男，湖北恩施人，理学博士。现任中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室副研究员。教育经历：
2016.09-2021.06 中国科学院大学，获地图学与地理信息系统专业理学博士学位
2012.09-2016.06 武汉大学，获地图学与地理信息系统专业理学学士学位
工作经历：
2021.06-2023.08 中国科学院地理科学与资源研究所，博士后
研究方向：
遥感信息分析与应用；新能源；深度学习；可持续发展
主持项目：
1. 国家自然科学基金青年项目：集成静止气象卫星观测和深度学习的地表太阳辐射短时预测方法研究（42201382）
2. 中国博士后科学基金面上资助：卫星和地面观测融合的地表太阳辐射预测方法研究（2021M703176）
3. 遥感科学国家重点实验室开放基金：风云和高分卫星影像驱动的中国屋顶光伏发电潜力评估方案研究（OFSLRSS202204）
代表性论文：
[1] Jiang H., Zhang X., Yao L., Lu N., Qin J., Liu T., Zhou C. High-resolution analysis of rooftop photovoltaic potential based on hourly generation simulations and load profiles, Applied Energy, 2023, 348: 121553，（中科院1区，IF: 11.2）
[2] Jiang H., Lu N., Yao L., Qin J., Liu T. Impact of climate changes on the stability of solar energy: Evidence from observations and reanalysis, Renewable Energy, 2023, 208: 726-736（中科院1区，IF: 8.7）
[3] Jiang H., Yao L., Zhou C. Assessment of offshore wind-solar energy potentials and spatial layout optimization in mainland China, Ocean Engineering, 2023, 287: 115914 (中科院1区, IF: 5.0)
[4] Jiang H., Lu N., Qin J., Yao L. Hierarchical identification of solar radiation zones in China. Renewable & Sustainable Energy Reviews, 2021, 145: 111105（中科院1区，IF: 15.9）
[5] Jiang, H., Yao, L., Qin, J., Liu, T., Liu, Y., Zhou, C. Multi-resolution dataset for photovoltaic panel segmentation from satellite and aerial imagery. Earth System Science Data, 2021, 13:5389–5401 (中科院1区, IF: 11.4)
[6] Jiang, H., Lu, N., Zhang, X., Yao, L., Bai, Y. Satellite observed cooling effects from re-vegetation on the Mongolian Plateau. Science of the Total Environment, 2021, 781:146707 (中科院1区, IF: 9.8)
[7] Jiang H., Lu N., Huang G., Yao L., Qin J., Liu H. Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data, Applied Energy, 2020, 270: 115178 （中科院1区，IF: 11.2）
[8] Jiang H., Lu N., Qin J., Tang W., Yao L. A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data. Renewable & Sustainable Energy Reviews, 2019, 114: 109327（中科院1区，IF: 15.9）
[9] Qin, J., Jiang, H., Lu, N., Yao, L. Zhou, C. Enhancing solar PV output forecast by integrating ground and satellite observations with deep learning. Renewable & Sustainable Energy Reviews, 2022, 167:112680. (共同第一作者, 中科院1区, IF: 15.9)
[10] Qin, J., Pan, W., He, M., Lu, N., Yao, L., Jiang, H., Zhou, C. A long-term 1km monthly near-surface air temperature dataset over the Tibetan glaciers by fusion of station and satellite observations. Earth System Science Data, 2023, 15:331-344. (共同通讯作者, 中科院1区, IF: 11.4)
[11] Jiang, H., Lu, N. & Wang, X. Assessing carbon reduction potential of rooftop PV in China through remote sensing data-driven simulations. Sustainability, 2023, 15:3380.
[12] Jiang, H., Yao, L., Lu, N., Qin, J., Liu, T., Liu, Y., & Zhou, C. Geospatial assessment of rooftop solar photovoltaic potential using multi-source remote sensing data. Energy and AI, 2022, 10:100185.
[13] Jiang, H., Lu, N., Qin, J. & Yao, L. Hourly 5-km surface total and diffuse solar radiation in China, 2007-2018. Scientific Data, 2020,7:311.
[14] Jiang, H., Yang, Y., Bai, Y. & Wang, H. Evaluation of the total, direct, and diffuse solar radiations from the ERA5 reanalysis data in China. IEEE Geoscience and Remote Sensing Letters, 2020,17(1) :47-51.
[15] Jiang, H., Yang, Y., Wang, H., Bai, Y. & Bai, Y. Surface diffuse solar radiation determined by reanalysis and satellite over East Asia: evaluation and comparison. Remote Sensing, 2020,12:1387.
[16] Jiang, H. & Lu, N. Multi-scale residual convolutional neural network for haze removal of remote sensing images. Remote Sensing, 2018,10:945.
[17] Jiang, H., Lu N., Yao L. & Zhang X. Single image dehazing for visible remote sensing based on tagged haze thickness maps. Remote Sensing Letters, 2018,9(7):627-635.
[18] Jiang, H., Yang, Y. & Bai, Y. Evaluation of All-for-One tourism in mountain areas using multi-source data. Sustainability, 2018,10:4065.
