姚霞，教授，博导电话：+86-25-84396565办公地点：生科楼A4009电子邮箱：yaoxia@njau.edu.cn研究领域：农情遥感监测研究兴趣：基于高光谱/日光诱导叶绿素荧光/无人机/激光雷达的作物生长监测；作物表型高通量获取非常欢迎接受从事农业遥感研究的硕士、博士研究生和博士后！尤其欢迎对日光诱导叶绿素荧光、LiDAR、高光谱影像、无人机遥感等感兴趣的同学加盟！欢迎具有遥感与GIS、植物生理学、农业信息学、计算机或测绘工程专业背景的学生加入本团队，优先考虑积极向上，刻苦钻研、勇于探索的学生，男女不限！2009年获南京农业大学农业信息学博士学位，2017年在美国夏威夷大学地理系做访问学者。主要围绕农情遥感监测理论与技术开展科研与教学工作。近五年来先后主持并参加6个国家自然科学基金、3个国家863计划子课题、2个国家科技支撑计划子课题、1个江苏省重点研发计划、2个省自然科学基金，已发表核心期刊论文60多篇，合作出版专著3部（其中1部为外文）；授权国家发明专利11项；登记国家计算机软件著作权6项。承担了2门本科生课程（农业信息学、农业遥感原理与技术），5门研究生课程；指导了20多名本科生（其中1名学生获得校优秀本科生论文设计）和11项SRT计划；指导研究生15名（其中1名硕士获省优秀硕士论文）。现任智慧农业系主任，负责博士和硕士研究生招生、面试、评奖评优、中期考核和毕业答辩等；作为秘书，配合学科负责人建设“农业信息学”省优势学科一期和二期项目；协助主任建设“国家信息农业工程技术中心”，参加“现代作物生产协同创新中心”的工作。获2016年江苏省高校“青蓝工程”中青年学术带头人称号。获2014年江苏省科技进步一等奖和2015年国家科技进步二等奖（排名第4）。获南京农业大学2010、2012、2013和2014年的年度考核“优秀”。任《Remote Sensing》和《International Journal of Precision Agricultural Aviation》编委，国际地球科学与遥感分会和江苏省遥感和地理信息系统成员。任国际期刊Remote Sensing of Environment, Remote Sensing, Field Crop Research, ISPRS Journal of Photogrammetry and Remote Sensing, International Journal of Applied Earth

Observation and Geoinformation的审稿人。其他社会职务南京农业大学智慧农业研究院副院长近期主要成果专著和教材1.专著：作物生长光谱监测. 科学出版社. 2020.（主编）2.专著：Estimating leaf nitrogen concentration of cereal crops with hyperspectral data. In: Prasad ST, John GL, Alfredo H. (eds.) Hyperspectral Remote Sensing of Vegetation. CRC Press, FL, USA. 2011.187-206.（参编）3.专著：数字农作技术. 科学出版社. 2008.（参编）4.教材：农业信息化技术导论.中国农业科学技术出版社. 2009.（参编）主要论文（仅列出第一作者和通讯作者文章）1.Yuan Fang, Xiaolei Qiu, Tai Guo, Yongqing Wang, Tao Cheng, Yan Zhu, Qi Chen, Weixing Cao, Xia Yao*,Qingsong Niu, Yongqiang Hu, and Lijuan Gui.An automatic method for counting wheat tiller number in the field withterrestrial LiDAR.Plant methods. 2020. Accepted.2.Jia, M., Colombo, R., Rossini, M., Celesti, M., Zhu, J., Cogliati, S., Cheng, T., Tian, Y., Zhu, Y., Cao, W., Yao, X*. 2020. Remote estimation of nitrogen content and photosynthetic nitrogen use efficiency in wheat leaf using sun-induced chlorophyll fluorescence at the leaf and canopy scales. European Journal of Agronomy. Accepted.3.Meng Zhou, Xue Ma, Kangkang Wang, Tao Cheng, Yongchao Tian, Jing Wang, Yan Zhu, Yongqiang Hu, Qingsong Niu, Lijuan Gui, Chunyu Yue and Xia Yao*. 2020.Detection of phenology using an improved shape model on time-series vegetation index in wheat. Computers and Electronics in Agriculture. Accepted.4.邱小雷，方圆，郭泰，程涛，朱艳，姚霞*。基于地基LiDAR高度指标的小麦生物量监测研究。农业机械学报，2019，50(10):159-1665.Min Jia, Dong Li, Roberto Colombo, Ying Wang, Xue Wang, Tao Cheng, Yan Zhu,Xia Yao*, Changjun Xu, Geli Ouer, Hongying Li, Chaokun Zhang. 2019. Quantifying chlorophyll fluorescence parameters from hyperspectral reflectance at the leaf scale under various nitrogen treatment regimes in winter wheat. Remote Sensing, 2019, 11, 2838; doi:10.3390/rs112328386.Min Jia, Wei Li, Kangkang Wang, Chen Zhou, Tao Cheng, Yongchao Tian, Yan Zhu, Weixing Cao and Xia Yao*. 