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Li,H., Yan, K., Gao, S., Ma, X.,Zeng, Y., Li, W., Yin, G., Mu, X., Yan, G., Myneni, R.B., 2023. A NovelInversion Approach for the Kernel-Driven BRDF Model for Heterogeneous Pixels.J. Remote Sens. 3, 0038. https://doi.org/10.34133/remotesensing.0038
Pu,J., Yan, K., Gao, S., Zhang,Y., Park, T., Sun, X., Weiss, M., Knyazikhin, Y., Myneni, R.B., 2023. Improvingthe MODIS LAI compositing using prior time-series information. Remote Sens.Environ. 287, 113493. https://doi.org/10.1016/j.rse.2023.113493
Lin,Y., Liu, S., Yan, L., Yan, K.,Zeng, Y., Yang, B., 2023. Improving the estimation of canopy structure usingspectral invariants: Theoretical basis and validation. Remote Sens. Environ.284, 113368. https://doi.org/10.1016/j.rse.2022.113368
Li,H., Yan, K., Gao, S., Ma, X.,Zeng, Y., Li, W., Yin, G., Mu, X., Yan, G., Myneni, R.B., 2023. A NovelInversion Approach for the Kernel-Driven BRDF Model for Heterogeneous Pixels.J. Remote Sens. 3, 0038. https://doi.org/10.34133/remotesensing.0038
Wang,J., Yan, K., Gao, S., Pu, J.,Liu, J., Park, T., Bi, J., Maeda, E.E., Heiskanen, J., Knyazikhin, Y., Myneni,R.B., 2023. Improving the Quality of MODIS LAI Products by ExploitingSpatiotemporal Correlation Information. IEEE Trans. Geosci. Remote Sens. 61,1–19. https://doi.org/10.1109/TGRS.2023.3264280
Li,H., Yan, K., Gao, S., Ma, X.,Zeng, Y., Li, W., Yin, G., Mu, X., Yan, G., Myneni, R.B., 2023. A NovelInversion Approach for the Kernel-Driven BRDF Model for Heterogeneous Pixels.J. Remote Sens. 3, 0038. https://doi.org/10.34133/remotesensing.0038
Chi,H., Yan, K., Yang, K., Du,S., Li, H., Qi, J., Zhou, W., 2022. Evaluation of Topographic Correction ModelsBased on 3-D Radiative Transfer Simulation. IEEE Geosci. Remote Sens. Lett. 19,1–5. https://doi.org/10.1109/LGRS.2021.3110907
Li,H., Yan, K., Gao, S., Song,W., Mu, X., 2022. Revisiting the Performance of the Kernel-Driven BRDF ModelUsing Filtered High-Quality POLDER Observations. Forests 13, 435.https://doi.org/10.3390/f13030435
Liu,Y., Zhou, W., Gao, S., Ma, X., Yan,K., 2022a. Phenological Responses to Snow Seasonality in the QilianMountains Is a Function of Both Elevation and Vegetation Types. Remote Sens.14, 3629. https://doi.org/10.3390/rs14153629
Liu,Y., Zhou, W., Yan, K., Guan,Y., Wang, J., 2022b. Identification of the disturbed range of coal miningactivities: A new land surface phenology perspective. Ecol. Indic. 143, 109375.https://doi.org/10.1016/j.ecolind.2022.109375
Yan, K., Gao, S., Chi, H., Qi,J., Song, W., Tong, Y., Mu, X., Yan, G., 2022. Evaluation of theVegetation-Index-Based Dimidiate Pixel Model for Fractional Vegetation CoverEstimation. IEEE Trans. Geosci. Remote Sens. 60, 1–14.https://doi.org/10.1109/TGRS.2020.3048493
Zhao,Y., Wang, M., Zhao, T., Luo, Y., Li, Y., Yan,K., Lu, L., Tran, N.N., Wu, X., Ma, X., 2022. Evaluating the potentialof H8/AHI geostationary observations for monitoring vegetation phenology overdifferent ecosystem types in northern China. Int. J. Appl. Earth Obs.Geoinformation 112, 102933. https://doi.org/10.1016/j.jag.2022.102933
Zou,D., Yan, K., Pu, J., Gao, S.,Li, W., Mu, X., Knyazikhin, Y., Myneni, R.B., 2022. Revisit the Performance ofMODIS and VIIRS Leaf Area Index Products from the Perspective of Time-SeriesStability. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 15, 8958–8973.https://doi.org/10.1109/JSTARS.2022.3214224
闫凯, 陈慧敏,付东杰, 曾也鲁, 董金玮,李世卫, 吴秋生, 李翰良,杜姝渊, 2022. 遥感云计算平台相关文献计量可视化分析. 遥感学报 26, 14.
