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男，四川人，博士，现任中国科学院地理科学与资源研究所研究员、博生生导师。长期从事数据同化、定量遥感以及气候变化等方面的研究，目前已在国内外发表SCI论文70余篇，SCI 总引6000余次，研究成果被 Science 和 Nature 等国际知名期刊报道与引用。获得发明专利授权1项。
教育经历：
1997-09--2001-06，就读于南京气象学院，获学士学位；
2001-09--2006-06，就读于北京师范大学，获博士学位；
工作经历：
2006-06~2008-04，中国科学院地理科学与资源研究所，博士后；
2008-04~2015-05，中国科学院青藏高原研究所，副研究员；
2015-05~2020-05，中国科学院青藏高原研究所，研究员；
2021-03~至今， 中国科学院地理科学与资源研究所，研究员；
研究领域和研究方向：
研究领域：定量遥感及其水文气象应用
主要研究方向：遥感大数据应用、全球气候变化
主要科研成果：
第一，独立开发了基于粒子滤波的陆面卫星数据同化算法，同时估算陆面模型的参数和状态变量，提高了地表土壤水分的估算精度。同时，和团队其他研究人员共同开发了业务化运行的变分陆面同化系统，生产了青藏高原近 10 年的时间土壤水分产品。
第二，为了推进土壤水分遥感与同化研究，参与设计和建设位于青藏高原那曲地区的多尺度（100公里、 25公里和 10公里）土壤温湿度观测网络，为现有和即将执行的卫星计划提供验证，利用该网络数据提出了全新的由点及面的空间升尺度算法，解决了土壤水分遥感产品验证的空间尺度不匹配问题，有效降低卫星土壤水分验证的不确定性。
第三， 针对高原台站空间代表性不足问题，采用卫星遥感数据与台站数据相结合的思路，获取青藏高原面上高空间分辨率网格温度和大气可降水量数据，并分析其变化趋势随海拔变化，弥补5000 米以上海拔没有常规观测站数据的缺点，提升了对高原气候变化更为全面的认识。
主要研究项目(最多10项)：
1.第三次新疆综合科学考察子课题“塔里木河流域干旱与风沙灾害调查和风险评估”,2021-2024，831万,主持
2.中国科学院前沿项目“融合多源遥感数据与水文模型提升模式性能”，2016，100万元
3.国家重点研发计划“全球陆面模型优化、同化、陆气耦合模拟与预测研究”子课题，50万元
4.中国科学院青年科学家促进会基金，40万元
5.自然科学基金面上项目“基于水热碳耦合模型的青藏高原多源遥感资料同化”, 2012-2015,65万元,主持
6.自然科学基金面上项目“动态融合多源遥感数据反演地表太阳辐射的研究”, 2011-2013,45万元,主持
7.载人航空天宫一号“综合对地观测数据民用试应用青藏高原地表监测”,2011-2014，50万元,主持
8.国家 863 计划“全球陆表特征参量产品生产与应用研究”子课题“全球下行太阳短波辐射的遥感提取方法研究”, 2009-2012,90万元,主持
9.环保公益性项目“中国温室气体时空格局及其气候效应影响研究”子课题“温室气体气候效应”, 2009-2011,46万元,主持
近十年代表性学术论文：
1. Tian J, Qin J, Yang K, et al., (2022): Improving surface soil moisture retrievals through a novel assimilation algorithm to estimate both model and observation errors, Remote Sensing of Environment, 269: 112802. (SCI, IF=10.2)
2.Jiang, H., Yao, L., Lu, N., Qin, J., et al., (2021): Multi-resolution dataset for photovoltaic panel segmentation from satellite and aerial imagery, Earth Syst. Sci. Data, 13, 5389–5401 (SCI, IF=11.33)
3.Liu T, Yao L, Qin J, et al., (2021): A Deep Neural Network for the Estimation of Tree Density Based on High-Spatial Resolution Image, IEEE Transactions on Geoscience and Remote Sensing, 2021, 60: 4403811 (SCI, IF=5.60)
4.Jiang, H., N. Lu, J. Qin, L. Yao, (2021): Hierarchical identification of solar radiation zones in China, Renewable and Sustainable Energy Reviews, 145: 111105 (SCI, IF=12.110)
5.Zhu F, Li X, Qin J, et al. (2021): Integration of Multisource Data to Estimate Downward Longwave Radiation Based on Deep Neural Networks, IEEE Transactions on Geoscience and Remote Sensing, 60: 1-15. (SCI, IF=5.60)
6.Tang W, Qin J, Yang K, et al. (2021): Does ERA5 outperform satellite products in estimating atmospheric downward longwave radiation at the surface?, Atmospheric Research, 2021, 252: 105453.