2019. A newly developed method to extract the optimal hyperspectral feature for monitoring leaf biomass in wheat. Computers and Electronics in Agriculture, 165, 104942.7.Jiale Jiang, Weidi Cai, Hengbiao Zheng, Tao Cheng, Yongchao Tian, Yan Zhu, Reza Ehsani, Yongqiang Hu, Qingsong Niu, Lijuan Gui，Xia Yao*. 2019. Using digital cameras onan unmanned aerial vehicle to derive optimum color vegetationindices for leaf nitrogen concentration monitoring in winter wheat. Remote Sensing, 11, 2667; doi:10.3390/rs112226678.Jiale Jiang, Hengbiao Zheng, Xusheng Ji, Tao Cheng,Yongchao Tian, Yan Zhu, Weixing Cao, Reza Ehsani, Xia Yao*. 2019. Analysis and evaluation of the image preprocessing process of a Six-band multispectral camera mounted on an unmanned aerial vehicle for winter wheat monitoring. Sensors, 19, 747; doi:10.3390/s190307479.Tai Guo, Yuan Fang, Tao Cheng, Yongchao Tian, Yan Zhu, Qi Chen, Xiaolei Qiu and Xia Yao*. 2019. Detection of wheat height using optimized multi-scan mode of LiDAR during the entire growth stages. Computers and Electronics in Agriculture, 165, 10495910.Wei Li, Jiale Jiang,Tai Guo, Meng Zhou, Yining Tang, Ying Wang, Yu Zhang, Tao Cheng, Yan Zhu, Weixing Cao and Xia Yao*. 2019. Generating red-edge images at 3 m spatial resolution by fusing Sentinel-2 and Planet satellite products. Remote Sensing, 11(12),1422; doi:10.3390/rs1112142211.Cao Z, Yao X, Liu H, Liu B, Cheng T, Tian Y, Cao W, Zhu Y*. 2019. Comparison of the abilities of vegetation indices and photosynthetic parameters to detect heat stress in wheat. Agricultural and Forest Meteorology. 265:121-136.12.Min Jia, Jie Zhu, Chunchen Ma, Luis Alonso, Dong Li, Tao Cheng, Yongchao Tian, Yan Zhu, Xia Yao*,Weixing Cao*. 2018. Difference and Potential of the Upward and Downward Sun-Induced Chlorophyll Fluorescence on Detecting Leaf Nitrogen Concentration in Wheat. Remote Sensing. 10.1315.doi:10.3390/rs1008131513.X. Yao,HY. Si, T. Cheng, Y. liu, M. Jia, YC. Tian, CY. Chen, SY Liu, Q. Chen, Y. Zhu*. 2018. Spectroscopic estimation of leaf dry weight per ground area using vegetation indices and continuous wavelet analysis in wheat.Frontiers in Plant Science. 0136014.Xia Yao,Ni Wang, Yong Liu, Tao Cheng, Yong Chao Tian, Qi Chen and Yan Zhu. Accurate Estimation of LAI with Multispectral Imagery on Unmanned Aerial Vehicle (UAV) in Wheat. Remote sensing, 2017,9,130415.Cao Z,Cheng T, Ma X, Tian Y, Zhu Y, Yao X*, Chen Q, Liu S, Guo Z, Zhen Q. A new three-band spectral index for mitigating the saturation in the estimation of leaf area index in wheat. International Journal of Remote Sensing. 2017, 38(13): 3865-3885.16.X. Yao, Y. Huang, G. Shang, C. Zhou, T. Cheng, Y. Tian, W. Cao and Y. Zhu. 2015. Evaluation of Six Algorithms to Monitor Wheat Leaf Nitrogen Concentration. Remote Sensing. 