1.学术论文
[1] Han, Y., Wen,J.G*., Xiao, Q., Wu, X.D., You, D.Q., Tang, Y., Gong, B.C., Zhang, H.L.,Liu, Q.H., Zhu, W.Z., & Chen, Z.Q. (2024). Characterizing the effects ofatmospheric and land surface factors on the diurnal variation of land surfacealbedo (DVLSA) over vegetated surfaces. Solar Energy, 270, 14, http://doi.org/10.1016/j.solener.2024.112386
[2] Li, T.C.,Xin, X.Z*., Zhang, H.L., Yu, S.S., Li, L., Ye, Z.Q., Liu, Q.H., &Cai, H. (2024). Evaluation of Six Data Products of Surface Downward ShortwaveRadiation in Tibetan Plateau Region. Remote Sensing, 16, 19, http://doi.org/10.3390/rs16050791
[3] Bian, Z.J*., Fan, T.Y., Roujean, J.L., Wang, D.D.,Irvine, M., Wu, S.B., Cao, B., Li, H*., Du, Y.M., Xiao, Q., & Liu,Q.H. (2024). An analytical urban temperature model with building heterogeneityusing geometric optical theory. Remote Sensing of Environment, 301, 16, http://doi.org/10.1016/j.rse.2023.113948
[4] Chu,T.J., Li, J*., Zhao, J., Gu, C.P., Mumtaz, F., Dong, Y.D., Zhang, H.,& Liu, Q.H. (2024). Regional Analysis of Dominant Factors Influencing LeafChlorophyll Content in Complex Terrain Regions Using a Geographic StatisticalModel. Remote Sensing, 16, 16, http://doi.org/10.3390/rs16030479
[5] He, M., Wen,J.G*., Wu, S.B., Meng, L., Lin, X.W., Han, Y., You, D.Q., Tang, Y., &Liu, Q.H. (2024). A New Forest Leaf Area Index Retrieval Algorithm Over SlopeSurface. Ieee Transactions on Geoscience and Remote Sensing, 62,18,http://doi.org/10.1109/tgrs.2023.3343876
[6] Hu, T*., Roujean, J.L., Cao, B., Mallick, K.,Boulet, G., Li, H., Xu, Z.H., Du, Y.M., & Liu, Q.H. (2023). Correction forLST directionality impact on the estimation of surface upwelling longwaveradiation over vegetated surfaces at the satellite scale. Remote Sensing ofEnvironment, 295, 22, http://doi.org/10.1016/j.rse.2023.113649
[7] Liu, C., Li,J*., Liu, Q.H., Gao, J.X., Mumtaz, F., Dong, Y.D., Wang, C., Gu, C.P.,& Zhao, J. (2023). Combined influence of ENSO and North AtlanticOscillation (NAO) on Eurasian Steppe during 1982-2018. Science of the TotalEnvironment, 892, 12, http://doi.org/10.1016/j.scitotenv.2023.164735
[8] Sun,G.Y., Li, Z., Zhang, A.Z., Wang, X., Yan, K*., Jia, X.P., Liu, Q.H.,& Li, J*. (2023). A 10-m resolution impervious surface area map forthe greater Mekong subregion from remote sensing images. Scientific Data, 10,9, http://doi.org/10.1038/s41597-023-02518-z
[9] Zhao, J.,Li, J*., Liu, Q.H., Dong, Y.D., Li, L., & Zhang, H. (2023).Assessment of Forest Ecosystem Variations in the Lancang-Mekong Region byRemote Sensing from 2010 to 2020. Sensors, 23, 17, http://doi.org/10.3390/s23229038
[10] Liu, C., Li,J*., Liu, Q.H., Xu, B.D., Dong, Y.D., Zhao, J., Mumtaz, F., Gu, C.P., &Zhang, H. (2023). Global Comparison of Leaf Area Index Products overWater-Vegetation Mixed Heterogeneous Surface Network (HESNet-WV). RemoteSensing, 15, 21, http://doi.org/10.3390/rs15051337
[11] Wen,J.G., Wu, X.D*., Xiao, Q*., Liu, Q.H., Ma, M.G., Zheng, X.M., Qu,Y.H., Jin, R., You, D.Q., Tang, Y., Lin, X.W., Yu, W.P., Gong, B.C., Yang, J.,& Han, Y. (2023). Full-band, multi-angle, multi-scale, and temporal dynamicfield spectral measurements in China. Scientific Data, 10, 17, http://doi.org/10.1038/s41597-023-02265-1
[12] Bian, Z.J*., Roujean, J.L., Fan, T.Y., Dong, Y.D., Hu,T., Cao, B., Li, H., Du, Y.M*., Xiao, Q., & Liu, Q.H*.(2023). An angular normalization method for temperature vegetation drynessindex (TVDI) in monitoring agricultural drought. Remote Sensing of Environment,284, 17, http://doi.org/10.1016/j.rse.2022.113330
[13] Mumtaz,F., Li, J*., Liu, Q.H., Tariq, A., Arshad, A., Dong, Y.D., Zhao, J.,Bashir, B., Zhang, H., Gu, C.P., & Liu, C. (2023). Impacts of GreenFraction Changes on Surface Temperature and Carbon Emissions: Comparison underForestation and Urbanization Reshaping Scenarios. Remote Sensing, 15, 24, http://doi.org/10.3390/rs15030859
[14] Cai, H., Zhong,B*., Liu, H.L., Du, B.L., Liu, Q.H., Wu, S.L., Li, L., Yang, A.X., Wu,J.J., Gu, X.F., & Jiang, J.X. (2023). An improved deep learning network forAOD retrieving from remote sensing imagery focusing on sub-pixel cloud.Giscience & Remote Sensing, 60, 25, http://doi.org/10.1080/15481603.2023.2262836
[15] Gu, C.P.,Li, J*., Liu, Q.H*., Zhang, H., Liu, L.Y., Mumtaz, F., Dong, Y.D., Zhao,J., Wang, X.H., & Liu, C. (2023). Retrieving decametric-resolution leafchlorophyll content from GF-6 WFV by assessing the applicability of red-edgevegetation indices. Computers and Electronics in Agriculture, 215, 14, http://doi.org/10.1016/j.compag.2023.108455
[16] Mumtaz, F*., Li, J*., Liu, Q.H*., Arshad,A., Dong, Y.D., Liu, C., Zhao, J., Bashir, B., Gu, C.P., Wang, X.H., &Zhang, H. (2023). Spatio-temporal dynamics of land use transitions associatedwith human activities over Eurasian Steppe: Evidence from improved residualanalysis. Science of the Total Environment, 905,16,http://doi.org/10.1016/j.scitotenv.2023.166940
[17] Wu, J.J.,Li, Y., Zhong, B*., Liu, Q.H., Wu, S.L., Ji, C.Y., Zhao, J., Li, L.,Shi, X.L., & Yang, A.X. (2023). Integrated vegetation cover of typicalsteppe in China based on mixed decomposing derived from high resolution remotesensing data. Science of the Total Environment, 904,16,http://doi.org/10.1016/j.scitotenv.2023.166738
[18] Yu, S.S.,Xin, X.Z*., Zhang, H.L., Li, L., Zhu, L., & Liu, Q.H. (2023). ACloud Water Path-Based Model for Cloudy-Sky Downward Longwave RadiationEstimation from FY-4A Data. Remote Sensing, 15,20,http://doi.org/10.3390/rs15235531
[19] Zhao, J.,Li, J., Liu, Q.H*., Xu, B.D., Mu, X.H., & Dong, Y.D. (2023).Generation of a 16 m/10-day fractional vegetation cover product over Chinabased on Chinese GaoFen-1 observations: method and validation. InternationalJournal of Digital Earth, 16, 4229-4246, http://doi.org/10.1080/17538947.2023.2264815
[20] Qin,B.X., Cao, B*., Roujean, J.L., Gastellu-Etchegorry, J.P., Ermida, S.L.,Bian, Z.J., Du, Y.M., Hu, T., Li, H., Xiao, Q., Chen, S.S., & Liu, Q.H.(2023). A thermal radiation directionality correction method for the surfaceupward longwave radiation of geostationary satellite based on a time-evolvingkernel-driven model. Remote Sensing of Environment, 294,23,http://doi.org/10.1016/j.rse.2023.113599
[21] Chen, Y.,Weng, Q.H., Tang, L.L*., Wang, L., Xing, H.F., & Liu, Q.H. (2023).Developing an intelligent cloud attention network to support global urban greenspaces mapping. Isprs Journal of Photogrammetry and Remote Sensing, 198,197-209,http://doi.org/10.1016/j.isprsjprs.2023.03.005
[22] Cao, B.,Gastellu-Etchegorry, J.P., Yin, T.G., Bian, Z.J., Bai, J.H., Fang, J.Y., Qin,B.X., Du, Y.M*., Li, H., Xiao, Q., & Liu, Q.H. (2023). Optimizingthe Protocol of Near-Surface Remote Sensing Experiments Over HeterogeneousCanopy Using DART Simulated Images. Ieee Transactions on Geoscience and RemoteSensing, 61, 16, http://doi.org/10.1109/tgrs.2023.3239423
[23] Dong,Y.D., Li, J*., Jiao, Z.T., Liu, Q.H., Zhao, J., Xu, B.D., Zhang, H.,Zhang, Z.X., Liu, C., Knyazikhin, Y., & Myneni, R.B. (2023). A Method forRetrieving Coarse-Resolution Leaf Area Index for Mixed Biomes Using aMixed-Pixel Correction Factor. Ieee Transactions on Geoscience and Remote Sensing,61, 17,http://doi.org/10.1109/tgrs.2023.3235949
[24] Li, H.,Li, R.B., Tu, H., Cao, B*., Liu, F.J., Bian, Z.J., Hu, T., Du, Y.M.,Sun, L., & Liu, Q.H. (2023). An Operational Split-Window Algorithm forGenerating Long-Term Land Surface Temperature Products from Chinese Fengyun-3Series Satellite Data. Ieee Transactions on Geoscience and Remote Sensing, 61,14, http://doi.org/10.1109/tgrs.2023.3315968
[25] Li, R.B.,Li, H*., Hu, T., Bian, Z.J., Liu, F.J., Cao, B., Du, Y.M., Sun, L.,& Liu, Q.H. (2023). Land Surface Temperature Retrieval from Sentinel-3ASLSTR Data: Comparison Among Split-Window, Dual-Window, Three-Channel, andDual-Angle Algorithms. Ieee Transactions on Geoscience and Remote Sensing, 61,14, http://doi.org/10.1109/tgrs.2023.3288584
[26] Yu, S.S*., Li, L., Cao, B., Zhang, H.L., Zhu, L., Xin,X.Z*., & Liu, Q.H. (2022). Surface downward longwave radiationestimation from new generation geostationary satellite data. AtmosphericResearch, 276, 20, http://doi.org/10.1016/j.atmosres.2022.106255
[27] Li, Y., Wu,J.J*., Zhong, B., Shi, X.L., Xu, K.P., Ao, K., Sun, B., Ding, X.Y., Wang,X.S., Liu, Q.H., Yang, A.X., Chen, F., & Shi, M.Q. (2022). Methods of SandyLand Detection in a Sparse-Vegetation Scene Based on the Fusion of HJ-2AHyperspectral and GF-3 SAR Data. Remote Sensing, 14, 20, http://doi.org/10.3390/rs14051203
[28] Bian,Z.J., Lu, Y.F., Du, Y.M., Zhao, W., Cao, B.A., Hu, T., Li, R.B., Li, H*.,Xiao, Q., & Liu, Q.H. (2022). Comparison between Physical and EmpiricalMethods for Simulating Surface Brightness Temperature Time Series. RemoteSensing, 14, 24, http://doi.org/10.3390/rs14143385
[29] Bian, Z.J*., Wu, S.B., Roujean, J.L., Cao, B*.,Li, H., Yin, G.F., Du, Y.M., Xiao, Q., & Liu, Q.H. (2022). A TIR forestreflectance and transmittance (FRT) model for directional temperatures withstructural and thermal stratification. Remote Sensing of Environment, 268, 16, http://doi.org/10.1016/j.rse.2021.112749