7.Yao, L., T. Liu, J. Qin, N. Lu, C. Zhou, (2021): Tree counting with high spatial-resolution satellite imagery based on deep neural networks, Ecological Indicator, 125: 107591 (SCI, IF=4.229)
8.Zhou, X., Qin, J., Li, H.D., Tang, W., Pan, X., Li, X., 2020: A statistical method to construct wind speed at turbine height for study of wind power in China. Theoretical and applied Climatology, 141: 419–432
9.Yang, K., Chen, Y.Y., He, J., Zhao, L., Lu, H., Qin, J., Zheng, D.H., Li, X. (2020): Development of a daily soil moisture product for the period of 2002-2011 in Chinese Mainland. Science China - Earth Sciences, 63:113-1125 (SCI, IF=2.370)
10.He, J., K. Yang, W. Tang, H. Lu, J. Qin, Y. Chen, X. Li, (2020): The first high-resolution meteorological forcing dataset for land process studies over China, Scientific Data, 7, 25 (SCI, IF=6.460)
11.Tang, W., J. Li, K. Yang, J. Qin, G. Zhang, Y. Wang, 2019: Dependence of remote sensing accuracy of global horizontal irradiance at different scales on satellite sampling frequency, Solar Energy, 193: 597-603 (SCI, IF=4.674)
12.Tang, W., K. Yang, J. Qin, X. Li, X. Niu, 2019: A 16-year dataset (2000-2015) of high-resolution (3 h, 10 km) global surface solar radiation, Earth System Science Data, 11:1905-1915 (SCI, IF=10.951)
13.Jiang, H., N., Lu, J. Qin, W. Tang, L. Yao, 2019: A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data, Renewable and Sustainable Energy Reviews, 114: 109327 (SCI, IF=10.556)
14.Lu, N., S. Liang, G. Huang, J. Qin, L. Yao, D. Wang, K. Yang, 2018: Hierarchical Bayesian space-time estimation of monthly maximum and minimum surface air temperature, Remote Sens. Environ, 211: 48-58 (SCI, IF=6.457)
15.Kang, J., R. Jin, X. Li, C. Ma, J. Qin, Y. Zhang, 2017: High spatio-temporal resolution mapping of soil moisture by integrating wireless sensor network observations and MODIS apparent thermal inertia in the Babao River Basin, China, Remote Sens. Environ, 191: 232-245 (SCI, IF=6.457)
16.Chen, Y., K. Yang, J. Qin, Q. Cui, H. Lu, Lazhu, M. Han, and W. Tang, 2017: Evaluation of SMAP, SMOS, and AMSR2 soil moisture retrievals against observations from two networks on the Tibetan Plateau, J. Geophys. Res. Atmos., 122(11), 5780-5792 (SCI, IF=3.159)
17.Wang, Y., K. Yang, Z. Pan, J. Qin, D. Chen, C. Lin, Y. Chen, Lazhu, W. Tang, M. Han, N. Lu, and H. Wu, 2017: Evaluation of Precipitable Water Vapor from Four Satellite Products and Four Reanalysis Datasets against GPS Measurements on the Southern Tibetan Plateau, J. Climate, 30(15), 5699-5713 (SCI, IF=4.850)
18.Han, M., H. Lu, K. Yang, J. Qin, Y. Chen, L. Zhao, and Lazhu, 2017: A surface soil temperature retrieval algorithm based on AMSR-E multi-frequency brightness temperatures, International Journal of Remote Sensing, 38(23): 6735-6754 (SCI, IF=1.782)
19.Tang, W., K. Yang, Z. Sun, J. Qin, and X. Niu, 2017: Global Performance of a Fast Parameterization Scheme for Estimating Surface Solar Radiation From MODIS Data, IEEE Trans. Geosci. Remote Sens, 55(6): 3558-3571 (SCI, IF=4.662)
20.Tang, W., J. Qin, K. Yang, X. Niu, M. Min, and S. Liang, 2017: An efficient algorithm for calculating photosynthetically active radiation with MODIS products, Remote Sens. Environ, 194: 146-154 (SCI, IF=6.457)
21.Tang, W., K. Yang, J. Qin, X. Niu, C. Lin, and X. Jing, 2017: A revisit to decadal change of aerosol optical depth and its impact on global radiation over China, Atmos. Env., 150, 106-115 (SCI, IF=3.708)
22.Lazhu, K. Yang, J. Wang, Y. Lei, Y. Chen, L. Zhu, B. Ding, and J. Qin, 2016: Quantifying evaporation and its decadal change for Lake Nam Co, central Tibetan Plateau, J. Geophys. Res. Atmos., 121(16), 7578-7591 (SCI, IF=3.159)
23.Tang, W., J. Qin, K. Yang, S. Liu, N. Lu, and X. Niu, 2016: Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data, Atmos. Chem. Phys., 16, 2543-2557 (SCI, IF=5.509)
