Name: FANG Hongliang Ph.D. (University of Maryland, College Park)
Current Appointment: Professor (2009), CEOS/WGCV/LPV biophysical focus area lead (2016-2022)
, Remote Sensing of Environment Editorial Board, IEEE Geoscience and Remote Sensing Letters Associate editor, 《Acta Geographica Sinica》 Editor.
Education:
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:
2023
Zhu, K., Chen, J., Wang, S., Fang, H., Chen, B., Zhang, L., Li, Y., Zheng, C., & Amir, M. (2023). Characterization of the layered SIF distribution through hyperspectral observation and SCOPE modeling for a subtropical evergreen forest. ISPRS Journal of Photogrammetry and Remote Sensing, 201, 78-91. https://doi.org/10.1016/j.isprsjprs.2023.05.014
Wang, Y., Fang, H., Zhang, Y., Li, S., Pang, Y., Ma, T., and Li, Y., 2023. Retrieval and validation of vertical LAI profile derived from airborne and spaceborne LiDAR data at a deciduous needleleaf forest site. GIScience & Remote Sensing, doi: 10.1080/15481603.2023.2214987
Filella, I., Descals, A., Balzarolo, M., Yin, G., Verger, A., Fang, H., and Pe？uelas, J, 2023. Photosynthetically active radiation and foliage clumping improve satellite-based NIRv estimates of gross primary production. Remote Sensing, 15(8):2207. https://doi.org/10.3390/rs15082207
Wang, Z., Qu, Y., and Fang, H. 2023. Improving the performance of smartphone-derived crop leaf area index. National Remote Sensing Bulletin (in Chinese), 27(2): 441-455. https://doi.org/10.11834/jrs.20210439.
Li, S., and H.Fang, 2023. Determination of the leaf inclination angle (LIA) through field and remote sensing methods: Current status and future prospects. Remote Sensing, 15(4), 946. https://doi.org/10.3390/rs15040946
Ma, T., and H. Fang, 2023. GSV-L: A general spectral vector model for hyperspectral leaf spectra simulation. International Journal of Applied Earth Observation and Geoinformation, 117, 103216. https://doi.org/10.1016/j.jag.2023.103216
Zhang, Y., Wu, Z., Fang, H., Gao, X., Wang, J., and Wu, G., 2023. Estimation of daily FAPAR from MODIS instantaneous observations at forest sites. Agricultural and Forest Meteorology, 331, 109336. https://doi.org/10.1016/j.agrformet.2023.109336
2022
Liu, T., Jin, H., Li, A., Fang, H., Wei, D., Xie, X., & Nan, X. (2022). Estimation of Vegetation Leaf-Area-Index Dynamics from Multiple Satellite Products through Deep-Learning Method. Remote Sensing, 14(19), 4733. https://doi.org/10.3390/rs14194733
Liu, T., Jin, H., Xie, X., Fang, H., Wei, D., and Li, A., 2022. Bi-LSTM model for time series leaf area index estimation using multiple satellite products, IEEE Geoscience and Remote Sensing Letters. 19, 2506805. https://doi.org/10.1109/LGRS.2022.3199765
Li, S., Fang, H., Zhang, Y., and Wang, Y., 2022. Comprehensive evaluation of global CI, FVC, and LAI products and their relationships using high-resolution reference data. Science of Remote Sensing, 5, 100066. https://doi.org/10.1016/j.srs.2022.100066
Li, Y. and Fang, H., 2022. Real-time software for the efficient generation of the clumping index and its application based on the Google Earth Engine. Remote Sensing, 14(15), 3837. https://doi.org/10.3390/rs14153837
Geng, X., Wang, X., Fang, H., Ye, J., Han, L., Gong, Y., & Cai, D. (2022). Vegetation coverage of desert ecosystems in the Qinghai-Tibet Plateau is underestimated. Ecological Indicators, 137, 108780. https://doi.org/10.1016/j.ecolind.2022.108780
Sun, T., Fang, H., Chen, L., and Sun, R., 2022. A method to estimate clear-sky albedo of paddy rice fields. Remote Sensing, 14(20), 5185. https://doi.org/10.3390/rs14205185
2021
Fang, H., Che, T., Jin, R., Li, A., Li, X., Li, Z., Liu, S., Ma, M., Xiao, Q., and Zhang Y., 2021. On the construction of China's fiducial reference measurement (FRM) network for land surface remote sensing product validation (In Chinese), Advances in Earth Science, 36(12): 1215-1223. https://doi.org/10.11867/j.issn.1001-8166.2022.003
Chen, B., Lu, X., Wang, S., Chen, J.M., Liu, Y., Fang, H., Liu, Z., Jiang, F., Arain, M.A., Chen, J., & Wang, X. (2021). Evaluation of Clumping Effects on the Estimation of Global Terrestrial Evapotranspiration. Remote Sensing, 13, 4075. https://doi.org/10.3390/rs13204075
Yan, K., Zou, D., Yan, G., Fang, H., Weiss, M., Rautiainen, M., Knyazikhin, Y., & Myneni, R.B. (2021). A Bibliometric Visualization Review of the MODIS LAI/FPAR Products from 1995 to 2020. Journal of Remote Sensing, 2021, 7410921. https://doi.org/10.34133/2021/7410921
Fang, H., Wang Y., Zhang, Y., and Li S., 2021. Long-term variation of global GEOV2 and MODIS leaf area index (LAI) and their uncertainties: An insight into the product stabilities. Journal of Remote Sensing, 2021, 9842830. https://doi.org/10.34133/2021/9842830
Fang, H., Li, S., Zhang, Y., Wei, S., and Wang Y., 2021. New insights of global vegetation structural properties through an analysis of canopy clumping index, fractional vegetation cover, and leaf area index. Science of Remote Sensing, 4, 100027. https://doi.org/10.1016/j.srs.2021.100027
Hu, K., Zhang, Z., Fang, H., Lu, Y., Gu, Z., and Gao M., 2021. Spatial-temporal characteristics and driving factors of the foliage clumping index in the Sanjiang Plain from 2001 to 2015, Remote Sensing, 13(14), 2797. https://doi.org/10.3390/rs13142797
Zhang Y., Fang, H., Wang, Y., and Li S., 2021. Variation of intra-daily instantaneous FAPAR estimated from the geostationary Himawari-8 AHI data. Agricultural and Forest Meteorology, 307, 108535. https://doi.org/10.1016/j.agrformet.2021.108535
Fang H., 2021. Retrieval of forest vertical leaf area index and clumping index through field measurement and remote sensing techniques: A review (in Chinese). Chinese Science Bulliten, 66(24), 3141-3153. https://doi.org/10.1360/TB-2020-1057.