7: 14939-14966.17.X. Yao, Y. Huang, G. Shang, C. Zhou, T. Cheng, Y. Tian, W. Cao and Y. Zhu. Evaluation of Six Algorithms to Monitor Wheat Leaf Nitrogen Concentration. Remote Sensing, 2015, 7: 14939-14966. 18.X. Yao, H. Ren, ZH. Cao, Y. Tian, W. Cao, Y. Zhu, T. Chen. 2014. Monitoring leaf nitrogen content in wheat with canopy hyperspectrum as influenced by soil background. International Journal of Applied Earth Observation and Geoinformation. 32 , 114-124 19.X. Yao,WQ. Jia, HY. Si, ZQ. Guo, YC. Tian, XJ. Liu, WX. Cao, Y. Zhu. 2014. Monitoring Leaf Equivalent Water Thickness based on Hyperspectrum in Wheat under Different Water and Nitrogen Treatments. PLOS ONE. 9(6):1-11 20.X. Yao,Syed Tahir Ata-Ul-Karim, Yan Zhu, Yongchao Tian, Xiaojun Liu, Weixing Cao. 2014. Development of critical nitrogen dilution curve in rice based on leaf dry matter. European Journal of Agronomy. 55: 20-28. (SCI) 21.X. Yao, Ben Zhao, YongChao Tian, XiaoJun Liu, Jun Ni, WeiXing Cao, Yan Zhu. 2014. Using leaf dry matter to quantify the critical nitrogen dilution curve for winter wheat in eastern China. Field Crops Research. 159: 33-42. (SCI) 22.姚霞，田永超，倪军，张玉森，曹卫星，朱艳．水稻叶片色素含量近红外光谱估测模型研究.分析化学. 2012. 40(4). 589-595. (SCI) 23.X. Yao,Zhu Y, Tian YC, Liu XJ, and Cao WX. 2010. Exploring hyperspectral bands and estimation indices for leaf nitrogen accumulation in wheat. International Journal of Applied Earth Observation and Geoinformation. 12(2): 89-100. (SCI) 24.X. Yao,Feng W, Zhu Y, Tian YC, and Cao WX. 2007. A non-destructive and real-time method of monitoring leaf nitrogen status in wheat. New Zealand of Agricultural Research. 50: 935-942. (SCI) 25.Ben Zhao, Xia Yao, YongChao Tian, XiaoJun Liu, Syed Tahir Ata-UI-Karim, Jun Ni, WeiXing Cao, Yan Zhu*. 2014. New Critical Nitrogen Curve Based on Leaf Area Index for Winter Wheat. (2014) Agronomy Journal. 106(2):379-389. (SCI) 26.Syed Tahir Ata-Ul-Karim, Xia Yao,Xiaojun Liu, Weixing Cao, Yan Zhu*. 2013. Development of critical nitrogen dilution curve of Japonica rice in Yangtze River Reaches. Field Crops Research. 149:149-158. (SCI) 27.Xinfeng Yao, Xia Yao, Wenqing Jia, Yongchao Tian, Jun Ni, Weixing Cao, and Yan Zhu*. 2013. Comparison and Intercalibration of Vegetation Indices from Different Sensors for Monitoring Plant Nitrogen Uptake in Wheat. Sensors. 13(3)：3109-3130(SCI) 28.Xinfeng Yao, Xia Yao, Yongchao Tian, Jun Ni, Weixing Cao, and Yan Zhu*. 2013. A New Method to DetermineCentral Wavelength and Optimal Bandwidth for Predicting Plant Nitrogen Uptake in Wheat. Journal of Integrative Agriculture. 12(5): 101-115(SCI) 29.Wang W, Yao X, Yao XF, Tian YC, Liu XJ, Ni J, Cao WX and Zhu Y. 2012. Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. Field Crops Research. 129: 90-98. (SCI) 30.Wang W, Yao X, Liu XJ, Tian YC, Ni J, Cao WX and Zhu Y*. 