Li,H., Yan, K., Gao, S., Ma, X.,Zeng, Y., Li, W., Yin, G., Mu, X., Yan, G., Myneni, R.B., 2023. A NovelInversion Approach for the Kernel-Driven BRDF Model for Heterogeneous Pixels.J. Remote Sens. 3, 0038. https://doi.org/10.34133/remotesensing.0038
Wang,J., Wang, S., Zou, D., Chen, H., Zhong, R., Li, H., Zhou, W., Yan, K., 2021. Social Networkand Bibliometric Analysis of Unmanned Aerial Vehicle Remote SensingApplications from 2010 to 2021. Remote Sens. 13, 2912.https://doi.org/10.3390/rs13152912
Yan, K., Pu, J., Park, T., Xu,B., Zeng, Y., Yan, G., Weiss, M., Knyazikhin, Y., Myneni, R.B., 2021a.Performance stability of the MODIS and VIIRS LAI algorithms inferred fromanalysis of long time series of products. Remote Sens. Environ. 260, 112438.https://doi.org/10.1016/j.rse.2021.112438
Yan, K., Zhang, Y., Tong, Y.,Zeng, Y., Pu, J., Gao, S., Li, L., Mu, X., Yan, G., Rautiainen, M., Knyazikhin,Y., Myneni, R.B., 2021b. Modeling the radiation regime of a discontinuouscanopy based on the stochastic radiative transport theory: Modification,evaluation and validation. Remote Sens. Environ. 267, 112728.https://doi.org/10.1016/j.rse.2021.112728
Yan, K., Zou, D., Yan, G.,Fang, H., Weiss, M., Rautiainen, M., Knyazikhin, Y., Myneni, R.B., 2021c. ABibliometric Visualization Review of the MODIS LAI/FPAR Products from 1995 to2020. J. Remote Sens. 2021, 2021/7410921. https://doi.org/10.34133/2021/7410921
Yin,G., Li, J., Xu, B., Zeng, Y., Wu, S., Yan,K., Verger, A., Liu, G., 2021. PLC-C: An Integrated Method forSentinel-2 Topographic and Angular Normalization. IEEE Geosci. Remote Sens.Lett. 18, 1446–1450. https://doi.org/10.1109/LGRS.2020.3001905
谢涓, 闫凯, 康志忠, 徐箫剑,薛彬, 杨建峰, 陶金有,2021. “祝融号”火星车多光谱相机岩矿类型识别的地面验证研究. 遥感学报 25, 15.
阎广建, 姜海兰, 闫凯, 程诗宇, 宋婉娟, 童依依, 刘雅楠, 漆建波, 穆西晗, 张吴明, 2021. 多角度光学定量遥感. 遥感学报 25, 26.
付东杰, 肖寒,苏奋振, 周成虎, 董金玮, 曾也鲁, 闫凯, 李世卫, 吴进, 吴文周, 2021. 遥感云计算平台发展及地球科学应用. 遥感学报 25, 11.
刘钊, 闫凯, 王铸, 蔡闻佳, 史培军, 2021. 1961-2020年中国31个城市热浪强度时空特征分析. 自然灾害学报 30, 9.