Fang, H., 2021. Scaling effects of the true and effective leaf area index (LAI and LAIe) and clumping Index (CI) (in Chinese). Journal of Geo-information Science, 23(7): 1155-1168. https://doi.org/0.12082/dqxxkx.2021.200609.
Fang, H., 2021. Canopy clumping index (CI): A review of methods, characteristics, and applications. Agricultural and Forest Meteorology, 303, 108374. https://doi.org/10.1016/j.agrformet.2021.108374
Fang, H., 2021. Retrieval of land surface parameters from geostationary satellite data：
An overview of recent developments (in Chinese). National Remote Sensing Bulletin, 25(1): 109-125. https://doi.org/10.11834/jrs.20210194
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
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.
2019
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, 57(3): 739-799. 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 Environment, 233, 111377, https://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.
2018
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.
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.
2017
Jiang, C.,Ryu, Y.,Fang, H.,Myneni, R.,Claverie, M.and Zhu, Z., 2017. Inconsistencies of interannual variability and trends in long-term satellite leaf area index products. Global Change Biology, 23(10): 4133-4146. doi: 10.1111/gcb.13787.
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 Meteorology, 233, 143-152. doi: 10.1016/j.agrformet.2016.11.010.
2016
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 Environment. 187: 476-491. doi: 10.1016/j.rse.2016.10.039.
2015
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 – Biogeosciences, 120: 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 Sensing, 101: 47-56, doi: 10.1016/j.isprsjprs.2014.11.004.
2014
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 Meteorology, 198-199(0): 126-141, doi: 10.1016/j.agrformet.2014.08.005.
Liu, Q., S. Liang, Z. Xiao, andH. Fang, 2014. Retrieval of leaf area index using temporal, spectral, and angular information from multiple satellite data.Remote Sensing of Environment,145: 25-37.
2013
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 – Biogeosciences, 118(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 Sensing, 5(2):830-844.
2012
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 Environment, 124, 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 Cycles, 26, 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 Ecology, 27(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 Environment, 119, 43-54.
Jiang, C., H. Fang, and S. Wei, 2012. Review of land surface roughness parameterization study (in Chinese). Advances in Earth Science, 27(3): 292-303.
Yang, F., J. Sun, H. Fang, Z. Yao, J. Zhang, Y. Zhua, K. Song, Z. Wang, M. Hua, Comparison of Different Methods for Corn LAI Estimation over Northeastern China. International Journal of Applied Earth Observation and Geoinformation. 2012. 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 Earth, 5(5): 439-455. doi:10.1080/17538947.2011.596579.
2011
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.
2008
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 Sensing, 29(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 Environment, 112(1): 75-93.
2007
Sun, W., S. Liang, G. Xu, H. Fang, and R. Dickinson, (2007), Mapping Plant Functional Types from MODIS Data Using Multisource 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
2006
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 - Atmosphere, 111, D15208, doi:10.1029/2005JD006730.
2005
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 Sensing, 43(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 Environment, 94(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 Management, 35(1): 1-13.
2004
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 Environment, 92(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 Sensing, 25(2): 409-422.
Liang, S., H. Fang, 2004. An improved atmospheric correction algorithm for hyperspectral remotely sensed imagery. IEEE Geosciences and Remote Sensing Letters, 1(2): 112-117.
2003
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.
2002
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 Environment, 83(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.
2001
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.
Before 2000
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 (in Chinese). The Journal of Chinese Geography, 9(4): 402-409.
Xu J., H. Fang, S. Fu, X. Huang, 1999. Estimating Suspended Sediment Concentrations from SPOT Image: A Case Study in Danshuihe, Taiwan (in Chinese). Remote Sensing Technology and Application, 14(4): 17-22.
Fang H., 1998. Rice Crop Area Estimation of an Administrative Division in China Using Remote Sensing. International Journal of Remote Sensing. 19(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 Research, 17, 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/Pacific, April/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 Application, 13(3): 48-53.
Fang H., and Q. Tian, 1998. A Review of Hyperspectral Remote Sensing in Vegetation Monitoring (in Chinese). Remote Sensing Technology and Application, 13(1): 62-69.
Fang H., and X. Huang, 1997. Remote Sensing Technique Applied in Geoscience-A Review Of Its Present Development (in Chinese). Geographical Research, 16(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 Application, 11(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 Geography, 6(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
Email: fanghl@lreis.ac.cn
Updated on June 6, 2023
