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刘婧 副教授    

 

1、个人基本情况

 

刘婧,女,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)


6、承担(参与)的主要科研项目

1)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,2021.012023.1224万元,结题,主持

2)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,2020.072023.0620万元,结题,主持

3)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,2019.102022.1015万元,结题,主持

4)江苏省双创博士计划,15万,结题,主持

5)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,2021.012024.12264万,在研,参加

6)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,2021.092024.12在研,参加

7)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,2014.012017.1275万元,结题,参加

 


7、近年发表的期刊论文(*通讯作者)

 

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 Articlehttps://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