Cao,Y., Wang, Y., Peng, J., Zhang, L., Xu, L., Yan,K., Li, L., 2020. DML-GANR: Deep Metric Learning With GenerativeAdversarial Network Regularization for High Spatial Resolution Remote SensingImage Retrieval. IEEE Trans. Geosci. Remote Sens. 58, 8888–8904. https://doi.org/10.1109/TGRS.2020.2991545
Li,X., Huang, H., Shabanov, N.V., Chen, L., Yan,K., Shi, J., 2020. Extending the stochastic radiative transfer theoryto simulate BRF over forests with heterogeneous distribution of damaged foliageinside of tree crowns. Remote Sens. Environ. 250, 112040.https://doi.org/10.1016/j.rse.2020.112040
Pu,J., Yan, K., Zhang, Y., Xu,L., 2020a. Quality Analysis of the VIIRS LAI/FPAR Time-Series, in: IGARSS 2020- 2020 IEEE International Geoscience and Remote Sensing Symposium. Presented atthe IGARSS 2020 - 2020 IEEE International Geoscience and Remote SensingSymposium, IEEE, Waikoloa, HI, USA, pp. 3176–3179.https://doi.org/10.1109/IGARSS39084.2020.9323339
Pu,J., Yan, K., Zhou, G., Lei,Y., Zhu, Y., Guo, D., Li, H., Xu, L., Knyazikhin, Y., Myneni, R.B., 2020b.Evaluation of the MODIS LAI/FPAR Algorithm Based on 3D-RTM Simulations: A CaseStudy of Grassland. Remote Sens. 12, 3391. https://doi.org/10.3390/rs12203391
Xu,B., Li, J., Park, T., Liu, Q., Zeng, Y., Yin, G., Yan, K., Chen, C., Zhao, J., Fan, W., Knyazikhin, Y.,Myneni, R.B., 2020. Improving leaf area index retrieval over heterogeneoussurface mixed with water. Remote Sens. Environ. 240, 111700.https://doi.org/10.1016/j.rse.2020.111700
Yan,G., Chu, Q., Tong, Y., Mu, X., Qi, J., Zhou, Y., Liu, Y., Wang, T., Xie, D.,Zhang, W., Yan, K., Chen, S.,Zhou, H., 2020. An Operational Method for Validating the Downward ShortwaveRadiation Over Rugged Terrains. IEEE Trans. Geosci. Remote Sens. 1–18.https://doi.org/10.1109/TGRS.2020.2994384
Zeng,Y., Badgley, G., Chen, M., Li, J., Anderegg, L.D.L., Kornfeld, A., Liu, Q., Xu,B., Yang, B., Yan, K., Berry,J.A., 2020a. A radiative transfer model for solar induced fluorescence usingspectral invariants theory. Remote Sens. Environ. 240, 111678.https://doi.org/10.1016/j.rse.2020.111678
Zeng,Y., Li, J., Liu, Q., Huete, A.R., Xu, B., Yin, G., Fan, W., Ouyang, Y., Yan, K., Hao, D., Chen, M.,2020b. A Radiative Transfer Model for Patchy Landscapes Based on StochasticRadiative Transfer Theory. IEEE Trans. Geosci. Remote Sens. 58, 2571–2589. https://doi.org/10.1109/TGRS.2019.295237
张寅、闫凯、刘钊、濮嘉彬、张一满、曾也鲁, 2020. 基于CRU数据的1901—2018年全球陆表气温时空变化特征分析. 首都师范大学学报：自然科学版 41, 8.
