1、个人基本情况
刘婧,女,陕西宝鸡人,副教授,硕士研究生导师,江苏省双创博士。担任国际数字地球学会激光雷达专业委员会委员,中国自然资源学会资源制图专业委员会委员,中国遥感应用协会女科技工作者工委会委员,苏港澳高校遥感与环境专业联盟委员会委员,Plant Phenomics期刊青年编委。Remote Sensing of Environment, ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, Agricultural and Forest Meteorology等期刊审稿人
2、研究方向
1)激光雷达遥感:应用多尺度(地基、机载、星载)激光雷达对地观测的算法研发与应用,如森林资源调查、地形测绘、城市土地覆盖分类等
2)植被遥感:基于多源遥感技术的森林结构参数定量反演,虚拟森林环境建模,及其在林业资源管理及陆地生态系统碳循环中的应用
3)点云智能处理:点云特征提取、分割分类、三维建模的算法研发
欢迎具有遥感、测绘或GIS背景,有志于进行科学研究的同学报考我们团队的硕士和博士研究生
招生专业:地图学与地理信息系统、测绘科学与技术、地理环境遥感、资源与环境工程硕士
3、工作经历
2020.07至今,南京师范大学,地理科学学院,副教授
2019.09~2020.07,南京师范大学,地理科学学院,讲师
4、教育经历
2014.09~2019.05,荷兰特文特大学国际地理信息科学与地球观测学院ITC,自然资源,博士
2015.09~2019.05,澳大利亚墨尔本皇家理工大学理学院,地球空间科学,博士
2011.09~2014.06,北京大学地球与空间科学学院,摄影测量与遥感,工学硕士
2007.09~2011.06,南京大学地理与海洋科学学院,地理信息系统,理学学士
5、荣誉获奖
1)2023,全国高等学校测绘学科教学创新与育才能力大赛青年教师讲课竞赛,特等奖
2)2023,第七届全国激光雷达大会数据处理大赛,特等奖(指导老师)
3)2020,第九届全国大学生GIS应用技能大赛,特等奖(指导老师)
4)2024,全国大学生测绘学科创新创业智能大赛创新开发比赛,二等奖(指导老师)
5)2023,南京师范大学研究生科技文化活动,优秀指导教师
6)2018,Remote Sensing Travel Award
7)2012,第七届中国青年遥感辩论会优秀辩论员
8)2011,南京大学优秀毕业生
6、承担(参与)的主要科研项目
- 国家自然科学基金委员会,面上项目,42471418,联合星载全波形与光子计数激光雷达的森林叶面积垂直分布反演,2025.01至2028.12,在研,主持
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- 江苏省基础研究计划,面上项目,BK20241884,融合激光雷达与高光谱数据的陆地生态系统总初级生产力遥感监测,2024.07至2027.06,在研,主持
- 遥感科学国家重点实验室,开放基金,OFSLRSS202431,顾及植被聚集效应的星载激光雷达森林叶面积垂直分布反演,2025.01至2026.12,在研,主持
- 国家自然科学基金委员会,青年科学基金项目,42001284,顾及森林冠层内部结构和外部轮廓异质性的叶面积指数垂直分布探测,2021.01至2023.12,结题,主持
- 江苏省基础研究计划,青年科学基金项目,基于多源遥感数据的长三角地区植被三维分布探测,2020.07至2023.06,结题,主持
- 南京师范大学引进人才科研启动项目,基于地基激光雷达的森林叶面积指数地面测量方法研究,2019.10至2022.10,结题,主持
- 江苏省双创博士计划,结题,主持
- 国家自然科学基金委员会,NSFC-新疆联合基金重点项目,塔里木河流域生态系统耗水-社会经济用水-水资源的协同与优化研究,2021.01至2024.12,在研,参加
- 江苏省高校优秀科技创新团队,人地系统耦合建模与可持续性评估,2021.09至2024.12在研,参加
- 国家自然科学基金委员会,面上项目,41371329,基于类别多点时空转换概率和决策融合的变化检测,2014.01至2017.12,结题,参加
7、近年发表的期刊论文(*通讯作者)
Wang, Z., Liu, J.*, Sheng, Y. & Yang, X. 2024. Intercomparison of the DART model and GEDI simulator for simulating GEDI waveforms in forests. International Journal of Applied Earth Observation and Geoinformation 134, 104148, https://doi.org/10.1016/j.jag.2024.104148
He, Z., Liu, J.*, Yang, S. 2024. DE-Net: A Dual-Encoder Network for Local and Long-Distance Context Information Extraction in Semantic Segmentation of Large-Scale Scene Point Clouds. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, https://ieeexplore.ieee.org/document/10652235.