24.Yang, K., Lazhu, Y. Chen, L. Zhao, J. Qin, H. Lu, W. Tang, M. Han, B. Ding, and N. Fang, 2016: Land surface model calibration through microwave data assimilation for improving soil moisture simulations, J. Hydrol., 533, 266–276 (SCI, IF=3.727)
25.Lu, H., K. Yang, T. Koike, L. Zhao, and J. Qin, 2015: An Improvement of the Radiative Transfer Model Component of a Land Data Assimilation System and Its Validation on Different Land Characteristics, Remote Sens., 7(5), 6358-6379 (SCI, IF=3.406)
26.Lin, C., K. Yang, J. Huang, W. Tang, J. Qin, X. Niu, Y. Chen, D. Chen, N. Lu, and R. Fu, 2015: Impacts of wind stilling on solar radiation variability in China, Sci. Rep., 5, 15135 (SCI, IF=4.122)
27.Qin, J., W. Tang, K. Yang, N. Lu, X. Niu, and S. Liang, 2015: An efficient physically based parameterization to derive surface solar irradiance based on satellite atmospheric products, J. Geophys. Res. Atmos., 120, 4975-4988 (SCI, IF=3.159)
28.Qin, J., L. Zhao, Y. Chen, K. Yang, Y. Yang, Z. Chen, and H. Lu, 2015: Inter-comparison of spatial upscaling methods for evaluation of satellite-based soil moisture, J. Hydrol., 523, 170-178 (SCI, IF=3.727)
29.Han, M., K. Yang, J. Qin, R. Jin, Y. Ma, J. Wen, Y. Chen, L. Zhao, Lazhu, and W. Tang, 2015: An algorithm based on the standard deviation of passive microwave brightness temperatures for monitoring soil surface freeze/thaw state on the Tibetan Plateau, IEEE Trans. Geosci. Remote Sens., 53(5), 2775-2783. (SCI, IF=4.662)
30.Lu, N., K.E. Trenberth, J. Qin, K. Yang, L. Yao, 2015: Detecting long-term trend in precipitable water over the Tibetan Plateau by synthesis of station and MODIS observations, Journal of Climate, 28, 1707-1722 (SCI, IF=4.850)
31.Lu, N., J. Qin, Y. Gao, K. Yang, K.E. Trenberth, M. Gehne, and Y. Zhu, 2014: Trends and variability in atmospheric precipitable water over the Tibetan Plateau for 2000–2010, Int. J. Climatol., DOI: 10.1002/joc.4064 (SCI, IF=3.100)
32.Yang, K., H. Wu, Y. Chen, J. Qin, and L. Wang, 2014: Toward a satellite-based observation of atmospheric heat source over land, J. Geophys. Res. Atmos., 119(6), 3124-3133 (SCI, IF=3.159)
33.Zhao, L., K. Yang, J. Qin, Y. Chen, W. Tang, H. Lu, and Z. Yang, 2014: The scale-dependence of SMOS soil moisture accuracy and its improvement through land data assimilation in the central Tibetan Plateau, Remote Sens. Environ., 152, 345-355. (SCI, IF=6.457)
34.Ding, B., K. Yang, J. Qin, L. Wang, Y. Chen, X. He, 2014: The dependence of precipitation types on surface elevation and meteorological conditions and its parameterization, Journal of Hydrology, 513:154-163 (SCI, IF=3.727)
35.Yang, K., H. Wu, J. Qin, C. Lin, W. Tang, Y. Chen, 2014: Recent climate changes over the Tibetan Plateau and their impacts on energy and water cycle: A review, Global and Planetary Change, 112: 79-91 (SCI, IF=3.155)
36.Yang, K., J. Qin, L. Zhao, Y. Chen, W. Tang, M. Han, Lazhu, Z. Chen, N. Lv, B. Ding, H. Wu, C. Lin, 2013: A Multiscale Soil Moisture and Freeze-Thaw Monitoring Network on the Third Pole，Bulletin of the American Meteorological Society, 94(12):1907-191 (SCI, IF=6.591)
37.Chen, Y., K. Yang, J. Qin, L. Zhao, W. Tang and M. Han,2013: Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau, J. Geophys. Res. Atmos., 118: 4466-4475 (SCI, IF=3.174)
38.Qin, J., K. Yang, N. Lv, Y. Chen, L. Zhao, M. Han, 2013:, Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia, Remote Sensing of Environment, 138: 1-9 (SCI, IF=5.103)
39.Qin, J., K. Yang, S. L. Liang, W. J. Tang, 2012: Estimation of daily photosynthetically active radiation under all-sky conditions from sunshine duration data, Journal of Applied Meteorology and Climatology, 51, 150~160 (SCI, IF=2.020)
研究生招生与培养：
招生专业：地图学与地理信息系统
招生方向：遥感大数据计算与分析、全球气候变化
欢迎有水文气象基础、数学背景和计算编程能力强的同学报考。
联系方式：
通信地址：北京市朝阳区大屯路甲11号
邮 编：100101
E – mail：qinjun@igsnrr.ac.cn
更新日期：2022年3月3日