[30] Cheng,J., Wen, J.G*., Xiao, Q., Wu, S.B., Hao, D.L., & Liu, Q.H. (2022).Extending the GOSAILT Model to Simulate Sparse Woodland Bi-DirectionalReflectance with Soil Reflectance Anisotropy Consideration. Remote Sensing, 14,21, http://doi.org/10.3390/rs14041001
[31] Wang, C.,Li, J*., Liu, Q.H., Huete, A., Li, L.H., Dong, Y.D., & Zhao, J.(2022). Eastern-Pacific and Central-Pacific Types of ENSO Elicit DiverseResponses of Vegetation in the West Pacific Region. Geophysical ResearchLetters, 49, 10, http://doi.org/10.1029/2021gl096666
[32] Lin,X.W., Wu, S.B*., Chen, B., Lin, Z.Y., Yan, Z.B., Chen, X.Z., Yin, G.F.,You, D.Q., Wen, J.G., Liu, Q., Xiao, Q., Liu, Q.H., & Lafortezza, R.(2022). Estimating 10-m land surface albedo from Sentinel-2 satelliteobservations using a direct estimation approach with Google Earth Engine. IsprsJournal of Photogrammetry and Remote Sensing, 194, 1-20, http://doi.org/10.1016/j.isprsjprs.2022.09.016
[33] Zhang,H., Li, J*., Liu, Q.H., Lin, S.R., Huete, A., Liu, L.Y., Croft, H.,Clevers, J., Zeng, Y.L., Wang, X.H., Gu, C.P., Zhang, Z.X., Zhao, J., Dong,Y.D., Mumtaz, F., & Yu, W.T. (2022). A novel red-edge spectral index forretrieving the leaf chlorophyll content. Methods in Ecology and Evolution, 13,2771-2787, http://doi.org/10.1111/2041-210x.13994
[34] Bian,Z.J., Qi, J.B., Gastellu-Etchegorry, J.P., Roujean, J.L., Cao, B., Li, H., Du,Y.M., Xiao, Q*., & Liu, Q.H. (2022). A GPU-Based Solution for RayTracing 3-D Radiative Transfer Model for Optical and Thermal Images. IeeeGeoscience and Remote Sensing Letters, 19, 5, http://doi.org/10.1109/lgrs.2022.3206312
[35] Chen, Y.,Weng, Q.H*., Tang, L.L*., Liu, Q.H., & Fan, R.S. (2022). AnAutomatic Cloud Detection Neural Network for High-Resolution Remote SensingImagery with Cloud-Snow Coexistence. Ieee Geoscience and Remote SensingLetters, 19, 5, http://doi.org/10.1109/lgrs.2021.3102970
[36] Cheng,J., Wen, J.G*., Xiao, Q., Hao, D.L., Lin, X.W., & Liu, Q.H. (2022).Exploring the Applicability of the Semi-Empirical BRDF Models at DifferentScales Using Airborne Multi-Angular Observations. Ieee Geoscience and RemoteSensing Letters, 19, 5, http://doi.org/10.1109/lgrs.2021.3135046
[37] Jia, C., Sun,L*., Chen, Y.F., Liu, Q.H., Yu, H.Y., & Zhang, W.H. (2022). SatelliteAerosol Retrieval Using Scene Simulation and Deep Belief Network. IeeeTransactions on Geoscience and Remote Sensing, 60, 16, http://doi.org/10.1109/tgrs.2021.3116154
[38] Lin,X.W., Wu, S.B.*., Hao, D.L., Wen, J.G*., Xiao, Q., & Liu,Q.H. (2022). Sloping Surface Reflectance: The Best Option for Satellite-BasedAlbedo Retrieval Over Mountainous Areas. Ieee Geoscience and Remote SensingLetters, 19, 5, http://doi.org/10.1109/lgrs.2021.3069637
[39] Ran,X.T., Cao, B*., Qin, B.X., Bian, Z.J., Du, Y.M., Li, H., Xiao, Q., &Liu, Q.H*. (2022). Assessment of Five Thermal Infrared Kernel-DrivenModels Using Limited Multiangle Observations. Ieee Geoscience and RemoteSensing Letters, 19, 5, http://doi.org/10.1109/lgrs.2021.3078647
[40] Wen,J.G., Lin, X.W*., Wu, X.D., Bao, Y.F., You, D.Q., Gong, B.C., Tang, Y.,Wu, S.B., Xiao, Q., & Liu, Q.H. (2022). Validation of the MCD43A3Collection 6 and GLASS VO4 Snow-Free Albedo Products Over Rugged Terrain. IeeeTransactions on Geoscience and Remote Sensing, 60, 11, http://doi.org/10.1109/tgrs.2022.3214103
[41] Wen,J.G., You, D.Q*., Han, Y., Lin, X.W., Wu, S.B.A., Tang, Y., Xiao, Q.,& Liu, Q.H. (2022). Estimating Surface BRDF/Albedo Over Rugged TerrainUsing an Extended Multisensor Combined BRDF Inversion (EMCBI) Model. IeeeGeoscience and Remote Sensing Letters, 19, 5, http://doi.org/10.1109/lgrs.2022.3143197
[42] Yu, W.T.,Li, J*., Liu, Q.H., Zhao, J., Dong, Y.D., Wang, C., Lin, S.R., Zhu,X.R., & Zhang, H. (2022). Spatial-Temporal Prediction of Vegetation Index withDeep Recurrent Neural Networks. Ieee Geoscience and Remote Sensing Letters, 19,5, http://doi.org/10.1109/lgrs.2021.3064814
[43] Zhao, J.,Li, J*., Liu, Q.H., Zhang, Z.X., & Dong, Y.D. (2022). ComparativeStudy of Fractional Vegetation Cover Estimation Methods Based on Fine SpatialResolution Images for Three Vegetation Types. Ieee Geoscience and RemoteSensing Letters, 19, 5, http://doi.org/10.1109/lgrs.2022.3222018
[44] Zhu,X.R., Li, J*., Liu, Q.H., Yu, W.T., Li, S.Z., Zhao, J., Dong, Y.D.,Zhang, Z.X., Zhang, H., & Lin, S.R. (2022). Use of a BP Neural Network andMeteorological Data for Generating Spatiotemporally Continuous LAI Time Series.Ieee Transactions on Geoscience and Remote Sensing, 60, 14, http://doi.org/10.1109/tgrs.2021.3095535
[45] Cao,B.A., Qi, J.B., Chen, E.X., Xiao, Q., Liu, Q.H*., & Li, Z.Y. (2021).Fine scale optical remote sensing experiment of mixed stand over complexterrain (FOREST) in the Genhe Reserve Area: objective, observation and a casestudy. International Journal of Digital Earth, 14, 1411-1432, http://doi.org/10.1080/17538947.2021.1968047
[46] Chen, Y.,Weng, Q.H*., Tang, L.L*., Liu, Q.H., Zhang, X., & Bilal, M. (2021).Automatic mapping of urban green spaces using a geospatial neural network.Giscience & Remote Sensing, 58, 624-642, http://doi.org/10.1080/15481603.2021.1933367
[47] Zhong,B., Yang, A.X*., Liu, Q.H., Wu, S.L., Shan, X.J., Mu, X.H., Hu, L.F.,& Wu, J.J. (2021). Analysis Ready Data of the Chinese GaoFen SatelliteData. Remote Sensing, 13, 16, http://doi.org/10.3390/rs13091709
[48] Bian,Z.J., Cao, B.A., Li, H., Du, Y.M*., Fan, W.J., Xiao, Q., & Liu, Q.H.(2021). The Effects of Tree Trunks on the Directional Emissivity and BrightnessTemperatures of a Leaf-Off Forest Using a Geometric Optical Model. IeeeTransactions on Geoscience and Remote Sensing, 59, 5370-5386, http://doi.org/10.1109/tgrs.2020.3011157
[49] Lin,S.R., Coops, N.C*., Tortini, R., Jia, W., Nesic, Z., Beamesderfer, E.,Arain, M.A., Li, J., & Liu, Q.H. (2021). Species and stand-age drivendifferences in photochemical reflectance index and light use efficiency acrossfour temperate forests. International Journal of Applied Earth Observation andGeoinformation, 98, 16, http://doi.org/10.1016/j.jag.2021.102308
[50] Zhang,H.L*., Dong, X.Q., Xi, B.K., Xin, X.Z*.,Liu, Q.H., He, H.M., Xie, X.P., Li, L., & Yu, S.S. (2021). Retrieving high-resolutionsurface photosynthetically active radiation from the MODIS and GOES-16 ABIdata. Remote Sensing of Environment, 260, 15, http://doi.org/10.1016/j.rse.2021.112436
[51] Bian,Z.J., Roujean, J.L., Cao, B.A., Du, Y.M*., Li, H., Gamet, P., Fang, J.Y.,Xiao, Q., & Liu, Q.H. (2021). Modeling the directional anisotropy offine-scale TIR emissions over tree and crop canopies based on UAV measurements.Remote Sensing of Environment, 252, 16, http://doi.org/10.1016/j.rse.2020.112150
[52] Cao, B.,Roujean, J.L., Gastellu-Etchegorry, J.P., Liu, Q.H., Du, Y.M*.,Lagouarde, J.P., Huange, H.G., Li, H., Bian, Z.J., Hu, T., Qin, B.X., Ran,X.T., & Xiao, Q. (2021). A general framework of kernel-driven modeling inthe thermal infrared domain. Remote Sensing of Environment, 252, 26, http://doi.org/10.1016/j.rse.2020.112157
[53] Li, H.,Li, R.B., Yang, Y.K., Cao, B., Bian, Z.J., Hu, T., Du, Y.M*., Sun, L.,& Liu, Q.H. (2021). Temperature-Based and Radiance-Based Validation of theCollection 6 MYD11 and MYD21 Land Surface Temperature Products Over BarrenSurfaces in Northwestern China. Ieee Transactions on Geoscience and RemoteSensing, 59, 1794-1807, http://doi.org/10.1109/tgrs.2020.2998945
[54] Wu, S.B.,Zeng, Y.L*., Hao, D.L., Liu, Q.H., Li, J., Chen, X.Z., Asrar, G.R., Yin,G.F., Wen, J.G., Yang, B., Zhu, P., & Chen, M*. (2021). Quantifyingleaf optical properties with spectral invariants theory. Remote Sensing ofEnvironment, 253, 9, http://doi.org/10.1016/j.rse.2020.112131
[55] Yu, W.T.,Li, J*., Liu, Q.H., Zhao, J., Dong, Y.D., Zhu, X.R., Lin, S.R., Zhang,H., & Zhang, Z.X. (2021). Gap Filling for Historical Landsat NDVI TimeSeries by Integrating Climate Data. Remote Sensing, 13, 21, http://doi.org/10.3390/rs13030484
[56] Menenti,M*., Li, X., Jia, L., Yang, K., Pellicciotti,F., Mancini, M., Shi, J.C., Escorihuela, M.J., Zheng, C.L., Chen, Q.T., Lu, J.,Zhou, J., Hu, G.C., Ren, S.T., Zhang, J., Liu, Q.H., Qiu, Y.B., Huang, C.L.,Zhou, J., Han, X.J., Pan, X.D., Li, H.Y., Wu, Y.R., Ding, B.H., Yang, W., Buri,P., McCarthy, M.J., Miles, E.S., Shaw, T.E., Ma, C.F., Zhou, Y.Z., Corbari, C.,Li, R., Zhao, T.J., Stefan, V., Gao, Q., Zhang, J.X., Xie, Q.X., Wang, N., Sun,Y.B., Mo, X.Y., Jia, J.R., Jouberton, A.P., Kneib, M., Fugger, S., Paciolla,N., & Paolini, G. (2021). Multi-Source Hydrological Data Products toMonitor High Asian River Basins and Regional Water Security. Remote Sensing,13, 29, http://doi.org/10.3390/rs13245122
[57] Zhang,H., Li, J*., Liu, Q.H., Dong, Y.D., Li, S.Z., Zhang, Z.X., Zhu, X.R.,Liu, L.Y., & Zhao, J. (2021). Estimating Leaf Area Index with Dynamic LeafOptical Properties. Remote Sensing, 13, 17, http://doi.org/10.3390/rs13234898