[19] Jiang, H., Lu, N. & Yao, L. A high-fidelity haze removal method based on HOT for visible remote sensing images. Remote Sensing. 2016,8:844.
[20] Yao, L., Lu, J., Jiang, H., Liu, T., Qin, J. & Zhou, C. Satellite-derived aridity index reveals China's drying in recent two decades. iScience, 2023, 26(3):106185.
[21] Qin, J., He, M., Jiang, H. & Lu, N. Reconstruction of 60-year (1961–2020) surface air temperature on the Tibetan Plateau by fusing MODIS and ERA5 temperatures. Science of the Total Environment, 2022, 853:138406.
[22] Liu, Y., Yao, L., Jiang, H., Lu, N., Qin, J., Liu, T. & Zhou, C. Spatial estimation of the optimum PV tilt angles in China by incorporating ground with satellite data. Renewable Energy, 2022, 189:7830.
[23] Zou, J., Lu, N., Jiang, H., Qin, J., Yao, L., Xin, Y. & Su, F. Performance of air temperature from ERA5-Land reanalysis in coastal urban agglomeration of Southeast China. Science of the Total Environment, 2022, 828:154459.
[24] Xin, Y., Lu, N., Jiang, H., Liu, Y. & Yao, L. Performance of ERA5 reanalysis precipitation products in the Guangdong-Hong Kong-Macao greater Bay Area, China. Journal of Hydrology, 2021,602:126791.
[25] Liu, H., Lu, N., Jiang, H., Qin, J. & Yao, L. Filling gaps of monthly Terra/MODIS daytime land surface temperature using discrete cosine transform method. Remote Sensing, 2020,12(3):361.
[26] Zhang, X., Lu, N., Jiang, H & Yao, L. Evaluation of reanalysis surface incident solar radiation data in China. Scientific Reports, 2020,10:3494.
[27] Bai, Y., Yang, Y. & Jiang, H. Intercomparison of AVHRR GIMMS3g, Terra MODIS, and SPOT-VGT NDVI Products over the Mongolian Plateau. Remote Sensing, 2019,11(17): 2030.
[28] Long, F., Liu, J., Zhang, S., Yu, H. & Jiang, H. (2018). Development Characteristics and Evolution Mechanism of Homestay Agglomeration in Mogan Mountain, China. Sustainability, 2018,10(9): 2964.
[29] Qin, J., He, M., Yang, W., Lu, N., Yao, L., Jiang, H., Wu, J., Yang, K., & Zhou, C. Temporally extended satellite-derived surface air temperatures reveal a complete warming picture on the Tibetan Plateau. Remote Sensing of Environment, 2023, 285:113410.
[30] Liu, T., Yao, L., Qin, J., Lu, N., Jiang, H. & Zhou, C. Multi-scale attention integrated hierarchical networks for high-resolution building footprint extraction. International Journal of Applied Earth Observation and Geoinformation, 2022, 109:102768.
[31] Lu, N., Yao, L., Qin, J., Yang, K., Wild, M., & Jiang, H. High emission scenario substantially damages China's photovoltaic potential. Geophysical Research Letters, 2022, 49:e2022GL100068.
[32] Lu, J., Bu, P., Xia, X., Lu, N., Yao, L., & Jiang, H. Feasibility of machine learning methods for predicting hospital emergency room visits for respiratory diseases. Environmental Science and Pollution Research, 2021, 28:29701–29709.
[33] 姜侯,吕宁. (2019).单幅光学遥感影像去霾算法及评价综述.中国图象图形学报,2019,24(09):1416-1433.
[34] 姜侯,杨雅萍,孙九林. (2019).农业大数据研究与应用.农业大数据学报,2019,1(01):5-15.
[35] 姜侯,吕宁,姚凌.改进HOT法的Landsat 8 OLI遥感影像雾霾及薄云去除.遥感学报,2016,20(04):620-631.
[36] 刘恒孜,吕宁,姜侯,等.基于DCT-PLS算法的MODIS LST缺值填补方法研究.地球信息科学学报, 2022,24(2):378-390.
[37] 杨雅萍,姜侯,孙九林.科学数据共享实践：以国家地球系统科学数据中心为例.地球信息科学学报,2020,22(6):1358-1369.
[38] 杨雅萍,姜侯,胡云锋,孙九林. (2020). “互联网 +”农产品质量安全追溯发展研究.中国工程科学,2020,22(4):58-64.
[39] 张星星,吕宁,姚凌,姜侯. ECMWF地表太阳辐射数据在我国的误差及成因分析.地球信息科学学报,2018,20(2):254-267.
其他奖励：
[1] 地理信息科技进步奖-特等奖（序9，2022）、地理信息科技进步奖-一等奖（序8，2023）
[2] 李小文遥感科学青年奖（2021）
联系方式：
通信地址：北京市朝阳区大屯路甲11号中国科学院地理科学与资源研究所
邮 编：100101
E–mail: jianghou@igsnrr.ac.cn
