2006.9-2012.1，中国科学院大学，地图学与地理信息系统专业，理学博士

2002.9-2006.7，中国矿业大学（北京），测绘工程专业，学士学位

2023.04 – 至今，中国科学院空天信息创新研究院，副研究员

2019.07 – 2023.03，中国科学院空天信息创新研究院, 助理研究员

2018.10 – 2019.08, 加拿大约克大学（York University）, 访问学者

2012.07 – 2019.06，中科院对地观测中心/遥感地球所，助理研究员

2022.11 – 2025.10 国家重点研发计划课题“城市人居环境卫星监测及时空格局研究” 课题骨干

2023.03 – 2025.02 海南省自然科学基金面上“基于深度学习的海南岛岸线提取与动态监测” 项目负责人

2019.01 – 2021.12 国家自然科学基金青年项目“基于深度学习的高分辨率遥感图像融合研究”   项目负责人

2018.03 – 2021.03 海南省自然科学基金面上“基于国产高分辨率遥感的海岸开发活动遥感监测研究-以海口市为例” 项目负责人

2018.01 – 2020.12 国家重点研发计划子课题“面向震后灾情准确提取的多源卫星遥感数据快速处理技术” 项目负责人

2019.09 – 2021.09 空天院科学与颠覆性技术项目“基于高分辨率卫星遥感影像的单木树种分类关键技术研究” 课题骨干

2016.01 – 2018.12 遥地所所长青年基金 “基于混合亚像元解混的高分辨率MS与PAN融合研究” 项目负责人

2016.08 – 2017.10 国家海洋科技中心“基于高分辨率遥感的面向对象海岸线提取” 课题骨干

2012.01 – 2016.12 中科院“百人计划”项目“遥感图像融合机理与方法” 课题骨干

[1]. Lei Z., Li H.*, Zhao J., Jing L. et al., Individual tree species classification based on hierarchical convolutional neural networks and multitemporal Google Earth images. Remote Sensing, 2022, 14, 5124.

[2]. Guo X., Li H.*, Jing L., Wang P. Individual tree species classification based on convolutional neural networks and multitemporal high-resolution remote sensing images. Sensors, 2022, 22, 3157.

[3]. Li H., Hu B., Li Q., Jing L., CNN-based tree species classification using high-resolution satellite imagery and airborne LiDAR data. Forests, 2021, 12, 1697.

[4]. Zhao X., Li H., Wang P., Jing L., An image registration method using deep residual network features for multisource high-resolution remote sensing images. Remote Sens, 2021, 13, 3425.

[5]. Chen C., Jing L.*, Li H., Tang Y., A New Individual Tree Species Classification Method Based on the ResU-Net Model. Forests 2021, 12, 1202.

[6]. Wan H., Tang Y., Jing L., Li H., Qiu F., Wu W. Tree Species Classification of Forest Stands Using Multisource Remote Sensing Data. Remote Sens. 2021, 13,144.

[7]. Zhao X., Li H., Wang P. and Jing L., An image registration method of multisource high-resolution remote sensing images for earthquake disaster assessment. Sensors, 2020, 20(8):2286.

[8]. Qiu, L., Jing, L., Hu, B., Li, H., Tang, Y. 2020. A new individual tree crown delineation method for high resolution multispectral imagery. Remote Sensing, 12, 585.

[9]. Li H., Jing L., Image fusion framework considering mixed pixels and its application to pansharpening methods based on multiresolution analysis. Journal of Applied Remote Sensing 2020, 14(3):038501.

[10]. Li H., Jing L., Tang, Y., Ding, H., An improved pansharpening method for misaligned panchromatic and multispectral data, Sensors, 2018, 18(2): 557.

[11]. Li, H., Jing, L., Tang, Y., Wang, L. 2018. An image fusion method based on image segmentation for high-resolution remotely sensed imagery. Remote Sensing, 10(5): 790.

[12]. Gao, H., Tang, Y., Jing, L., Li, H., Ding, H. 2017. A novel unsupervised segmentation quality evaluation method for remote sensing images. Remote Sensing, 17(10): 2427.

[13]. Li, H., Jing, L. 2017. Improvement of a pansharpening method taking into account haze. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(11): 5039-5055.

[14]. Li, H., Jing, L., Tang, Y. 2017. Assessment of pansharpening methods applied to WorldView-2 imagery fusion. Sensors, 17(1): 89.

[15]. Li, H., Jing, L., Wang, L., Cheng, Q. 2016. Improved pansharpening with un-mixing of mixed MS sub-pixels near boundaries between vegetation and non-vegetation objects. Remote Sensing, 8(83): 1-24.

……

……