[58] Lin,S.R., Li, J*., Liu, Q.H., Gioli, B., Paul-Limoges, E., Buchmann, N.,Gharun, M., Hörtnagl, L., Foltynová, L., Dusek, J., Li, L.H., & Yuan, W.P.(2021). Improved global estimations of gross primary productivity of naturalvegetation types by incorporating plant functional type. International Journal of Applied Earth Observation and Geoinformation, 100, 14, http://doi.org/10.1016/j.jag.2021.102328
[59] Du, Y.M.,Cao, B*., Li, H., Bian, Z.J., Qin, B.X., Xiao, Q., Liu, Q.H., Zeng,Y.J., & Su, Z.B. (2020). Modeling Directional Brightness Temperature (DBT)over Crop Canopy with Effects of Intra-Row Heterogeneity. Remote Sensing, 12,20, http://doi.org/10.3390/rs12172667
[60] Wu, J.J.,Wang, X., Zhong, B*., Yang, A.X., Jue, K.S., Wu, J.H., Zhang, L., Xu,W.J., Wu, S.L., Zhang, N., & Liu, Q.H. (2020). Ecological environmentassessment for Greater Mekong Subregion based on Pressure-State-Responseframework by remote sensing. Ecological Indicators, 117, 14, http://doi.org/10.1016/j.ecolind.2020.106521
[61] Du, Y.M.,Li, H*., Cao, B., Bian, Z.J., Zhao, J.M., Xiao, Q., Liu, Q.H., Zeng,Y.J., & Su, Z.B. (2020). A Modified Interactive Spectral Smooth TemperatureEmissivity Separation Algorithm for Low-Temperature Surface. Ieee Transactionson Geoscience and Remote Sensing, 58, 7643-7653, http://doi.org/10.1109/tgrs.2020.2982960
[62] Yang,A.X., Zhong, B*., Hu, L.F., Wu, S.L., Xu, Z.P., Wu, H.B., Wu, J.J.,Gong, X.S., Wang, H.B., & Liu, Q.H. (2020). Radiometric Cross-Calibrationof the Wide Field View Camera Onboard GaoFen-6 in Multispectral Bands. RemoteSensing, 12, 21, http://doi.org/10.3390/rs12061037
[63] Qin,B.X., Cao, B*., Li, H., Bian, Z.J., Hu, T., Du, Y.M., Yang, Y.P., Xiao,Q., & Liu, Q.H. (2020). Evaluation of Six High-Spatial Resolution Clear-SkySurface Upward Longwave Radiation Estimation Methods with MODIS. RemoteSensing, 12, 24, http://doi.org/10.3390/rs12111834
[64] Liu, J., &Liu, Q.H*. (2020). Soil Moisture Estimate Uncertainties from the Effectof Soil Texture on Dielectric Semiempirical Models. Remote Sensing, 12, 21, http://doi.org/10.3390/rs12142343
[65] Hu, T*., Renzullo, L.J., van Dijk, A., He, J.,Tian, S.Y., Xu, Z.H., Zhou, J., Liu, T.J., & Liu, Q.H. (2020). Monitoringagricultural drought in Australia using MTSAT-2 land surface temperatureretrievals. Remote Sensing of Environment, 236, 13, http://doi.org/10.1016/j.rse.2019.111419
[66] Bian,Z.J., Roujean, J.L., Lagouarde, J.P., Cao, B., Li, H., Du, Y.M*., Liu,Q., Xiao, Q., & Liu, Q.H. (2020). A semi-empirical approach for modelingthe vegetation thermal infrared directional anisotropy of canopies based onusing vegetation indices. Isprs Journal of Photogrammetry and Remote Sensing,160, 136-148, http://doi.org/10.1016/j.isprsjprs.2019.12.004
[67] Zhong,B., Wu, S.L., Yang, A.X*., Ao, K., Wu, J.H., Wu, J.J., Gong, X.S., Wang,H.B., & Liu, Q.H. (2020). An Atmospheric Correction Method over Bright andStable Surfaces for Moderate to High Spatial-Resolution Optical Remotely SensedImagery. Remote Sensing, 12, 16, http://doi.org/10.3390/rs12040733
[68] Liu, J., Ferrazzoli,P*., Guerriero, L., Bai, J.H., Liu, Q.H*., & Zhang, Z.J. (2020).Modeling Microwave Emission of Corn Crop Considering Leaf Shape and OrientationUnder the Physical Optics Approximation. Ieee Transactions on Geoscience andRemote Sensing, 58, 8316-8331, http://doi.org/10.1109/tgrs.2020.2986256
[69] You,D.Q., Wen, J.G*., Liu, Q., Zhang, Y.T., Tang, Y., Liu, Q.H., & Xie, H.J.(2020). The Component-Spectra-Parameterized Angular and Spectral Kernel-DrivenModel: A Potential Solution for Global BRDF/Albedo Retrieval From MultisensorSatellite Data. Ieee Transactions on Geoscience and Remote Sensing, 58,8674-8688, http://doi.org/10.1109/tgrs.2020.2989635
[70] Li, R.B.,Li, H*., Sun, L., Yang, Y.K., Hu, T., Bian, Z.J., Cao, B., Du, Y.M.,& Liu, Q.H. (2020). An Operational Split-Window Algorithm for RetrievingLand Surface Temperature from Geostationary Satellite Data: A Case Study onHimawari-8 AHI Data. Remote Sensing, 12, 24, http://doi.org/10.3390/rs12162613
[71] Zhao, J.,Li, J*., Liu, Q.H., Xu, B.D., Yu, W.T., Lin, S.R., & Hu, Z. (2020).Estimating fractional vegetation cover from leaf area index and clumping indexbased on the gap probability theory. International Journal of Applied EarthObservation and Geoinformation, 90, 10, http://doi.org/10.1016/j.jag.2020.102112
[72] Lin,X.W., Wen, J.G*., Liu, Q.H., You, D.Q., Wu, S.B., Hao, D.L., Xiao, Q.,Zhang, Z.Y., & Zhang, Z.Z. (2020). Spatiotemporal Variability of LandSurface Albedo over the Tibet Plateau from 2001 to 2019. Remote Sensing, 12,18, http://doi.org/10.3390/rs12071188
[73] Xu, B.D.,Li, J*., Park, T.J., Liu, Q.H*., Zeng, Y.L., Yin, G.F., Yan, K.,Chen, C., Zhao, J., Fan, W.L., Knyazikhin, Y., & Myneni, R.B. (2020).Improving leaf area index retrieval over heterogeneous surface mixed withwater. Remote Sensing of Environment, 240, 16, http://doi.org/10.1016/j.rse.2020.111700
[74] Zeng,Y.L., Badgley, G., Chen, M., Li, J*., Anderegg, L.D.L., Kornfeld, A.,Liu, Q.H., Xu, B.D., Yang, B., Yan, K., & Berry, J.A. (2020). A radiativetransfer model for solar induced fluorescence using spectral invariants theory.Remote Sensing of Environment, 240, 15, http://doi.org/10.1016/j.rse.2020.111678
[75] Zeng,Y.L., Li, J*., Liu, Q.H., Huete, A.R., Xu, B.D., Yin, G.F., Fan, W.L.,Ouyang, Y.X., Yan, K., Hao, D.L., & Chen, M. (2020). A Radiative TransferModel for Patchy Landscapes Based on Stochastic Radiative Transfer Theory. IeeeTransactions on Geoscience and Remote Sensing, 58, 2571-2589, http://doi.org/10.1109/tgrs.2019.2952377
[76] Bian,Z.J., Li, H*., Göttsche, F.M., Li, R.B., Du, Y.M., Ren, H.Z., Cao, B.,Xiao, Q., & Liu, Q.H. (2020). Retrieving Soil and Vegetation TemperaturesFrom Dual-Angle and Multipixel Satellite Observations. Ieee Journal of SelectedTopics in Applied Earth Observations and Remote Sensing, 13, 5536-5549, http://doi.org/10.1109/jstars.2020.3024190
[77] Wu, S.B.,Wen, J.G*., Liu, Q.H., You, D.Q., Yin, G.F., & Lin, X.W. (2020).Improving Kernel-Driven BRDF Model for Capturing Vegetation Canopy ReflectanceWith Large Leaf Inclinations. Ieee Journal of Selected Topics in Applied EarthObservations and Remote Sensing, 13, 2639-2655, http://doi.org/10.1109/jstars.2020.2987424
[78] Yu, W.T.,Li, J*., Liu, Q.H., Yin, G.F., Zeng, Y.L., Lin, S.R., & Zhao, J.(2020). A Simulation-Based Analysis of Topographic Effects on LAI InversionOver Sloped Terrain. Ieee Journal of Selected Topics in Applied EarthObservations and Remote Sensing, 13, 794-806, http://doi.org/10.1109/jstars.2020.2970999
[79] Cao, B*.,Liu, Q.H*., Du, Y.M., Roujean, J.L.,Gastellu-Etchegorry, J.P., Trigo, I.F., Zhan, W.F., Yu, Y.Y., Cheng, J., Jacob,F., Lagouarde, J.P., Bian, Z.J., Li, H., Hu, T., & Xiao, Q. (2019). Areview of earth surface thermal radiation directionality observing andmodeling: Historical development, current status and perspectives. RemoteSensing of Environment, 232, 29, http://doi.org/10.1016/j.rse.2019.111304
[80] Du, Y.M.,Cao, B*., Li, H., Xiao, Q., Liu, Q.H., Zeng, Y.J., & Su, Z.B.(2019). An Experimental Study on Separating Temperature and Emissivity of aNonisothermal Surface. Ieee Geoscience and Remote Sensing Letters, 16,1610-1614, http://doi.org/10.1109/lgrs.2019.2905016
[81] Hu, T., Li,H*., Cao, B., van Dijk, A., Renzullo, L.J., Xu, Z., Zhou, J., Du, Y.M.,& Liu, Q.H*. (2019). Influence of emissivity angular variation onland surface temperature retrieved using the generalized split-windowalgorithm. International Journal of Applied Earth Observation andGeoinformation, 82, 11, http://doi.org/10.1016/j.jag.2019.101917
[82] Li, H.,Yang, Y.K., Li, R.B., Wang, H.S., Cao, B., Bian, Z.J., Hu, T., Du, Y.M*.,Sun, L., & Liu, Q.H. (2019). Comparison of the MuSyQ and MODIS Collection 6Land Surface Temperature Products Over Barren Surfaces in the Heihe RiverBasin, China. Ieee Transactions on Geoscience and Remote Sensing, 57,8081-8094, http://doi.org/10.1109/tgrs.2019.2918259
[83] Li, H.,Wang, H.S., Yang, Y.K., Du, Y.M*., Cao, B., Bian, Z.J., & Liu, Q.H.(2019). Evaluation of Atmospheric Correction Methods for the ASTER Temperatureand Emissivity Separation Algorithm Using Ground Observation Networks in theHiWATER Experiment. Ieee Transactions on Geoscience and Remote Sensing, 57,3001-3014, http://doi.org/10.1109/tgrs.2018.2879316
[84] Ni, W.J*., Zhang, Z.Y., Sun, G.Q., & Liu, Q.H.(2019). Modeling the Stereoscopic Features of Mountainous Forest Landscapes forthe Extraction of Forest Heights from Stereo Imagery. Remote Sensing, 11, 21, http://doi.org/10.3390/rs11101222
[85] Wang, C.,Beringer, J., Hutley, L.B., Cleverly, J., Li, J., Liu, Q.H., & Sun, Y*.(2019). Phenology Dynamics of Dryland Ecosystems Along the North AustralianTropical Transect Revealed by Satellite Solar-Induced Chlorophyll Fluorescence.Geophysical Research Letters, 46, 5294-5302, http://doi.org/10.1029/2019gl082716
