in Chinese). ACTA Geographical Sinica. 63(1):58-65. 

Fang H., X. Yang, and Y. Du, 1998. Research on Integrating ADEOS-AVNIR XS and PAN DataUsing Primary Component Transformation – Antitransformation (in Chinese). Remote Sensing Technology And Application13(3): 48-53 

Fang H., and Q. Tian, 1998. A Review of Hyperspectral Remote Sensing in Vegetation Monitoring (in Chinese). Remote Sensing Technology And Application13(1): 62-69. 

Fang H., and X. Huang, 1997. Remote Sensing Technique Applied in Geoscience-A Review Of Its Present Development (in Chinese). Geographical Research16(2): 96-103. 

Fang H., H. Liu, J. Huang, K. Liu, 1996. An Integrated System For Rice Production Estimation (in Chinese). Remote Sensing Technology And Application11(2): 45-53. 

Liu H., B. Wu, H. Fang, J. Huang, 1996. A Practical Method for Rice Acreage Estimation with Remote Sensing. The Journal of Chinese Geography6(4): 61-65. 

Major Research Projects:
1. Retrieval of land surface parameters and assimilation with a crop growth model for crop yield estimation.
2. Uncertainty analysis and improvement of global leaf area index (LAI) products in China’s paddy rice fields.

Office Address:
11A Da Tun Road
An Wai, Beijing 100101
People’s Republic of China
Telephone: 86-10-6488-8005
Fax: 86-10-6488-9630

Updated on December 17, 2020 

Copyright Institute of Geographic Sciences and Natural Resources Research, CAS
Address: 11A, Datun Road ,Chaoyang District, Beijing, 100101, China   Email: weboffice@igsnrr.ac.cn