Chu,Q., Yan, G., Wild, M., Zhou, Y., Yan,K., Li, L., Liu, Y., Tong, Y., Mu, X., 2019. Ground-Based RadiationObservational Method in Mountainous Areas, in: IGARSS 2019 - 2019 IEEEInternational Geoscience and Remote Sensing Symposium. Presented at the IGARSS2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, IEEE,Yokohama, Japan, pp. 8566–8569. https://doi.org/10.1109/IGARSS.2019.8900174
Yan, K., Tong, Y., Song, W.,Zeng, Y., Liu, Z., Mu, X., Yan, G., 2019. Analysis of the Kernel-Driven BrdfModel Over Rugged Terrains, in: IGARSS 2019 - 2019 IEEE InternationalGeoscience and Remote Sensing Symposium. Presented at the IGARSS 2019 - 2019IEEE International Geoscience and Remote Sensing Symposium, IEEE, Yokohama,Japan, pp. 6807–6810. https://doi.org/10.1109/IGARSS.2019.8898377
Chen,L., Mei, G., Yan, K., Hao,W., Yu, X., 2018. Species Discrimination of Plantations in Subtropical ChinaUsing 4-Band VHR Imagery and an Operational Image Analysis Framework. IEEE J.Sel. Top. Appl. Earth Obs. Remote Sens. 11, 2800–2813. https://doi.org/10.1109/JSTARS.2018.2837884
Li,L., Mu, X., Macfarlane, C., Song, W., Chen, J., Yan, K., Yan, G., 2018. A half-Gaussian fitting method forestimating fractional vegetation cover of corn crops using unmanned aerialvehicle images. Agric. For. Meteorol. 262, 379–390.https://doi.org/10.1016/j.agrformet.2018.07.028
Song,W., Knyazikhin, Y., Wen, G., Marshak, A., M?ttus, M., Yan, K., Yang, B., Xu, B., Park, T., Chen, C., Zeng, Y.,Yan, G., Mu, X., Myneni, R.B., 2018. Implications of Whole-Disc DSCOVR EPICSpectral Observations for Estimating Earth’s Spectral Reflectivity Based onLow-Earth-Orbiting and Geostationary Observations. Remote Sens. 10, 1594.https://doi.org/10.3390/rs10101594
Yan,G., Tong, Y., Yan, K., Mu,X., Chu, Q., Zhou, Y., Liu, Y., Qi, J., Li, L., Zeng, Y., Zhou, H., Xie, D.,Zhang, W., 2018. Temporal Extrapolation of Daily Downward Shortwave RadiationOver Cloud-Free Rugged Terrains. Part 1: Analysis of Topographic Effects. IEEETrans. Geosci. Remote Sens. 56, 6375–6394.https://doi.org/10.1109/TGRS.2018.2838143
Yan, K., Park, T., Chen, C.,Xu, B., Song, W., Yang, B., Zeng, Y., Liu, Z., Yan, G., Knyazikhin, Y., Myneni,R.B., 2018. Generating Global Products of LAI and FPAR From SNPP-VIIRS Data:Theoretical Background and Implementation. IEEE Trans. Geosci. Remote Sens. 56,2119–2137. https://doi.org/10.1109/TGRS.2017.2775247
Yin,G., Li, A., Wu, S., Fan, W., Zeng, Y., Yan,K., Xu, B., Li, J., Liu, Q., 2018. PLC: A simple and semi-physicaltopographic correction method for vegetation canopies based on path lengthcorrection. Remote Sens. Environ. 215, 184–198.https://doi.org/10.1016/j.rse.2018.06.009
Zeng,Y., Xu, B., Yin, G., Wu, S., Hu, G., Yan,K., Yang, B., Song, W., Li, J., 2018. Spectral Invariant Provides aPractical Modeling Approach for Future Biophysical Variable Estimations. RemoteSens. 10, 1508. https://doi.org/10.3390/rs10101508
Zhou,Y., Yan, G., Zhao, J., Chu, Q., Liu, Y., Yan,K., Tong, Y., Mu, X., Xie, D., Zhang, W., 2018. Estimation of DailyAverage Downward Shortwave Radiation over Antarctica. Remote Sens. 10, 422.https://doi.org/10.3390/rs10030422
Chen,C., Knyazikhin, Y., Park, T., Yan, K.,Lyapustin, A., Wang, Y., Yang, B., Myneni, R., 2017. Prototyping of LAI andFPAR Retrievals from MODIS Multi-Angle Implementation of Atmospheric Correction(MAIAC) Data. Remote Sens. 9, 370. https://doi.org/10.3390/rs9040370
Li,L., Yan, G., Mu, X., Suhong, Liu, Chen, Y., Yan, K., Luo, J., Song, W., 2017. Estimation of fractionalvegetation cover using mean-based spectral unmixing method, in: 2017 IEEEInternational Geoscience and Remote Sensing Symposium (IGARSS). Presented atthe 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),IEEE, Fort Worth, TX, pp. 3178–3180.https://doi.org/10.1109/IGARSS.2017.8127672