[86] Wu, S.B.,Wen, J.G*., Gastellu-Etchegorry, J.P., Liu, Q.H., You, D.Q., Xiao, Q.,Hao, D.L., Lin, X.W., & Yin, T.G. (2019). The definition of remotely sensedreflectance quantities suitable for rugged terrain. Remote Sensing ofEnvironment, 225, 403-415, http://doi.org/10.1016/j.rse.2019.01.005
[87] Zhang, Y*., Zhang, G.Y., Zhao, H.H., Cao, Y.M., Liu,Q.H*., Shen, Z.F., & Li, A.M. (2019). A Convenient Tool for DistrictHeating Route Optimization Based on Parallel Ant Colony System Algorithm and 3DWebGIS. Isprs International Journal of Geo-Information, 8, 18, http://doi.org/10.3390/ijgi8050225
[88] Du, Y*., Yang, C., Liu, Q.H., & Li, Z.Y.(2019). Physically Based Polarimetric Volumetric Scattering From CylindricallyDominated Vegetation Canopies. Ieee Transactions on Geoscience and RemoteSensing, 57, 1629-1636, http://doi.org/10.1109/tgrs.2018.2867861
[89] Guo,M.Z., Cao, B., Fan, W.J*., Ren, H.Z., Cui, Y.K., Du, Y.M., & Liu,Q.H. (2019). Scattering Effect Contributions to the Directional CanopyEmissivity and Brightness Temperature Based on CE-P and CBT-P Models. IeeeGeoscience and Remote Sensing Letters, 16, 957-961, http://doi.org/10.1109/lgrs.2018.2886606
[90] Lin, S.R.,Li, J*., Liu, Q.H., Li, L.H., Zhao, J., & Yu, W.T. (2019).Evaluating the Effectiveness of Using Vegetation Indices Based on Red-EdgeReflectance from Sentinel-2 to Estimate Gross Primary Productivity. RemoteSensing, 11, 25, http://doi.org/10.3390/rs11111303
[91] Hu, T.,Renzullo, L.J., Cao, B*., van Dijk, A., Du, Y.M., Li, H., Cheng, J., Xu,Z.H., Zhou, J., & Liu, Q.H*. (2019). Directional variation insurface emissivity inferred from the MYD21 product and its influence onestimated surface upwelling longwave radiation. Remote Sensing of Environment,228, 45-60 http://doi.org/10.1016/j.rse.2019.04.012
[92] Ma, Q.M.,Li, Y.J*., Li, J., & Liu, Q.H*. (2019). Modeling ofMixed-Pixel Clumping Index From Remote Sensing Data and Its Evaluation. IeeeJournal of Selected Topics in Applied Earth Observations and Remote Sensing,12, 2320-2331, http://doi.org/10.1109/jstars.2019.2897818
[93] Wu, S.B.,Wen, J.G*., You, D.Q., Zhang, H.L., Xiao, Q., & Liu, Q.H. (2019).Algorithms for Calculating Topographic Parameters and Their Uncertainties inDownward Surface Solar Radiation Estimation. Ieee Geoscience and Remote SensingLetters, 16, 160-160, http://doi.org/10.1109/lgrs.2018.2868526
[94] Li, F.G.,Xin, X.Z*., Peng, Z.Q., & Liu, Q.H. (2019). Estimating dailyevapotranspiration based on a model of evaporative fraction (EF) for mixedpixels. Hydrology and Earth System Sciences, 23, 949-969, http://doi.org/10.5194/hess-23-949-2019
[95] Liang,S.L*., Liu, Q.H., Yan, G.J., Shi, J.C., &Kerekes, J.P. (2019). Foreword to the Special Issue on The Recent Progress inQuantitative Land Remote Sensing: Modeling and Estimation. Ieee Journal ofSelected Topics in Applied Earth Observations and Remote Sensing, 12, 391-395, http://doi.org/10.1109/jstars.2019.2895942
[96] Wu, S.B.,Wen, J.G*., Lin, X.W., Hao, D.L., You, D.Q., Xiao, Q., Liu, Q.H., &Yin, T.G. (2019). Modeling Discrete Forest Anisotropic Reflectance Over aSloped Surface With an Extended GOMS and SAIL Model. Ieee Transactions onGeoscience and Remote Sensing, 57, 944-957, http://doi.org/10.1109/tgrs.2018.2863605
[97] Wu, S.B.,Wen, J.G*., Xiao, Q., Liu, Q.H., Hao, D.L., Lin, X.W., & You, D.Q.(2019). Derivation of Kernel Functions for Kernel-Driven Reflectance Model OverSloping Terrain. Ieee Journal of Selected Topics in Applied Earth Observationsand Remote Sensing, 12, 396-409, http://doi.org/10.1109/jstars.2018.2854771
[98] Yin, G.F*., Verger, A., Qu, Y.H., Zhao, W., Xu, B.D.,Zeng, Y.L., Liu, K., Li, J*., & Liu, Q.H. (2019). Retrieval of HighSpatiotemporal Resolution Leaf Area Index with Gaussian Processes, WirelessSensor Network, and Satellite Data Fusion. Remote Sensing, 11, 18, http://doi.org/10.3390/rs11030244
[99] Yu, S.S.,Xin, X.Z*., Liu, Q.H., Zhang, H.L., & Li, L. (2019). An ImprovedParameterization for Retrieving Clear-Sky Downward Longwave Radiation fromSatellite Thermal Infrared Data. Remote Sensing, 11, 27, http://doi.org/10.3390/rs11040425
[100] Zhang, D.F., Liu, J.L., Ni, W.J*.,Sun, G.Q., Zhang, Z.Y., Liu, Q.H., & Wang, Q. (2019). Estimation of ForestLeaf Area Index Using Height and Canopy Cover Information Extracted FromUnmanned Aerial Vehicle Stereo Imagery. Ieee Journal of Selected Topics inApplied Earth Observations and Remote Sensing, 12, 471-481, http://doi.org/10.1109/jstars.2019.2891519
[101] Cao, B., Gastellu-Etchegorry, J.P., Du,Y.M*., Li, H., Bian, Z.J., Hu, T., Fan, W.J., Xiao, Q., & Liu, Q.H.(2019). Evaluation of Four Kernel-Driven Models in the Thermal Infrared Band.Ieee Transactions on Geoscience and Remote Sensing, 57, 5456-5475, http://doi.org/10.1109/tgrs.2019.2899600
[102] Lin, S.R., Li, J*., Liu, Q.H*., Huete,A., & Li, L.H. (2018). Effects of Forest Canopy Vertical Stratification onthe Estimation of Gross Primary Production by Remote Sensing. Remote Sensing,10, 25,http://doi.org/10.3390/rs10091329
[103] Yin, G.F*., Li, A.N*., Wu, S.B., Fan, W.L., Zeng, Y.L., Yan, K.,Xu, B.D., Li, J., & Liu, Q.H. (2018). PLC: A simple and semi-physicaltopographic correction method for vegetation canopies based on path lengthcorrection. Remote Sensing of Environment, 215, 184-198, http://doi.org/10.1016/j.rse.2018.06.009
[104] Zhang, Y., Zhao, H.H., Cao, Y.M*., Liu,Q.H*., Shen, Z.F., Wang, J., & Hu, M.G. (2018). A Hybrid Ant Colony andCuckoo Search Algorithm for Route Optimization of Heating Engineering.Energies, 11, 23, http://doi.org/10.3390/en11102675
[105] Huang, H.G*., Zhang, Z.Y., Ni, W.J., Chai, L.N., Qin, W.H., Liu, G.,Xie, D.H., Jiang, L.M., & Liu, Q.H. (2018). Extending RAPID model tosimulate forest microwave backscattering. Remote Sensing of Environment, 217,272-291, http://doi.org/10.1016/j.rse.2018.08.011
[106] Liu, J., Liu, Q.H*., Li, H*., Du,Y.M., & Cao, B. (2018). An mproved Microwave Semiempirical Model for theDielectric Behavior of Moist Soils. Ieee Transactions on Geoscience and RemoteSensing, 56, 6630-6644, http://doi.org/10.1109/tgrs.2018.2841025
[107] Liu, Q.H*., Yan, G.J., Jiao, Z.T., Xiao, Q., Wen, J.G., Liang,S.L*., Wang, J.D., Schaaf, C., & Strahler, A. (2018). FromGeometric-Optical Remote Sensing Modeling to Quantitative Remote SensingScience-In Memory of Academician Xiaowen Li. Remote Sensing, 10, 11, http://doi.org/10.3390/rs10111764
[108] Bian, Z.J., Cao, B., Li, H., Du, Y.M.,Lagouarde, J.P., Xiao, Q., & Liu, Q.H*. (2018). An analyticalfour-component directional brightness temperature model for crop and forestcanopies. Remote Sensing of Environment, 209, 731-746, http://doi.org/10.1016/j.rse.2018.03.010
[109] Bian, Z.J., Cao, B.A., Li, H., Du, Y.M*.,Huang, H.G., Xiao, Q., & Liu, Q.H*. (2018). Modeling theDistributions of Brightness Temperatures of a Cropland Study Area Using a Modelthat Combines Fast Radiosity and Energy Budget Methods. Remote Sensing, 10, 20,http://doi.org/10.3390/rs10050736
[110] Fan, W.L., Li, J., Liu, Q.H., Zhang, Q., Yin,G.F., Li, A.N., Zeng, Y.L., Xu, B.D., Xu, X.J., Zhou, G.M*., & Du, H.Q*.(2018). Topographic Correction of Forest Image Data Based on the CanopyReflectance Model for Sloping Terrains in Multiple Forward Mode. RemoteSensing, 10, 16, http://doi.org/10.3390/rs10050717
[111] Ni, W.J., Zhang, Z.Y., Sun, G.Q*.,& Liu, Q.H. (2018). Modeling Interferometric SAR Features of ForestCanopies Over Mountainous Area at Landscape Scales. Ieee Transactions onGeoscience and Remote Sensing, 56, 2958-2967, http://doi.org/10.1109/tgrs.2017.2787704
[112] Xu, B.D., Li, J*., Park, T*., Liu, Q.H*.,Zeng, Y.L., Yin, G.F., Zhao, J., Fan, W.L., Yang, L., Knyazikhin, Y., &Myneni, R.B. (2018). An integrated method for validating long-term leaf areaindex products using global networks of site-based measurements. Remote Sensingof Environment, 209, 134-151, http://doi.org/10.1016/j.rse.2018.02.049
[113] Yu, S.S., Xin, X.Z*., Liu, Q.H.,Zhang, H.L., & Li, L. (2018). Comparison of Cloudy-Sky Downward LongwaveRadiation Algorithms Using Synthetic Data, Ground-Based Data, and SatelliteData. Journal of Geophysical Research-Atmospheres, 123, 5397-5415, http://doi.org/10.1029/2017jd028234
[114] Wen, J.G*., Liu, Q., Xiao, Q., Liu, Q.H., You, D.Q., Hao, D.L.,Wu, S.B., & Lin, X.W. (2018). Characterizing Land Surface AnisotropicReflectance over Rugged Terrain: A Review of Concepts and Recent Developments.Remote Sensing, 10, 30, http://doi.org/10.3390/rs10030370
[115] Zhang, H.L., Huang, C., Yu, S.S., Li, L., Xin,X.Z*., & Liu, Q.H*. (2018). A Lookup-Table-Based Approach to EstimatingSurface Solar Irradiance from Geostationary and Polar-Orbiting Satellite Data.Remote Sensing, 10, 19, http://doi.org/10.3390/rs10030411
[116] Yu, W.T., Li, J*., Liu, Q.H*., Zeng,Y.L., Zhao, J., Xu, B.D., & Yin, G.F. (2018). Global Land CoverHeterogeneity Characteristics at Moderate Resolution for Mixed Pixel Modelingand Inversion. Remote Sensing, 10, 17, http://doi.org/10.3390/rs10060856