Wang Z., Chen H.*, Liu J.*, et al. Multilevel intuitive attention neural network for airborne LiDAR point cloud semantic segmentation. International Journal of Applied Earth Observation and Geoinformation, 2024; 132:104020. https://doi.org/10.1016/j.jag.2024.104020
Han D., Liu J.*, Zhang R., et al. Evaluation of the SAIL Radiative Transfer Model for Simulating Canopy Reflectance of Row Crop Canopies. Remote Sensing. 2023; 15(23):5433. https://doi.org/10.3390/rs15235433
Wang J., Liu J.*, Li L. Detecting Photovoltaic Installations in Diverse Landscapes Using Open Multi-Source Remote Sensing Data. Remote Sensing. 2022; 14(24):6296. https://doi.org/10.3390/rs14246296
雷秋佳,刘婧*,曹新运.利用机载LiDAR数据的开放DEM产品精度评估. 武汉大学学报(信息科学版). https://doi.org/10.13203/j.whugis20220421
Liu, J.*, Li, L., Akerblom, M., Wang, T., Skidmore, A., Zhu, X., & Heurich, M. 2021. Comparative Evaluation of Algorithms for Leaf Area Index Estimation from Digital Hemispherical Photography through Virtual Forests. Remote Sensing, 2021, 13(16), 3325 https://doi.org/10.3390/rs13163325
Liu, J.*, Wang, T., Skidmore, A.K., Jones, S., Heurich, M., Beudert, B., Premier, J., 2019. Comparison of terrestrial LiDAR and digital hemispherical photography for estimating leaf angle distribution in European broadleaf beech forests, ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 158: 76-89. https://doi.org/10.1016/j.isprsjprs.2019.09.015
Liu, J.*, Skidmore, A.K., Wang, T., Zhu, X., Premier, J., Heurich, M., Beudert, B., Jones, S., 2019. Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest. ISPRS Journal of Photogrammetry and Remote Sensing, 148, 208-220. (入选期刊Featured Article) https://doi.org/10.1016/j.isprsjprs.2019.01.005
Liu, J.*, Skidmore, A.K., Jones, S., Wang, T., Heurich, M., Zhu, X., Shi, Y., 2018. Large off-nadir scan angle of airborne LiDAR can severely affect the estimates of forest structure metrics. ISPRS Journal of Photogrammetry and Remote Sensing, 136, 13-25. (入选期刊Featured Article) https://doi.org/10.1016/j.isprsjprs.2017.12.004
Liu, J.*, Skidmore, A.K., Heurich, M., Wang, T.*, 2017. Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests. ISPRS Journal of Photogrammetry and Remote Sensing, 132, 77-87. (入选期刊Featured Article) https://doi.org/10.1016/j.isprsjprs.2017.08.005
Liu, J., Li, P.*, Wang, X., 2015.A new segmentation method for very high resolution imagery using spectral and morphological information. ISPRS Journal of Photogrammetry and Remote Sensing, 101, 145-162. https://doi.org/10.1016/j.isprsjprs.2014.11.009
Zhu, X.*, Liu, J., Skidmore, A.K., Premier, J., Heurich, M., 2020. A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data. Remote Sensing of Environment, 240, 111696. https://doi.org/10.1016/j.rse.2020.111696
Wang, D., Wan, B.*, Liu, J., Su, Y., Guo, Q., Qiu, P., Wu, X., 2020. Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery. International Journal of Applied Earth Observation and Geoinformation, 85, 101986. https://doi.org/10.1016/j.jag.2019.101986
Zhu, X.*, Skidmore, A.K., Wang, T., Liu, J., Darvishzadeh, R., Shi, Y., Premier, J., Heurich, M., 2018. Improving leaf area index (LAI) estimation by correcting for clumping and woody effects using terrestrial laser scanning. Agricultural and Forest Meteorology, 263, 276-286. https://doi.org/10.1016/j.agrformet.2018.08.026
Zhu, X., Skidmore, A.K., Darvishzadeh., R., Niemann, K., Liu, J., Shi, Y., Wang, T., 2018. Foliar and woody materials discriminated using terrestrial LiDAR in a mixed natural forest. International Journal of Applied Earth Observation and Geoinformation, 64, 43-50. https://doi.org/10.1016/j.jag.2017.09.004
Zhu, X., Wang, T., Skidmore, A.K., Darvishzadeh., R., Niemann, K., Liu, J., 2017. Canopy leaf water content estimated using terrestrial LiDAR. Agricultural and Forest Meteorology, 232, 152-162. https://doi.org/10.1016/j.agrformet.2016.08.016
8、专利软件
一种基于机载点云数据的大范围建筑光伏潜力计算方法, 中国专利(CN118570023A),已公开、实质审查
基于局部和长距离上下文信息的大规模点云语义分割方法, 中国专利(CN118135212A),已公开、实质审查