姚霞 教授

姚霞，教授，博士生导师。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，先后主持并参加国家自然科学基金、国家863计划子课题、国家科技支撑计划子课题等14项，已发表核心期刊论文60多篇，合作出版专著4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名本科生（其中1名学生获得校优秀本科生论文设计）、27篇文献综述和11项SRT计划；独立指导硕士研究生8名，协助指导博士生4名，硕士生10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”。同时担任Remote Sensing、ISPRS Journal of Photogrammetry and Remote Sensing、International Journal of Applied Earth Observation and Geoinformation、Field Crop Research等期刊的审稿人。

部分论著：

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）

发表论文：

Jiang J, Zhu J, Wang X, Cheng T, Tian Y, Zhu Y, Cao W, Yao X*. Estimating the leaf nitrogen content with a new feature extracted from the ultra-high spectral and spatial resolution images in wheat. Remote Sensing. 2021, 13(4): 739.

Jia, M., Colombo, R., Rossini, M., Celesti, M., Zhu, J., Cogliati, S., Cheng, T., Tian, Y., Zhu, Y., Cao, W., Yao, X*. 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. 2021.12:14.

Khan I1, Liu H1, Li W, Cao A, Wang X, Liu H, Cheng T, Tian Y, Zhu Y, Cao W, Yao X*. Early detection of powdery mildew disease and accurate quantification of its severity using hyperspectral images in wheat. Remote Sensing. 2021, 13(18): 3612.

Fang Y, Qiu X, Guo T, Wang Y, Cheng T , Zhu Y, Chen Q, Cao W, Yao X*, Niu Q, Hu Y, Gui L. An automatic method for counting wheat tiller number in the field with terrestrial LiDAR. Plant Methods. 2020, 16(1): 132.

Zhou M, Ma X, Wang K, Cheng T, Tian Y, Wang J, Zhu Y, Hu Y, Niu Q, Gui L, Yue C*, Yao X*. Detection of phenology using an improved shape model on time-series vegetation index in wheat. Computers and Electronics in Agriculture. 2020, 173: 105398

Jia M, Li D, Colombo R, Wang Y, Wang X, Cheng T, Zhu Y, Yao X*, Xu C, Ouer G, Li H, Zhang C. Quantifying chlorophyll fluorescence parameters from hyperspectral reflectance at the leaf scale under various nitrogen treatment regimes in winter wheat. Remote Sensing. 2019, 11: 2838.

Jia M, Li W, Wang K, Zhou C, Cheng T, Tian Y, Zhu Y, Cao W, Yao X*. A newly developed method to extract the optimal hyperspectral feature for monitoring leaf biomass in wheat. Computers and Electronics in Agriculture. 2019, 165: 104942.

Li W, Jiang J, Guo T, Zhou M, Tang Y, Wang Y, Zhang Y, Cheng T, Zhu Y, Cao W, Yao X*. Generating Red-Edge images at 3 M spatial resolution by fusing Sentinel-2 and Planet satellite products. Remote Sensing. 2019, 11(12):1422.

Jiang J, Cai W, Zheng H, Cheng T, Tian Y, Zhu Y, Ehsani R, Hu Y, Niu Q, Gui L, Yao X*. Using digital cameras on an unmanned aerial vehicle to derive optimum color vegetation indices for leaf nitrogen concentration monitoring in winter wheat. Remote Sensing. 2019, 11: 2667.

Jiang J, Zheng H, Ji X, Cheng T, Tian Y, Zhu Y, Cao W, Ehsani R, Yao X*. 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. 2019, 19, 747.

Guo T, Fang Y, Cheng T, Tian Y, Zhu Y, Chen Q, Qiu X, Yao X*. Detection of wheat height using optimized multi-scan mode of LiDAR during the entire growth stages. Computers and Electronics in Agriculture. 2019, 165: 104959.

Cao Z, Yao X, Liu H, Liu B, Cheng T, Tian Y, Cao W, Zhu Y*. Comparison of the abilities of vegetation indices and photosynthetic parameters to detect heat stress in wheat. Agricultural and Forest Meteorology. 2019. 65:121-136.

Zheng H, Li W, Jiang J, Liu Y, Cheng T, Tian Y, Zhu Y, Cao W, Zhang Y, Yao X *. A comparative assessment of different modeling algorithms for estimating leaf nitrogen content in winter wheat using multispectral images from an unmanned aerial vehicle. Remote Sensing. 2018. 10, 2026.

Jia M, Zhu J, Ma C, Alonso L, Li D, Cheng T, Tian Y, Zhu Y, Yao X*, Cao W*. Difference and potential of the upward and downward sun-induced chlorophyll fluorescence on detecting leaf nitrogen concentration in wheat. Remote Sensing. 2018, 10(8):1315.

Yao X, Si HY, Cheng T, Liu Y, Jia M, Tian YC, Chen CY, Liu SY, Chen Q, Zhu Y*. Spectroscopic estimation of leaf dry weight per ground area using vegetation indices and continuous wavelet analysis in wheat. Frontiers in Plant Science. 2018.01,360

Yao X, Wang N, Liu Y, Cheng T, Tian YC,Chen Q , Zhu Y. Accurate Estimation of LAI with Multispectral Imagery on Unmanned Aerial Vehicle (UAV) in Wheat. Remote sensing, 2017,9,1304

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.