[117] Zhao, J., Li, J*., Liu, Q.H*., Wang,H.Y., Chen, C., Xu, B.D., & Wu, S.L. (2018). Comparative Analysis ofChinese HJ-1 CCD, GF-1 WFV and ZY-3 MUX Sensor Data for Leaf Area IndexEstimations for Maize. Remote Sensing, 10, 20, http://doi.org/10.3390/rs10010068
[118] Lin, X.W., Wen, J.G*., Liu, Q.H*.,Xiao, Q., You, D.Q., Wu, S.B., Hao, D.L., & Wu, X.D. (2018). A Multi-ScaleValidation Strategy for Albedo Products over Rugged Terrain and PreliminaryApplication in Heihe River Basin, China. Remote Sensing, 10, 23, http://doi.org/10.3390/rs10020156
[119] Xu, B.D., Park, T*., Yan, K., Chen,C., Zeng, Y.L., Song, W.J., Yin, G.F., Li, J., Liu, Q.H., Knyazikhin, Y., &Myneni, R.B. (2018). Analysis of Global LAI/FPAR Products from VIIRS and MODISSensors for Spatio-Temporal Consistency and Uncertainty from 2012-2016.Forests, 9, 21, http://doi.org/10.3390/f9020073
[120] Cao, B., Guo, M.Z., Fan, W.J*., Xu,X.R., Peng, J.J., Ren, H.Z., Du, Y.M*., Li, H., Bian, Z.J., Hu, T.,Xiao, Q., & Liu, Q.H. (2018). A New Directional Canopy Emissivity ModelBased on Spectral Invariants. Ieee Transactions on Geoscience and RemoteSensing, 56, 6911-6926, http://doi.org/10.1109/tgrs.2018.2845678
[121] Liu, S.M*., Li, X., Xu, Z.W., Che, T., Xiao, Q., Ma, M.G., Liu,Q.H., Jin, R., Guo, J.W., Wang, L.X., Wang, W.Z., Qi, Y., Li, H.Y., Xu, T.R.,Ran, Y.H., Hu, X.L., Shi, S.J., Zhu, Z.L., Tan, J.L., Zhang, Y., & Ren,Z.G. (2018). The Heihe Integrated Observatory Network: A Basin-Scale LandSurface Processes Observatory in China. Vadose Zone Journal, 17, 21, http://doi.org/10.2136/vzj2018.04.0072
[122] Wu, S.B., Wen, J.G*., You, D.Q., Hao,D.L., Lin, X.W., Xiao, Q., Liu, Q.H., & Gastellu-Etchegorry, J.P. (2018).Characterization of Remote sensing Albedo Over Sloped Surfaces Based on DARTSimulations and In Situ Observations. Journal of GeophysicalResearch-Atmospheres, 123, 8599-8622, http://doi.org/10.1029/2018jd028283
[123] Wu, S.B., Wen, J.G*., You, D.Q.,Zhang, H.L., Xiao, Q., & Liu, Q.H. (2018). Algorithms for CalculatingTopographic Parameters and Their Uncertainties in Downward Surface SolarRadiation (DSSR) Estimation. Ieee Geoscience and Remote Sensing Letters, 15,1149-1153, http://doi.org/10.1109/lgrs.2018.2831916
[124] Wu, J.J., Gao, Z.H., Liu, Q.H., Li, Z.Y*.,& Zhong, B. (2018). Methods for sandy land detection based on multispectralremote sensing data. Geoderma, 316, 89-99, http://doi.org/10.1016/j.geoderma.2017.12.015
[125] Zhao, J., Li, J*., Liu, Q.H., Yang,L., & Bai, J.H. (2018). A method of analyzing LAI underestimation for densevegetation based on the vertical distribution of the leaf area density. RemoteSensing Letters, 9, 121-130, http://doi.org/10.1080/2150704x.2017.1399471
[126] Wang, C., Li, J*., Liu, Q.H*.,Zhong, B., Wu, S.L., & Xia, C.F. (2017). Analysis of Differences inPhenology Extracted from the Enhanced Vegetation Index and the Leaf Area Index.Sensors, 17, 16, http://doi.org/10.3390/s17091982
[127] Bian, Z.J., Du, Y.M*., Li, H., Cao,B.A., Huang, H.G., Xiao, Q., & Liu, Q.H*. (2017). Modeling theTemporal Variability of Thermal Emissions From Row-Planted Scenes Using aRadiosity and Energy Budget Method. Ieee Transactions on Geoscience and RemoteSensing, 55, 6010-6026, http://doi.org/10.1109/tgrs.2017.2719098
[128] Li, X.J., Xin, X.Z*., Peng, Z.Q.,Zhang, H.L., Li, L., Shao, S.S., & Liu, Q.H. (2017). Estimation of landsurface heat fluxes based on visible infrared imaging radiometer suite data:case study in northern China. Journal of Applied Remote Sensing, 11, 15, http://doi.org/10.1117/1.Jrs.11.046012
[129] Zhang, Y., Liu, Q.H*., Tan, L.F.,Huang, H.G., Ni, W.J., Yin, T.G., Qin, W.H., & Sun, G.Q. (2017). A 3-DJoint Simulation Platform for Multiband Remote Sensing. Ieee Journal ofSelected Topics in Applied Earth Observations and Remote Sensing, 10,4763-4778, http://doi.org/10.1109/jstars.2017.2750223
[130] Zhong, B*, Chen, W.H., Wu, S.L., Hu, L.F., Luo, X.B., & Liu,Q.H. (2017). A Cloud Detection Method Based on Relationship Between Objects ofCloud and Cloud-Shadow for Chinese Moderate to High Resolution SatelliteImagery. Ieee Journal of Selected Topics in Applied Earth Observations andRemote Sensing, 10, 4898-4908, http://doi.org/10.1109/jstars.2017.2734912
[131] Yang, A.X., Zhong, B*., Wu, S.L.,& Liu, Q.H*. (2017). Radiometric Cross-Calibration of GF-4 inMultispectral Bands. Remote Sensing, 9, 17, http://doi.org/10.3390/rs9030232
[132] Huang, H.G*., Qin, W.H., Spurr, R.J.D., & Liu, Q.H. (2017).Evaluation of Atmospheric Effects on Land-Surface Directional Reflectance Withthe Coupled RAPID and VLIDORT Models. Ieee Geoscience and Remote SensingLetters, 14, 916-920, http://doi.org/10.1109/lgrs.2017.2687702
[133] Zhong, B*., Wu, S.L., Yang, A.X., & Liu, Q.H. (2017). AnImproved Aerosol Optical Depth Retrieval Algorithm for Moderate to High SpatialResolution Optical Remotely Sensed Imagery. Remote Sensing, 9, 16, http://doi.org/10.3390/rs9060555
[134] Yang, A.X., Zhong, B*., Wu, S.L.,& Liu, Q.H*. (2017). Evaluation on Radiometric Capability of ChineseOptical Satellite Sensors. Sensors, 17, 20, http://doi.org/10.3390/s17010204
[135] Wen, J.G., Dou, B.C., You, D.Q., Tang, Y., Xiao,Q*., Liu, Q., & Qinhuo, L. (2017). Forward a Small-TimescaleBRDF/Albedo by Multisensor Combined BRDF Inversion Model. Ieee Transactions onGeoscience and Remote Sensing, 55, 683-697, http://doi.org/10.1109/tgrs.2016.2613899
[136] Bian, Z.J., Cao, B., Li, H., Du, Y.M*.,Song, L.S., Fan, W.J., Xiao, Q., & Liu, Q.H*. (2017). A RobustInversion Algorithm for Surface Leaf and Soil Temperatures Using the VegetationClumping Index. Remote Sensing, 9, 16, http://doi.org/10.3390/rs9080780
[137] Hu, T., Cao, B*., Du, Y.M., Li, H.,Wang, C., Bian, Z.J., Sun, D.L., & Liu, Q.H*. (2017). Estimation ofSurface Upward Longwave Radiation Using a Direct Physical Algorithm. IeeeTransactions on Geoscience and Remote Sensing, 55, 4412-4426, http://doi.org/10.1109/tgrs.2017.2692261
[138] Li, X.J., Xin, X.Z*., Jiao, J.J.,Peng, Z.Q., Zhang, H.L., Shao, S.S., & Liu, Q.H. (2017). EstimatingSubpixel Surface Heat Fluxes through Applying Temperature-Sharpening Methods toMODIS Data. Remote Sensing, 9, 30, http://doi.org/10.3390/rs9080836
[139] Wang, Q.X., Sun, L.*, Wei, J., Yang,Y.K., Li, R.B., Liu, Q.H., & Chen, L.F. (2017). Validation and AccuracyAnalysis of Global MODIS Aerosol Products over Land. Atmosphere, 8, 17, http://doi.org/10.3390/atmos8080155
[140] Wu, X.D., Wen, J.G*., Xiao, Q., Liu,Q., Peng, J.J., Dou, B.C., Li, X.H., You, D.Q., Tang, Y., & Liu, Q.H.(2016). Coarse scale in situ albedo observations over heterogeneous snow-freeland surfaces and validation strategy: A case of MODIS albedo productspreliminary validation over northern China. Remote Sensing of Environment, 184,25-39, http://doi.org/10.1016/j.rse.2016.06.013
[141] Hu, T., Du, Y.M*., Cao, B., Li, H.,Bian, Z.J., Sun, D.L., & Liu, Q.H*. (2016). Estimation of UpwardLongwave Radiation From Vegetated Surfaces Considering Thermal Directionality.Ieee Transactions on Geoscience and Remote Sensing, 54, 6644-6658, http://doi.org/10.1109/tgrs.2016.2587695
[142] Peng, Z.Q., Xin, X.Z*., Jiao, J.J.,Zhou, T., & Liu, Q.H. (2016). Remote sensing algorithm for surfaceevapotranspiration considering landscape and statistical effects on mixedpixels. Hydrology and Earth System Sciences, 20, 4409-4438, http://doi.org/10.5194/hess-20-4409-2016
[143] Zeng, Y.L., Li, J*., Liu, Q.H*.,Huete, A.R., Xu, B.D., Yin, G.F., Zhao, J., Yang, L., Fan, W.L., Wu, S.B.,& Yan, K. (2016). An Iterative BRDF/NDVI Inversion Algorithm Based on APosteriori Variance Estimation of Observation Errors. Ieee Transactions onGeoscience and Remote Sensing, 54, 6481-6496, http://doi.org/10.1109/tgrs.2016.2585301
[144] Xu, B.D., Li, J*., Liu, Q.H*, Huete,A.R., Yu, Q., Zeng, Y.L., Yin, G.F., Zhao, J., & Yang, L. (2016).Evaluating Spatial Representativeness of Station Observations for RemotelySensed Leaf Area Index Products. Ieee Journal of Selected Topics in AppliedEarth Observations and Remote Sensing, 9, 3267-3282, http://doi.org/10.1109/jstars.2016.2560878
[145] Guo, Y.H*., Zhong, B., & Liu, Q.H. (2016). Efficientstripmap-mode synthetic aperture radar raw data generation accounting fortrajectory deviation with a nonzero squint angle. Journal of Applied RemoteSensing, 10, 12, http://doi.org/10.1117/1.Jrs.10.044002
[146] Wang, S.G., Li, X*., Ge, Y., Jin, R.,Ma, M.G., Liu, Q.H., Wen, J.G., & Liu, S.M. (2016). Validation ofRegional-Scale Remote Sensing Products in China: From Site to Network. RemoteSensing, 8, 26, http://doi.org/10.3390/rs8120980
[147] Zhang, Y., Liu, Q.H*., Du, Y., Yang,L., Du, Y.M., Cao, B., & Tan, L.F. (2016). Convenient Measurement andModified Model for Broadleaf Permittivity. Ieee Transactions on Geoscience andRemote Sensing, 54, 6986-6996, http://doi.org/10.1109/tgrs.2016.2593798