2012. Common spectral bands and optimum vegetation indices for monitoring leaf nitrogen accumulation in rice and wheat. Journal of Integrative Agriculture. 11(12): 101-108. (SCI) 31.Tian YC, Yao X, Yang J, Cao WX, Hannaway DB, Zhu Y. 2011. Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground-andspace-based hyperspectral reflectance. Field Crops Research, 120: 299-310. (SCI) 32.Feng W, Yao X,Zhu Y, Tian YC, Cao WX. 2008. Monitoring leaf nitrogen status with hyperspectral reflectance in wheat. European Journal of Agronomy. (28): 394-404. (SCI) 33.Feng W, Yao X,Tian YC, Cao WX, and Zhu Y. 2008. Monitoring leaf pigment status with hyperspectral remote sensing in wheat. Australian Journal of Agricultural Research. (59): 748-760. (SCI) 34.Zhu Y, Yao X, Tian YC, Liu XJ, Cao WX. 2008. Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice. International Journal of Applied Earth Observation and Geoinformation. (10): 1-10. (SCI) 35.姚霞, 王雪, 黄宇, 汤守鹏, 田永超, 朱艳*, 曹卫星. 应用近红外光谱法估测小麦叶片糖氮比. 应用生态学报, 2015, 26(8): 2371-2378.36.姚霞,刘小军, 田永超, 曹卫星, 朱艳*, 张羽. 基于星载通道光谱指数与小麦冠层叶片氮素营养指标的定量关系. 应用生态学报, 2013, 24(2): 431-437. 37.姚霞，刘小军，王薇，倪军，曹卫星，朱艳．小麦氮素无损监测仪敏感波长的最佳波段宽度研究．农业机械学报．2011，42（2）:162-167. (EI) 38.姚霞，汤守鹏，田永超，曹卫星，朱艳．应用近红外光谱估测小麦叶片氮含量. 植物生态学报. 2011. 35 (8): 844-852. 39.姚霞，田永超，刘小军，曹卫星，朱艳．不同算法红边位置监测小麦冠层氮素营养指标的比较．中国农业科学．2010，43(13)：2661-2667．40.姚霞，刘小军，王薇，田永超，曹卫星，朱艳.基于减量精细采样法探究估算小麦叶片氮积累量的最佳归一化光谱指数．应用生态学报．2010，21(12)：3175-3182．41.姚霞，朱艳，冯伟，田永超，曹卫星．监测小麦叶片氮积累量的新高光谱特征波段及比值植被指数．光谱学与光谱分析．2009，29(8)：2191-2195. (SCI/EI) 42.姚霞，朱艳，田永超，冯伟，曹卫星．小麦叶层氮含量估测的最佳高光谱参数研究．中国农业科学．2009，42(8)：2716-2725．43.姚霞，吴华兵，朱艳，田永超，周治国，曹卫星．棉花功能叶片色素含量与高光谱参数的相关性研究．棉花学报．2007，19(4)：267-272．44.冯伟，姚霞，田永超，朱艳，李映雪，曹卫星．基于高光谱遥感的小麦叶片糖氮比监测．中国农业科学．2008，41(6)：1630-1639．45.冯伟，姚霞，田永超，朱艳，刘小军，曹卫星．小麦籽粒蛋白质含量高光谱预测模型研究．作物学报．2007，33(12)：1935-1942．46.张玉森，姚霞，田永超，曹卫星，朱艳．应用近红外光谱预测水稻叶片氮含量．植物生态学报．2010，34(6)：704-712．授权和公示国家发明专利1.一种土壤背景干扰下小麦叶层氮含量光谱监测模型及建模方法，已授权，发明专利，ZL201310227380.8，姚霞，朱艳，田永超，曹卫星，孙传范2.一种小麦叶片等效水厚度高光谱监测方法，已授权，发明专利，ZL201310382064.8，姚霞，朱艳，贾雯晴，田永超，刘小军，倪军，曹卫星3.一种基于三波段光谱指数估测植物氮含量的方法，已授权，发明专利，ZL 201110278513.5，朱艳，姚霞，王薇，曹卫星，田永超，倪军，刘小军，孙传范4.一种基于光谱技术的小麦叶片糖氮比快速检测方法，已授权，发明专利，ZL 201010543330.7，朱艳，姚霞，倪军，田永超，汤守鹏，王薇，曹卫星5.一种稻麦叶片氮含量光谱监测模型建模方法，已授权，发明专利，ZL 201110033113.8，曹卫星，王薇，姚霞，朱艳，倪军，田永超，刘小军6.一种确定小麦植株吸氮量核心波段的方法，已受理，发明专利，201210109597.4 ，姚霞，朱艳，姚鑫锋，田永超，倪军，曹卫星7.一种土壤背景干扰下小麦叶层氮含量光谱监测模型及建模方法，已受理，发明专利，201310215439.1，姚霞，朱艳，任海建，田永超，曹卫星，孙传范8.一种小麦叶片等效水厚度高光谱监测方法，已受理，发明专利，201310382064.8，姚霞，朱艳，贾雯晴，田永超，刘小军，倪军，曹卫星9.一种基于冠层高光谱指数的小麦植株水分监测方法，已受理，发明专利，201110368757.2，朱艳，姚霞，韩刚，田永超，刘小军，王薇，倪军，曹卫星10.一种不同植株氮含量水平下小麦植株含水率的监测方法，已受理，发明专利，201310422607.4，朱艳，姚霞，贾雯晴，田永超，刘小军，倪军，曹卫星11.一种根据小麦植株吸氮量核心波长确定适宜带宽的方法，已受理，发明专利，201210109596.X，朱艳，姚鑫锋，姚霞，田永超，倪军，曹卫星学术研究表彰/奖励1.稻麦生长指标光谱监测与定量诊断技术．国家科技进步二等奖，2015年2.稻麦生长指标光谱监测与定量诊断技术．江苏省科技进步一等奖，2014年3.基于模型的作物生长预测与精确管理技术．国家科技进步二等奖，2008年4.作物管理知识模型系统的构建与应用．中国高校科技进步一等奖，2007年专业学会1.IEEE,Geoscience and Remote Sensing Society2.Union of RS and GIS in Jiangsu province, China