Yang,B., Knyazikhin, Y., M?ttus, M., Rautiainen, M., Stenberg, P., Yan, L., Chen,C., Yan, K., Choi, S., Park,T., Myneni, R.B., 2017. Estimation of leaf area index and its sunlit portionfrom DSCOVR EPIC data: Theoretical basis. Remote Sens. Environ. 198, 69–84.https://doi.org/10.1016/j.rse.2017.05.033
Bi,J., Myneni, R., Lyapustin, A., Wang, Y., Park, T., Chi, C., Yan, K., Knyazikhin, Y., 2016.Amazon Forests’ Response to Droughts: A Perspective from the MAIAC Product.Remote Sens. 8, 356. https://doi.org/10.3390/rs8040356
Yan, K., Park, T., Yan, G.,Chen, C., Yang, B., Liu, Z., Nemani, R., Knyazikhin, Y., Myneni, R., 2016a.Evaluation of MODIS LAI/FPAR Product Collection 6. Part 1: Consistency andImprovements. Remote Sens. 8, 359. https://doi.org/10.3390/rs8050359
Yan, K., Park, T., Yan, G.,Liu, Z., Yang, B., Chen, C., Nemani, R., Knyazikhin, Y., Myneni, R., 2016b.Evaluation of MODIS LAI/FPAR Product Collection 6. Part 2: Validation andIntercomparison. Remote Sens. 8, 460. https://doi.org/10.3390/rs8060460
Yang,B., Knyazikhin, Y., Lin, Y., Yan, K.,Chen, C., Park, T., Choi, S., M?ttus, M., Rautiainen, M., Myneni, R., Yan, L.,2016. Analyses of Impact of Needle Surface Properties on Estimation of NeedleAbsorption Spectrum: Case Study with Coniferous Needle and Shoot Samples.Remote Sens. 8, 563. https://doi.org/10.3390/rs8070563
Zeng,Y., Li, J., Liu, Q., Huete, A.R., Xu, B., Yin, G., Zhao, J., Yang, L., Fan, W.,Wu, S., Yan, K., 2016a. AnIterative BRDF/NDVI Inversion Algorithm Based on A Posteriori VarianceEstimation of Observation Errors. IEEE Trans. Geosci. Remote Sens. 54,6481–6496. https://doi.org/10.1109/TGRS.2016.2585301
Zeng,Y., Li, J., Liu, Q., Huete, A.R., Yin, G., Xu, B., Fan, W., Zhao, J., Yan, K., Mu, X., 2016b. ARadiative Transfer Model for Heterogeneous Agro-Forestry Scenarios. IEEE Trans.Geosci. Remote Sens. 54, 4613–4628. https://doi.org/10.1109/TGRS.2016.2547326
Chen,Y., Zhang, W., Yan, K., Li,X., Zhou, G., 2012. Extracting corn geometric structural parameters usingKinect, in: 2012 IEEE International Geoscience and Remote Sensing Symposium.Presented at the IGARSS 2012 - 2012 IEEE International Geoscience and RemoteSensing Symposium, IEEE, Munich, Germany, pp. 6673–6676.https://doi.org/10.1109/IGARSS.2012.6352068
Wang,H., Zhang, W., Chen, Y., Chen, M., Yan,K., 2015. Semantic Decomposition and Reconstruction of CompoundBuildings with Symmetric Roofs from LiDAR Data and Aerial Imagery. Remote Sens.7, 13945–13974. https://doi.org/10.3390/rs71013945
Yan,G., Ren, H., Hu, R., Yan, K.,Zhang, W., 2012. A portable Multi-Angle Observation System, in: 2012 IEEEInternational Geoscience and Remote Sensing Symposium. Presented at the IGARSS2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium, IEEE,Munich, Germany, pp. 6916–6919. https://doi.org/10.1109/IGARSS.2012.6352572
Yan, K., Ren, H., Hu, R., Mu,X., Liu, Z., Yan, G., 2013. Error analysis for emissivity measurement usingFTIR spectrometer, in: 2013 IEEE International Geoscience and Remote SensingSymposium - IGARSS. Presented at the IGARSS 2013 - 2013 IEEE InternationalGeoscience and Remote Sensing Symposium, IEEE, Melbourne, Australia, pp.3080–3083. https://doi.org/10.1109/IGARSS.2013.6723477
Zhang,W., Wang, H., Chen, Y., Yan, K.,Chen, M., 2014. 3D Building Roof Modeling by Optimizing Primitive’s ParametersUsing Constraints from LiDAR Data and Aerial Imagery. Remote Sens. 6,8107–8133. https://doi.org/10.3390/rs6098107
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