[148] Bian, Z.J., Xiao, Q*., Cao, B., Du, Y.M*.,Li, H., Wang, H.S., Liu, Q.H., & Liu, Q. (2016). Retrieval of Leaf, SunlitSoil, and Shaded Soil Component Temperatures Using Airborne Thermal InfraredMultiangle Observations. Ieee Transactions on Geoscience and Remote Sensing,54, 4660-4671, http://doi.org/10.1109/tgrs.2016.2547961
[149] Yang, C., Shi, J.C., Liu, Q.H., & Du,Y*. (2016). Scattering From Inhomogeneous Dielectric Cylinders With FiniteLength. Ieee Transactions on Geoscience and Remote Sensing, 54, 4555-4569, http://doi.org/10.1109/tgrs.2016.2544379
[150] Yin, G.F., Li, J*., Liu, Q.H*., Zhong,B., & Li, A.N. (2016). Improving LAI spatio-temporal continuity using acombination of MODIS and MERSI data. Remote Sensing Letters, 7, 771-780, http://doi.org/10.1080/2150704x.2016.1182657
[151] Zeng, Y.L., Li, J*., Liu, Q.H*.,Huete, A.R., Yin, G.F., Xu, B.D., Fan, W.L., Zhao, J., Yan, K., & Mu, X.H.(2016). A Radiative Transfer Model for Heterogeneous Agro-Forestry Scenarios.Ieee Transactions on Geoscience and Remote Sensing, 54, 4613-4628, http://doi.org/10.1109/tgrs.2016.2547326
[152] Cao, B., Du, Y.M*., Li, J., Li, H.,Li, L., Zhang, Y., Zou, J., & Liu, Q.H*. (2015). Comparison of FiveSlope Correction Methods for Leaf Area Index Estimation From HemisphericalPhotography. Ieee Geoscience and Remote Sensing Letters, 12, 1958-1962, http://doi.org/10.1109/lgrs.2015.2440438
[153] Tian, X., Li, Z.Y*., Chen, E.X., Liu,Q.H., Yan, G.J., Wang, J.D., Niu, Z., Zhao, S.J., Li, X., Pang, Y., Su, Z.B.,van der Tol, C., Liu, Q.W., Wu, C.Y., Xiao, Q., Yang, L., Mu, X.H., Bo, Y.C.,Qu, Y.H., Zhou, H.M., Gao, S.H., Chai, L.N., Huang, H.G., Fan, W.J., Li, S.H.,Bai, J.H., Jiang, L.M., & Zhou, J. (2015). The Complicate Observations andMulti-Parameter Land Information Constructions on Allied Telemetry Experiment(COMPLICATE). Plos One, 10, 27, http://doi.org/10.1371/journal.pone.0137545
[154] Zeng, Y.L., Li, J*., Liu, Q.H*., Hu,R.H., Mu, X.H., Fan, W.L., Xu, B.D., Yin, G.F., & Wu, S.B. (2015).Extracting Leaf Area Index by Sunlit Foliage Component from Downward-LookingDigital Photography under Clear-Sky Conditions. Remote Sensing, 7, 13410-13435,http://doi.org/10.3390/rs71013410
[155] Zhong, B*., Yang, A.X., Nie, A.H., Yao, Y.J., Zhang, H., Wu, S.L.,& Liu, Q.H. (2015). Finer Resolution Land-Cover Mapping Using MultipleClassifiers and Multisource Remotely Sensed Data in the Heihe River Basin. IeeeJournal of Selected Topics in Applied Earth Observations and Remote Sensing, 8,4973-4992, http://doi.org/10.1109/jstars.2015.2461453
[156] Peng, J.J., Fan, W.J*., Xu, X.R.,Wang, L.Z., Liu, Q.H*., Li, J.C., & Zhao, P. (2015). Estimating CropAlbedo in the Application of a Physical Model Based on the Law of EnergyConservation and Spectral Invariants. Remote Sensing, 7, 15536-15560, http://doi.org/10.3390/rs71115536
[157] Hu, T., Liu, Q.H*., Du, Y.M*., Li, H.,Wang, H.S., & Cao, B. (2015). Analysis of the Land Surface TemperatureScaling Problem: A Case Study of Airborne and Satellite Data over the HeiheBasin. Remote Sensing, 7, 6489-6509, http://doi.org/10.3390/rs70506489
[158] Li, L., Du, Y.M., Tang, Y., Xin, X.Z., Zhang,H.L., Wen, J.G., & Liu, Q.H*. (2015). A New Algorithm of the FPARProduct in the Heihe River Basin Considering the Contributions of Direct andDiffuse Solar Radiation Separately. Remote Sensing, 7, 6414-6432, http://doi.org/10.3390/rs70506414
[159] Jiang, J.X., Li, H*., Liu, Q.H*.,Wang, H.S., Du, Y.M., Cao, B.A., Zhong, B., & Wu, S.L. (2015). Evaluationof Land Surface Temperature Retrieval from FY-3B/VIRR Data in an Arid Area ofNorthwestern China. Remote Sensing, 7, 7080-7104, http://doi.org/10.3390/rs70607080
[160] Peng, J.J., Liu, Q*., Wang, L.Z., Liu,Q.H., Fan, W.J*., Lu, M., & Wen, J.G. (2015). Characterizing thePixel Footprint of Satellite Albedo Products Derived from MODIS Reflectance inthe Heihe River Basin, China. Remote Sensing, 7, 6886-6907, http://doi.org/10.3390/rs70606886
[161] Sun, D.L*., Yu, Y.Y., Yang, H.Q., Fang, L., Liu, Q.H., & Shi,J.C. (2015). A case study for intercomparison of land surface temperatureretrieved from GOES and MODIS. International Journal of Digital Earth, 8,476-494, http://doi.org/10.1080/17538947.2014.906509
[162] You, D.Q., Wen, J.G*., Xiao, Q., Liu,Q., Liu, Q.H., Tang, Y., Dou, B.C., & Peng, J.J. (2015). Development of aHigh Resolution BRDF/Albedo Product by Fusing Airborne CASI Reflectance withMODIS Daily Reflectance in the Oasis Area of the Heihe River Basin, China.Remote Sensing, 7, 6784-6807, http://doi.org/10.3390/rs70606784
[163] Zhang, Y.L., Li, X*., Wen, J.G., Liu,Q.H., & Yan, G.J. (2015). Improved Topographic Normalization for Landsat TMImages by Introducing the MODIS Surface BRDF. Remote Sensing, 7, 6558-6575, http://doi.org/10.3390/rs70606558
[164] Zhao, J., Li, J*., Liu, Q.H*., Fan,W.J., Zhong, B., Wu, S.L., Yang, L., Zeng, Y.L., Xu, B.D., & Yin, G.F.(2015). Leaf Area Index Retrieval Combining HJ1/CCD and Landsat8/OLI Data inthe Heihe River Basin, China. Remote Sensing, 7, 6862-6885, http://doi.org/10.3390/rs70606862
[165] Cao, B., Liu, Q.H., Du, Y.M*., Li, H.,Wang, H.S., & Xiao, Q. (2015). Modeling Directional Brightness TemperatureOver Mixed Scenes of Continuous Crop and Road: A Case Study of the Heihe RiverBasin. Ieee Geoscience and Remote Sensing Letters, 12, 234-238, http://doi.org/10.1109/lgrs.2014.2333874
[166] Wang, H.S., Xiao, Q*., Li, H., Du,Y.M., & Liu, Q.H. (2015). Investigating the Impact of Soil Moisture onThermal Infrared Emissivity Using ASTER Data. Ieee Geoscience and RemoteSensing Letters, 12, 294-298, http://doi.org/10.1109/lgrs.2014.2336912
[167] Yang, L., Liu, Q.H*., Zhao, J., &Bao, L.F. (2015). Global Land Surface Backscatter at Ku-Band Using MergedJason1, Envisat, and Jason2 Data Sets. Ieee Transactions on Geoscience andRemote Sensing, 53, 784-794, http://doi.org/10.1109/tgrs.2014.2328616
[168] Yin, G.F., Li, J*., Liu, Q.H*., Li,L.H., Zeng, Y.L., Xu, B.D., Yang, L., & Zhao, J. (2015). Improving LeafArea Index Retrieval Over Heterogeneous Surface by Integrating Textural andContextual Information: A Case Study in the Heihe River Basin. Ieee Geoscienceand Remote Sensing Letters, 12, 359-363, http://doi.org/10.1109/lgrs.2014.2341925
[169] Zeng, Y.L., Li, J*., Liu, Q.H*., Qu,Y.H., Huete, A.R., Xu, B.D., Yin, G.F., & Zhao, J. (2015). An OptimalSampling Design for Observing and Validating Long-Term Leaf Area Index withTemporal Variations in Spatial Heterogeneities. Remote Sensing, 7, 1300-1319, http://doi.org/10.3390/rs70201300
[170] Zhang, H.L., Xin, X.Z*., Li, L., &Liu, Q.H. (2015). Estimating global solar radiation using a hybrid parametricmodel from MODIS data over the Tibetan Plateau. Solar Energy, 112, 373-382, http://doi.org/10.1016/j.solener.2014.12.015
[171] Li, L., Xin, X.Z*., Zhang, H.L., Yu,J.F., Liu, Q.H., Yu, S.S., & Wen, J.G. (2015). A method for estimatinghourly photosynthetically active radiation (PAR) in China by combininggeostationary and polar-orbiting satellite data. Remote Sensing of Environment,165, 14-26, http://doi.org/10.1016/j.rse.2015.03.034
[172] Yang, A.X., Zhong, B*., Lv, W.B., Wu,S.L., & Liu, Q.H. (2015). Cross-Calibration of GF-1/WFV over a Desert SiteUsing Landsat-8/OLI Imagery and ZY-3/TLC Data. Remote Sensing, 7, 10763-10787, http://doi.org/10.3390/rs70810763
[173] Fan, W.L., Li, J., & Liu, Q.H*.(2015). GOST2: The Improvement of the Canopy Reflectance Model GOST inSeparating the Sunlit and Shaded Leaves. Ieee Journal of Selected Topics inApplied Earth Observations and Remote Sensing, 8, 1423-1431, http://doi.org/10.1109/jstars.2015.2413994
[174] Peng, J.J., Liu, Q*., Wen, J.G., Liu,Q.H., Tang, Y., Wang, L.Z., Dou, B.C., You, D.Q., Sun, C.K., Zhao, X.J., Feng,Y.B., & Shi, J. (2015). Multi-scale validation strategy for satellite albedoproducts and its uncertainty analysis. Science China-Earth Sciences, 58,573-588, http://doi.org/10.1007/s11430-014-4997-y
[175] Wen, J.G., Liu, Q., Tang, Y., Dou, B.C., You,D.Q., Xiao, Q*., Liu, Q.H., & Li, X.W. (2015). Modeling Land SurfaceReflectance Coupled BRDF for HJ-1/CCD Data of Rugged Terrain in Heihe RiverBasin, China. Ieee Journal of Selected Topics in Applied Earth Observations andRemote Sensing, 8, 1506-1518, http://doi.org/10.1109/jstars.2015.2416254
[176] Yin, G.F., Li, J*., Liu, Q.H*., Fan,W.L., Xu, B.D., Zeng, Y.L., & Zhao, J. (2015). Regional Leaf Area IndexRetrieval Based on Remote Sensing: The Role of Radiative Transfer ModelSelection. Remote Sensing, 7, 4604-4625, http://doi.org/10.3390/rs70404604
[177] Cao, B.A., Du, Y.M*., Xu, D.Q., Li,H., & Liu, Q.H. (2015). An improved histogram matching algorithm for theremoval of striping noise in optical remote sensing imagery. Optik, 126,4723-4730, http://doi.org/10.1016/j.ijleo.2015.08.079
[178] Zhong, B*., Zhang, Y.H., Du, T.T., Yang, A.X., Lv, W.B., & Liu,Q.H*. (2014). Cross-Calibration of HJ-1/CCD Over a Desert Site UsingLandsat ETM plus Imagery and ASTER GDEM Product. Ieee Transactions onGeoscience and Remote Sensing, 52, 7247-7263, http://doi.org/10.1109/tgrs.2014.2310233