Yao X, Huang Y, Shang G, Zhou C, Cheng T, Tian YC, Cao WX, Zhu Y. Evaluation of Six Algorithms to Monitor Wheat Leaf Nitrogen Concentration. Remote Sensing. 2015.7: 14939-14966.

Yao X, Huang Y, Shang G, Zhou C, Cheng T, Tian YC, Cao WX, Zhu Y. Evaluation of Six Algorithms to Monitor Wheat Leaf Nitrogen Concentration. Remote Sensing, 2015, 7: 14939-14966.

Yao X, Ren H, Cao ZH, Tian YC, Cao WX, Zhu Y, Chen T. Monitoring leaf nitrogen content in wheat with canopy hyperspectrum as influenced by soil background. International Journal of Applied Earth Observation and Geoinformation. 2014. 32 , 114-124

Yao X, Jia WQ, Si HY, Guo ZQ, Tian YC, Liu XJ, Cao WX, Zhu Y. Monitoring Leaf Equivalent Water Thickness based on Hyperspectrum in Wheat under Different Water and Nitrogen Treatments. PLOS ONE. 2014. 9(6):1-11

Yao X, Ata-Ul-Karim ST, Zhu Y, Tian YC, Liu XJ, Cao WX. Development of critical nitrogen dilution curve in rice based on leaf dry matter. European Journal of Agronomy. 2014. 55: 20- 28. (SCI)

Yao X, Zhao B, Tian YC, Liu XJ, Ni J, Cao WX, Zhu Y. Using leaf dry matter to quantify the critical nitrogen dilution curve for winter wheat in eastern China. Field Crops Research. 2014. 159: 33-42. (SCI)

Yao X, Zhu Y, Tian YC, Liu XJ, and Cao WX. Exploring hyperspectral bands and estimation indices for leaf nitrogen accumulation in wheat. International Journal of Applied Earth Observation and Geoinformation. 2010.12(2): 89-100. (SCI)

Yao X, Feng W, Zhu Y, Tian YC, and Cao WX. A non-destructive and real-time method of monitoring leaf nitrogen status in wheat. New Zealand of Agricultural Research. 2007. 50: 935-942. (SCI)

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):159-166。

周萌, 韩晓旭, 郑恒彪, 程涛, 田永超, 朱艳, 曹卫星, 姚霞*。基于参数化和非参数化法的棉花生物量高光谱遥感估算. 中国农业科学, 2021, 54(20): 4299-4311。

印玉明, 王永清, 马春晨, 郑恒彪, 程涛, 田永超, 朱艳, 曹卫星, 姚霞*。利用日光诱导叶绿素荧光监测水稻叶片叶绿素含量. 农业工程学报, 2021, 37(12): 169-180。

授权和公示国家发明专利：

1.一种基于三波段植被指数的小麦叶面积指数估算模型的构建方法，已授权，发明专利，ZL201610803703.7，姚霞、曹中盛、程涛、朱艳、田永超、马吉锋、张羽、王雪.

2.一种基于连续小波分析建立小麦叶干重定量模型的方法，已授权，发明专利， ZL201611116173.5，姚霞、朱艳、程涛、司海洋、田永超、马吉锋、张羽、邱小雷、王雪、曹卫星.

3.一种面向田块尺度作物生长监测的遥感影像时空融合方法，已授权，发明专利，ZL201811312555.4，程涛，江佳乐，姬旭升，姚霞，田永超，朱艳，曹卫星.

4.一种基于无人机多光谱影像的水稻地上部生物量估测方法, 已授权，发明专利，ZL201811267697.3, 朱艳、郑恒彪、程涛、姚霞、田永超、曹卫星.

5.田间作物表型监测机器人，已授权，发明专利，ZL201811273308.8, 倪军，袁华丽，朱艳，曹卫星，田永超，姚霞，姚立立，徐可，庞方荣.

6.Crop growth sensing apparatus and method supporting agricultural machinery variable quantity fertilization operations，US6540039，已授权，发明专利，Jun Ni, Weixing Cao, Yan Zhu, Shanshan Yu, Yongchao Tian, Xia Yao, Fangrong Pang, Lili Yao, Fang Liu.

7.一种不同PNC水平下小麦植株含水率的监测模型和方法,2013104226074, 已授权，发明专利，朱艳，姚霞，贾雯晴，田永超，刘小军，倪军，曹卫星.

科研项目：

主持和参加国家自然科学基金、国家863计划、国家科技支撑计划、省创新学者攀登计划、省自然科学基金、省科技支撑计划和省高技术等10多项。

常年接受从事农业遥感研究的硕士、博士研究生和博士后！尤其欢迎对高光谱影像、日光诱导叶绿素荧光、LiDAR、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报考或申请本团队，优先考虑积极向上，刻苦钻研、勇于探索的学生，男女不限！