[179] Zeng, Y.L., Li, J*., Liu, Q.H*., Li,L.H., Xu, B.D., Yin, G.F., & Peng, J.J. (2014). A Sampling Strategy forRemotely Sensed LAI Product Validation Over Heterogeneous Land Surfaces. IeeeJournal of Selected Topics in Applied Earth Observations and Remote Sensing, 7,3128-3142, http://doi.org/10.1109/jstars.2014.2312231
[180] Li, H., Sun, D.L., Yu, Y.Y., Wang, H.Y., Liu,Y.L., Liu, Q.H*., Du, Y.M., Wang, H.S., & Cao, B.A. (2014).Evaluation of the VIIRS and MODIS LST products in an arid area of NorthwestChina. Remote Sensing of Environment, 142, 111-121, http://doi.org/10.1016/j.rse.2013.11.014
[181] Zhong, B*., Ma, P., Nie, A.H., Yang, A.X., Yao, Y.J., Lü, W.B.,Zhang, H., & Liu, Q.H. (2014). Land cover mapping using time seriesHJ-1/CCD data. Science China-Earth Sciences, 57, 1790-1799, http://doi.org/10.1007/s11430-014-4877-5
[182] You, D.Q., Wen, J.G*., Liu, Q., Liu,Q.H., & Tang, Y. (2014). The Angular and Spectral Kernel-Driven Model:Assessment and Application. Ieee Journal of Selected Topics in Applied EarthObservations and Remote Sensing, 7, 1331-1345, http://doi.org/10.1109/jstars.2013.2271502
[183] Huang, H.G*., Qin, W.H., & Liu, Q.H. (2013). RAPID: A RadiosityApplicable to Porous Individual Objects for directional reflectance over complexvegetated scenes. Remote Sensing of Environment, 132, 221-237, http://doi.org/10.1016/j.rse.2013.01.013
[184] Sun, D.L*., Yu, Y.Y., Yang, H.Q., Liu, Q.H., & Shi, J.C.(2013). Comparison Between GOES-East and - West for Land Surface TemperatureRetrieval From a Dual-Window Algorithm. Ieee Geoscience and Remote SensingLetters, 10, 578-582, http://doi.org/10.1109/lgrs.2012.2214473
[185] Yu, S.S., Xin, X.Z*., & Liu, Q.H.(2013). Estimation of clear-sky longwave downward radiation from HJ-1B thermaldata. Science China-Earth Sciences, 56, 829-842, http://doi.org/10.1007/s11430-012-4507-z
[186] Li, H., Liu, Q.H*., Du, Y.M., Jiang,J.X., & Wang, H.S. (2013). Evaluation of the NCEP and MODIS AtmosphericProducts for Single Channel Land Surface Temperature Retrieval With GroundMeasurements: A Case Study of HJ-1B IRS Data. Ieee Journal of Selected Topicsin Applied Earth Observations and Remote Sensing, 6, 1399-1408, http://doi.org/10.1109/jstars.2013.2255118
[187] Zhang, H.L., Xin, X.Z*., Li, L., &Liu, Q.H. (2013). An Improved Parametric Model for Simulating Cloudy Sky DailyDirect Solar Radiation on Tilted Surfaces. Ieee Journal of Selected Topics inApplied Earth Observations and Remote Sensing, 6, 180-187, http://doi.org/10.1109/jstars.2012.2211000
[188] Li, X*., Cheng, G.D., Liu, S.M., Xiao, Q., Ma, M.G., Jin, R.,Che, T., Liu, Q.H., Wang, W.Z., Qi, Y., Wen, J.G., Li, H.Y., Zhu, G.F., Guo,J.W., Ran, Y.H., Wang, S.G., Zhu, Z.L., Zhou, J., Hu, X.L., & Xu, Z.W.(2013). Heihe Watershed Allied Telemetry Experimental Research (HiWATER):Scientific Objectives and Experimental Design. Bulletin of the AmericanMeteorological Society, 94, 1145-1160, http://doi.org/10.1175/bams-d-12-00154.1
[189] Yao, Y.J*., Liu, Q., Liu, Q.H., & Gao, Y.H. (2012). Optimisingview angles for the estimation of leaf area index via entropy-differenceanalysis. Journal of Earth System Science, 121, 687-695, http://doi.org/10.1007/s12040-012-0178-6
[190] Zhang, Z.J*., Zhang, L.X., Sun, G.Q., & Liu, Q.H. (2012). Amethod to estimate crop effects at higher frequencies by modeling and microwaveradiometric data. Science China-Earth Sciences, 55, 1159-1165, http://doi.org/10.1007/s11430-012-4410-7
[191] Bai, J.H*., Li, J., Liu, Q.H., Wang, X., & Li, S.K. (2012).Diagnosing Cotton Farmland Quality Using Multi-Temporal Remotely Sensed Data.Sensor Letters, 10, 475-483, http://doi.org/10.1166/sl.2012.1869
[192] Huang, H.G*., Liu, Q., Liu, Q.H., & Qin, W.H. (2012). Validatingtheoretical simulations of thermal emission hot spot effects on maize canopies.International Journal of Remote Sensing, 33, 746-761, http://doi.org/10.1080/01431161.2011.577827
[193] Yang, L*., Lin, M.S., Liu, Q.H., & Pan, D.L. (2012). Acoastal altimetry retracking strategy based on waveform classification andsub-waveform extraction. International Journal of Remote Sensing, 33,7806-7819, http://doi.org/10.1080/01431161.2012.701350
[194] Huang, H.G*., Liu, Q.H., Qin, W.H., Du, Y.M., & Li, X.W. (2011).Temporal patterns of thermal emission directionality of crop canopies. Journalof Geophysical Research-Atmospheres, 116, 18, http://doi.org/10.1029/2010jd014613
[195] Ma, R.H., Duan, H.T*., Liu, Q.H.,& Loiselle, S.A. (2011). Approximate bottom contribution to remote sensingreflectance in Taihu Lake, China. Journal of Great Lakes Research, 37, 18-25, http://doi.org/10.1016/j.jglr.2010.12.002
[196] Cheng, J*., Liang, S.L., Liu, Q.H., & Li, X.W. (2011).Temperature and Emissivity Separation From Ground-Based MIR Hyperspectral Data.Ieee Transactions on Geoscience and Remote Sensing, 49, 1473-1484, http://doi.org/10.1109/tgrs.2010.2076818
[197] Bao, Y.F*., Chen, S.B*., Liu, Q.H., Xiao, Q., & Cao, C.X.(2011). Land surface temperature and emissivity retrieval by integrating MODISdata onboard Terra and Aqua satellites. International Journal of Remote Sensing,32, 1449-1469, http://doi.org/10.1080/01431160903559754
[198] Huang, H.G*., Liu, Q.H., & Qin, W.H. (2010). Thermal EmissionHot-Spot Effect of Crop Canopies-Part I: Simulation. Ieee Journal of SelectedTopics in Applied Earth Observations and Remote Sensing, 3, 313-322, http://doi.org/10.1109/jstars.2010.2046625
[199] Liu, S.H., Liu, Q.A., Liu, Q.H*., Wen,J.G., & Li, X.W. (2010). The Angular and Spectral Kernel Model for BRDF andAlbedo Retrieval. Ieee Journal of Selected Topics in Applied Earth Observationsand Remote Sensing, 3, 241-256, http://doi.org/10.1109/jstars.2010.2048745
[200] Li, L., Xin, X.Z., Su, G.L., & Liu,Q.H*. (2010). Photosynthetically active radiation retrieval based onHJ-1A/B satellite data. Science China-Earth Sciences, 53, 81-91, http://doi.org/10.1007/s11430-010-4142-5
[201] Sun, L., Sun, C.K., Liu, Q.H*., &Zhong, B. (2010). Aerosol optical depth retrieval by HJ-1/CCD supported byMODIS surface reflectance data. Science China-Earth Sciences, 53, 74-80, http://doi.org/10.1007/s11430-010-4134-5
[202] Li, X*., Li, X.W., Li, Z.Y., Ma, M.G., Wang, J., Xiao, Q., Liu,Q., Che, T., Chen, E.X., Yan, G.J., Hu, Z.Y., Zhang, L.X., Chu, R.Z., Su, P.X.,Liu, Q.H., Liu, S.M., Wang, J.D., Niu, Z., Chen, Y., Jin, R., Wang, W.Z., Ran,Y.H., Xin, X.Z., & Ren, H.Z. (2009). Watershed Allied TelemetryExperimental Research. Journal of Geophysical Research-Atmospheres, 114, 19, http://doi.org/10.1029/2008jd011590
[203] Huang, H.G*., Chen, M., Liu, Q.H., Liu, Q., Zhang, Y., Zhao, L.Q.,& Qin, W.H. (2009). A realistic structure model for large-scale surfaceleaving radiance simulation of forest canopy and accuracy assessment.International Journal of Remote Sensing, 30, 5421-5439, http://doi.org/10.1080/01431160903130911
[204] Wen, J.G*., Liu, Q., Liu, Q.H., Xiao, Q., & Li, X.W. (2009).Scale effect and scale correction of land-surface albedo in rugged terrain.International Journal of Remote Sensing, 30, 5397-5420, http://doi.org/10.1080/01431160903130903
[205] Wen, J.G*., Liu, Q.H., Liu, Q., Xiao, Q., & Li, X.W. (2009).Parametrized BRDF for atmospheric and topographic correction and albedoestimation in Jiangxi rugged terrain, China. International Journal of RemoteSensing, 30, 2875-2896, http://doi.org/10.1080/01431160802558618
[206] Yang, G.J*., Liu, Q.H., Liu, Q., Huang, W.J., & Wang, J.H.(2009). Simulation of high-resolution mid-infrared (3-5 μm) images using anatmosphere radiative transfer analytic model. International Journal of RemoteSensing, 30, 6003-6022, http://doi.org/10.1080/01431160902798403
[207] Chen, L.F*., Gao, Y.H., Li, L., Liu, Q.H., & Gu, X.F. (2008).Forest NPP estimation based on MODIS data under cloudless condition. Science inChina Series D-Earth Sciences, 51, 331-338, http://doi.org/10.1007/s11430-008-0013-8
[208] Cheng, J*., Liu, Q.H., Li, X.W., Xiao, Q., Liu, Q., & Du, Y.M.(2008). Correlation-based temperature and emissivity separation algorithm.Science in China Series D-Earth Sciences, 51, 357-369, http://doi.org/10.1007/s11430-008-0022-7
[209] Yao, Y.J., Liu, Q.H*., Liu, Q., &Li, X.W. (2008). LAI retrieval and uncertainty evaluations for typicalrow-planted crops at different growth stages. Remote Sensing of Environment,112, 94-106, http://doi.org/10.1016/j.rse.2006.09.037
[210] Wen, J.G*., Liu, Q.H., Xiao, Q., Liu, Q., & Li, X.W. (2008).Modeling the land surface reflectance for optical remote sensing data in ruggedterrain. Science in China Series D-Earth Sciences, 51, 1169-1178, http://doi.org/10.1007/s11430-008-0085-5
[211] Chen, L.F*., Gao, Y.H., Yang, L., Liu, Q.H., Go, X.F., & Tian,G.L. (2008). MODIS-derived daily PAR simulation from cloud-free images and itsvalidation. Solar Energy, 82, 528-534, http://doi.org/10.1016/j.solener.2007.12.001
[212] Liu, Q.H*., Huang, H.G., Qin, W.H., Fu, K.H., & Li, X.W.(2007). An extended 3-D radiosity-graphics combined model for studyingthermal-emission directionality of crop canopy. Ieee Transactions on Geoscienceand Remote Sensing, 45, 2900-2918, http://doi.org/10.1109/tgrs.2007.902272
[213] Sun, G.Y., Liu, Q.H*., Liu, Q., Ji,C.Y.Y., & Li, X.M. (2007). A novel approach for edge detection based on thetheory of universal gravity. Pattern Recognition, 40, 2766-2775, http://doi.org/10.1016/j.patcog.2007.01.006
[214] Du, Y.M., Liu, Q.H., Chen, L.F., Liu, Q.A.,& Yu, T. (2007). Modeling directional brightness temperature of the winterwheat canopy at the ear stage. Ieee Transactions on Geoscience and RemoteSensing, 45, 3721-3739, http://doi.org/10.1109/tgrs.2007.903401
[215] Xin, J.F*., Tian, G.L., Liu, Q.H., & Chen, L.F. (2006).Combining vegetation index and remotely sensed temperature for estimation ofsoil moisture in China. International Journal of Remote Sensing, 27, 2071-2075,http://doi.org/10.1080/01431160500497549
[216] Chen, L.F., Gao, Y.H., Cheng, Y., Wei, Z.,Xiao, Q., Liu, X.H., Yu, T., Liu, Q.J., Gu, X.F., & Tian, G.L. (2005). Biomassestimation and uncertainty analysis based on CBERS-02 CCD camera data and fieldmeasurement. Science in China Series E-Technological Sciences, 48, 116-128, http://doi.org/10.1360/05ze1011
[217] Li, J., Liu, Q.H., Liu, Q., Chen, L.F., Bo,J.H., & Li, S.K. (2005). Cotton pixel identification with CBERS-02 CCD databased on spectral knowledge. Science in China Series E-Technological Sciences,48, 129-144, http://doi.org/10.1360/05ze1013
[218] Xin, X.Z., Liu, X.H., Tang, Y., Tian, G.L.,Gu, X.F., Li, X.W., Zheng, H.S., & Chen, J.Y. (2005). Estimating surfaceevapotranspiration using combined MODIS and CBERS-02 data. Science in ChinaSeries E-Engineering & Materials Science, 48, 145-160, http://doi.org/10.1360/05ye0014
[219] Chen, S.S*., Chen, L.F., Liu, Q.H., Li, X., & Tan, Q.Y. (2005).Remote sensing and GIS-based integrated analvsis of coastal changes and theirenvironmental impacts in Lingding Bay, Pearl River Estuary, South China. Ocean& Coastal Management, 48, 65-83, http://doi.org/10.1016/j.ocecoaman.2004.11.004
[220] Chen, L.F*., Li, Z.L., Liu, Q.H., Chen, S., Tang, Y., & Zhong,B. (2004). Definition of component effective emissivity for heterogeneous andnon-isothermal surfaces and its approximate calculation. International Journalof Remote Sensing, 25, 231-244, http://doi.org/10.1080/0143116031000116426
[221] Deng, R.R*., Liu, Q.H., Ke, R.P., Cheng, L., & Liu, X.P.(2004). Model for water pollution remote sensing based on double scattering andits application in the Zhujiang River outfall. Acta Oceanologica Sinica, 23,119-127
[222] Xiao, Q., Liu, Q.H., Li, X.W., Chen, L.F.,Liu, Q., & Xin, X.Z. (2003). A field measurement method of spectralemissivity and research on the feature of soil thermal infrared emissivity.Journal of Infrared and Millimeter Waves, 22, 373-378
[223] Chen, L.F*., Liu, Q.H., Fan, W.J., Li, X.W., Xiao, Q., Yan, G.J.,& Tian, G.L. (2002). A bi-directional gap model for simulating thedirectional thermal radiance of row crops. Science in China Series D-Earth Sciences,45, 1087-1098, http://doi.org/10.1360/02yd9106
[224] Liu, Q.A*., Liu, Q.H., Xiao, Q., & Tian, G.L. (2002). Study ongeometric correction of airborne multiangular imagery. Science in China SeriesD-Earth Sciences, 45, 1075-1086, http://doi.org/10.1360/02yd9105
[225] Ji, C.Y., Liu, Q.H., Sun, D.F., Wang, S.,Lin, P., & Li, X.W. (2001). Monitoring urban expansion with remote sensingin China. International Journal of Remote Sensing, 22, 1441-1455, http://doi.org/10.1080/01431160117207
[226] Chen, L.F*., Zhuang, J.L., Liu, Q.H., Xu, X.R., & Tian, G.L.(2000). Study on the law of radiant directionality of row crops. Science inChina Series E-Technological Sciences, 43, 70-82, http://doi.org/10.1007/bf02916581
[227] Liu, Q.H*., Gu, X.F., Li, X.W., Jacob, F., Hanocq, J.F., Friedl,M., Strahler, A.H., Yu, T., & Tian, G.L. (2000). Study on thermal infraredemission directionality over crop canopies with TIR camera imagery. Science inChina Series E-Technological Sciences, 43, 95-103, http://doi.org/10.1007/bf02916583
[228] Niu, Z*., Liu, Q.H., Gao, Y.C., Zhang, Q.Y., & Wang, C.Y.(2000). The gap probability model for canopy thermal infrared emission withnon-scattering approximation. Science in China Series E-Technological Sciences,43, 83-94, http://doi.org/10.1007/bf02916582
[229] Xu, X.R., Liu, Q.H., & Chen, J.Y. (1998).Synchronous retrieval of land surface temperature and emissivity. Science inChina Series D-Earth Sciences, 41, 658-668, http://doi.org/10.1007/bf02878749
2.专著（参与编写）
（1）王琦安，柳钦火等，全球生态环境j9游会真人游戏第一品牌监测2021年度报告：全球陆域生态系统可持续发展态势，测绘出版社，2022年06月。
（2）王琦安，柳钦火等，全球生态环境j9游会真人游戏第一品牌监测2021年度报告：欧亚大陆草原生态状况，测绘出版社，2022年06月。
（3）王琦安，柳钦火等，全球生态环境j9游会真人游戏第一品牌监测2021年度报告：全球大宗粮油作物生产与粮食安全形势，测绘出版社，2022年06月。
（4）王琦安，柳钦火等，全球生态环境j9游会真人游戏第一品牌监测2021年度报告：全球典型湖泊生态环境状况,，测绘出版社，2022年06月。
（5）柳钦火，吴俊君，仲波，李静，辛晓洲，贾立等，“一带一路”东南亚区生态环境j9游会真人游戏第一品牌监测，科学出版社，2019年4月。
（6）辛晓洲，张海龙，余珊珊，李丽，柳钦火等，地表辐射收支j9游会真人游戏第一品牌方法与技术，科学出版社，2019年1月。
（7）仲波，李宏益，柳钦火，唐娉，辛晓州，李静等，多源协同陆表定量j9游会真人游戏第一品牌产品生产技术与系统，北京：科学出版社，2018年9月。
（8）闻建光，刘强，柳钦火，肖青，李小文，陆表二向反射特性j9游会真人游戏第一品牌建模及反照率反演, 科学出版社，2015。
（9）仲波，柳钦火，单小军，穆西晗，多源光学j9游会真人游戏第一品牌数据归一化处理技术与方法，科学出版社，2015。
（10）田国良、柳钦火、陈良富等，热红外j9游会真人游戏第一品牌（第二版），电子工业出版社，2014。
（11）柳钦火, 仲波, 吴纪桃, 肖志强, 王桥，环境j9游会真人游戏第一品牌定量反演与同化，中国科学出版社, 2011。
（12）柳钦火、辛晓洲、唐娉、廖静娟、吴炳方等，定量j9游会真人游戏第一品牌模型、应用及不确定性研究，科学出版社，2010。
（13）王锦地、张立新、柳钦火、张兵、尹球等，中国典型地物波谱知识库，科学出版社，2009。
（14）田国良、柳钦火、陈良富、余涛、刘强、辛晓洲等，红外j9游会真人游戏第一品牌，电子工业出版社，2006。
（15）李小文、汪骏发、王锦地、柳钦火，多角度与热红外对地j9游会真人游戏第一品牌, 科学出版社，2001。
3.专利授权
（1）秦伯雄; 曹彪; 陈水森; 李丹; 杜永明; 历华; 肖青; 柳钦火，一种纠正静止卫星地表温度产品热辐射方向性的方法，发明，授权号：CN115952697B，2023.06.06（发明专利权授予）
（2）卞尊健; 李嘉昕; 范腾远; 曹彪; 历华; 杜永明; 肖青; 柳钦火，一种三维复杂地表叶面积指数反演方法及系统，发明，授权号：CN113505486B，2023.12.29（发明专利权授予）
（3）卞尊健; 范腾远; 李嘉昕; 曹彪; 历华; 杜永明; 肖青; 柳钦火，一种三维复杂地表j9游会真人游戏第一品牌光学特征反演方法及系统，发明，授权号：CN113516767B，2023.12.29（发明专利权授予）
（4）柏军华; 柳钦火; 肖青; 刘学; 曹彪; 杨建，定量j9游会真人游戏第一品牌地面试验协同观测方法及观测平台，发明，授权号：CN112857459B，2022.06.07（发明专利权授予）
（5）卞尊健; 李嘉昕; 范腾远; 曹彪; 历华; 杜永明; 肖青; 柳钦火，基于辐射度的地表高分辨率光谱信息j9游会真人游戏第一品牌反演方法，发明，授权号：CN113012276B，2021.09.24（发明专利权授予）
（6）曹彪; 秦伯雄; 杜永明; 卞尊健; 历华; 肖青; 柳钦火，纠正静止卫星地表上行长波辐射产品热辐射方向性的方法，发明，授权号：CN112985607B，2021.09.24（发明专利权授予）
（7）柏军华; 柳钦火; 肖青; 李静; 张召星，一种适用于野外连续观测的植被株高自动测定方法及系统，发明，授权号：CN112595243B，2022.05.17（发明专利权授予）
（8）柏军华; 杜永明; 肖青; 柳钦火; 张召星，一种持续自动模拟植被生长状态的方法及系统，发明，授权号：CN112632752B，2024.02.09（发明专利权授予）
（9）卞尊健; 杜永明; 历华; 曹彪; 肖青; 柳钦火，一种离散森林场景热红外辐射传输模拟方法，发明，授权号：CN112254820B，2021.04.27（发明专利权授予）
（10）曹彪; 杜永明; 卞尊健; 历华; 肖青; 柳钦火，一种高精度的热辐射方向性半经验半物理模拟方法，发明，授权号：CN112198814B，2021.09.10（发明专利权授予）
（11）卞尊健; 历华; 杜永明; 曹彪; 肖青; 柳钦火，基于贝叶斯模型平均方法的地表组分温度多算法集成算法，发明，授权号：CN112199634B，2021.05.11（发明专利权授予）
（12）杜永明; 秦伯雄; 曹彪; 历华; 卞尊健; 肖青; 柳钦火，一种小面元黑体扩束定标方法及系统，发明，授权号：CN112129420B，2021.06.15（发明专利权授予）
（13）辛晓洲; 彭志晴; 柳钦火，一种用于地表变量的非均匀性时空分析方法及系统，发明，授权号：CN111814316B，2024.04.02（发明专利权授予）
（14）李静; 朱欣然; 柳钦火; 赵静; 董亚冬，叶面积指数时间序列重建方法、装置、设备及存储介质，发明，授权号：CN111723328B，2024.02.13（发明专利权授予）
（15）李静; 林尚荣; 柳钦火; 赵静; 董亚冬，全球中高分辨率植被总初级生产力产品的计算方法及装置，发明，授权号：CN111582703B，2024.04.05（发明专利权授予）
（16）李静; 张虎; 柳钦火; 赵静; 董亚冬，叶片叶绿素含量反演方法、装置、电子设备及存储介质，发明，授权号：CN111398178B，2023.05.16（发明专利权授予）
（17）董亚冬; 李静; 柳钦火; 赵静，一种中分辨率叶面积指数产品的校正方法及装置，发明，授权号：CN111402322B，2024.04.05（发明专利权授予）
（18）柏军华; 柳钦火; 肖青; 曹彪; 张召星，一种植被冠层垂直结构参数测量方法、装置及系统，发明，授权号：CN110849329B，2021.06.25（发明专利权授予）
（19）辛晓洲; 李福根; 彭志晴; 矫京均; 柳钦火，一种j9游会真人游戏第一品牌影像中混合像元的日蒸散量的计算方法和系统，发明，授权号：CN107843569B，2020.02.18（发明专利权授予）
（20）柏军华; 柳钦火; 肖青; 杨习荣; 孙刚，j9游会真人游戏第一品牌地面定位试验的多角度观测装置及方法，发明，授权号：CN106094886B，2019.08.06（发明专利权授予）
（21）柏军华; 柳钦火; 李静; 肖青，一种作物长势定量j9游会真人游戏第一品牌监测方法及系统，发明，授权号：CN106018284B，2018.10.30（发明专利权授予）
（22）李丽; 杜永明; 张海龙; 柏军华; 辛晓洲; 柳钦火; 肖青，一种植被冠层光合有效辐射吸收比例的观测系统及方法，发明，授权号：CN104568145B，2018.02.13（发明专利权授予）
（23）仲波; 吴善龙; 柳钦火，一种高分辨率j9游会真人游戏第一品牌数据大气校正方法，发明，授权号：CN102955154B，2014.04.16（发明专利权授予）
4.国家标准
（1）陆地定量j9游会真人游戏第一品牌产品真实性检验通用方法.葛咏; 胡茂桂; 王江浩; 李新; 王劲峰; 张仁华; 吴骅; 柳钦火; 王新鸿; 潘志强; 刘照言.国家标准, GB/T 39468-2020, 全国j9游会真人游戏第一品牌技术标准化技术委员会(SAC/TC 327), 2020-11-19.
（2）植被指数j9游会真人游戏第一品牌产品真实性检验.闻建光; 彭菁菁; 游冬琴; 刘强; 唐勇; 肖青; 柳钦火; 李新; 范闻捷; 葛咏; 吴骅; 王新鸿; 刘照言. 国家标准, GB/T 40038-2021, 全国j9游会真人游戏第一品牌技术标准化技术委员会(SAC/TC 327), 2021-04-30.
（3）叶面积指数j9游会真人游戏第一品牌产品真实性检验.李静; 赵静; 邹杰; 曾也鲁; 柳钦火; 李新; 方红亮; 唐伯惠; 范闻捷; 屈永华; 穆西晗; 姜小光; 陈尔学; 吴文斌; 董亚冬; 王新鸿; 刘照言; 尹高飞; 徐保东. 国家标准, GB/T 40034-2021, 全国j9游会真人游戏第一品牌技术标准化技术委员会(SAC/TC 327), 2021-04-30.
（4）光合有效辐射j9游会真人游戏第一品牌产品真实性检验.李丽; 辛晓洲; 张海龙; 闻建光; 吴骅; 王培娟; 高彦华; 姚延娟; 仲波; 余珊珊; 柏军华; 杜永明; 柳钦火; 刘照言; 于江丰; 龚力峰. 国家标准, GB/T 41281-2022, 全国j9游会真人游戏第一品牌技术标准化技术委员会(SAC/TC 327), 2022-03-09.
（5）反照率j9游会真人游戏第一品牌产品真实性检验.游冬琴; 闻建光; 刘强; 吴小丹; 林兴稳; 唐勇; 肖青; 柳钦火; 李新; 焦子锑; 范闻捷; 马明国; 刘照言; 王新鸿. 国家标准, GB/T 41279-2022, 全国j9游会真人游戏第一品牌技术标准化技术委员会(SAC/TC 327), 2022-03-09.
（6）气溶胶光学厚度j9游会真人游戏第一品牌产品真实性检验.仲波; 吴善龙; 陈武汉; 孙林; 张玉环; 孙长奎; 周春艳; 杨爱霞; 吴俊君; 柳钦火; 刘照言; 闻建光; 李丽; 孙刚; 李凯涛. 国家标准, GB/T 41535-2022, 全国j9游会真人游戏第一品牌技术标准化技术委员会(SAC/TC 327), 2022-07-11.
（7）地表温度j9游会真人游戏第一品牌产品真实性检验.李召良; 唐伯惠; 吴骅; 周成虎; 李传荣; 邱实; 尚国琲; 钱永刚; 段四波; 刘照言; 阎广建; 刘向阳; 范锦龙; 张仁华; 冷佩; 赵伟; 任华忠; 唐荣林; 柳钦火; 郑小坡; 姜小光; 赵恩宇; 高懋芳; 张霞; 于文凭. 国家标准, GB/T 41534-2022, 全国j9游会真人游戏第一品牌技术标准化技术委员会(SAC/TC 327), 2022-07-11.
