Curriculum Vitae

Xia YAO (姚霞), Ph.D.

Professor

College of Agriculture, National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University (NAU)

Rm. A4009, Biology Building, 1 Weigang Rd, Nanjing, Jiangsu 210095, P. R. China

Tel: +86-25-84396565, Fax: +86-25-84396672, Mobile: 13952028787

Email: yaoxia@njau.edu.cn,

Web: http://www.netcia.org.cn/XiaYao.html; http://www.netcia.org.cn/XiaYao_cn.html

Research Interests

n Crop growth/biotic/abiotic stress/senescence monitoring based on SIF

n Active remote sensing (LiDAR) of vegetation

n Unmanned aerial vehicles (UAVs) of vegetation

n Hyperspectral remote sensing of vegetation

n Quantification of crop biophysical/biochemical properties

n Field ecosystem dynamics

n Crop-land use change

n Vegetation mapping

Education

n 2006, 9- 2009, 9 PhD, Crop Informatics, NAU, China

n 2001, 9- 2004, 7 MS, Ecology, NAU, China

n 1997, 9- 2001, 7 BS, Agronomy, NAU, China

Work Experience

n 2017.01-2017.12 Visiting professor, Dep. Of Geography, UH., China

n 2015, 1 – Professor, College of Agriculture, NAU, China

n 2010, 1 – 2014,12 Associate Professor, College of Agriculture, NAU, China

n 2007, 1 - 2009, 12 Lecturer, College of Agriculture, NAU, China

n 2004, 7 - 2006, 12 Teaching Assistant, College of Agriculture, NAU, China

n Joint investigator

Ø National Natural Science Foundation of China: Monitoring mechanism and estimation model of nitrogen nutrition in wheat based on hyperspectra; Monitoring mechanism of nitrogen nutrition in rice based on reflectance spectra

Ø PhD Program Grant of China: The non-destructive monitoring mechanism of nitrogen nutrition in wheat based on hyperspectra

Ø Natural Science Foundation of Jiangsu Province: The mechanism of monitoring and diagnosis of crop nitrogen nutrition by non-destructive method

Ø High Technology Program of Jiangsu Province: Monitoring growth status and forecasting productivity in rice

Publications ( * note the correspond author)

(1). Zhou M., Zheng H., He C., Liu P., Mustafa G., Wang X., Cheng T., Zhu Y., Cao W., Yao X.*. Wheat phenology detection with the methodology of classification based on the time-series UAV images. Field Crops Research. 2023, 292:108798.

(2). Mustafa G., Zheng H., Li W., Yin Y., Wang Y., Zhou M., Liu P., Bilal M., Jia H., Li.G, Cheng T., Tian Y., Cao W., Zhu Y.*, Yao X.*. Fusarium head blight monitoring in wheat ears using machine learning and multimodal data from asymptomatic to symptomatic periods. Frontiers in Plant Science.2023, doi: 10.3389/fpls.2022.1102341

(3). Mustafa G., Zheng H., Khan I., Tian L., Jia H., Li G., Cheng T., Tian Y., Cao W., Zhu Y.*, Yao X.*. Hyperspectral reflectance proxies to diagnose in-field fusarium head blight in wheat with machine learning. Remote Sensing. 2022, 14(12): 2784.

(4). Jiang J., Liu H., Zhao C., He C., Ma J., Cheng T., Zhu Y., Cao W., Yao X.*. Evaluation of diverse convolutional neural networks and training strategies for wheat leaf disease identification with field-acquired photographs. Remote Sensing. 2022, 14(14): 3446.

(5). Khan, I.H., Liu, H., 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, 3612. https://doi.org/10.3390/rs13183612

(6). Min Jia, Colombo Roberto, Micol Rossini, Marco Celesti, Jie Zhu, Sergio Cogliati, Tao Cheng, Yongchao Tian, Yan Zhu, Weixing Cao, Xia Yao*. 2021. 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.12:14.

(7). Yuang Fang, Xiaolei Qiu, Tai Guo, Yongqing Wang , Tao Cheng , Yan Zhu, Qi Chen, Weixing Cao, Xia Yao*, Qingsong Niu, Yongqiang Hu, Lijuan Gui. 2020. An automatic method for counting wheat tiller number in the field with terrestrial LiDAR. Plant Methods. 16(1): 132.

(8). Meng Zhou, Xue Ma, Kangkang Wang, Tao Cheng, Yongchao Tian, Jing Wang, Yan Zhu, Yongqiang Hu, Qingsong Niu, Lijuan Gui, Chunyu Yue*, Xia Yao*. 2020. Detection of phenology using an improved shape model on time-series vegetation index in wheat. Computers and Electronics in Agriculture.173: 105398

(9). 邱小雷，方圆，郭泰，程涛，朱艳，姚霞*。2019，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， 50(10):159-166

(10). 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 Sens. Remote Sensing. 11, 2838; doi:10.3390/rs11232838

(11). 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.

(12). 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 on an Unmanned Aerial Vehicle to Derive Optimum Color Vegetation Indices for Leaf Nitrogen Concentration Monitoring in Winter Wheat. Remote Sensing, 11, 2667; doi:10.3390/rs11222667

(13). 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/s19030747

(14). 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, 104959

(15). 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/rs11121422

(16). 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.

(17). H. Liu, N.Wang, T. Cheng, Q. Chen, YC. Tian, Y. Zhu, X. Yao*. 2019. Extract the Features to Detect the Wheat Powdery Mildew (Blumeriagraminis Speer) at Early Stage on the Sub-window Permutation Algorithm. To be submitted.

(18). Y. Liu, N.Wang, T. Cheng, Q. Chen, YC. Tian, Y. Zhu, X. Yao*.2019. A new colour index to monitoring nitrogen status on unmanned aerial vehicle system in wheat. International Journal of Applied Earth Observation and Geoinformation.

(19). C. Zhou, M. Jia, T. Cheng, YC. Tian, Q. Chen, Y. Zhu X. Yao*. 2019. Selection of sensitive spectral feature to monitor wheat leaf biomass from the near ground hyperspectral image. Computers and Electronics in Agriculture. To be submitted.

(20). 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/rs10081315

(21). 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.01360

(22). 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, 2017,9,1304

(23). 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.

(24). Chen Jiayue, Yao Xia, Huang Fen*, Liu Yong, Yu Qi, Wang Ni, Xu Huanliang, Zhu Yan. 2016. N status monitoring model in winter wheat based on image processing. Transactions of the Chinese Society of Agricultural Engineering.32. 4: 163-170 (EI)

(25). 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.

(26). X. Yao, HJ. Ren, ZS. Cao, YC. Tian, WX. Cao, Y. Zhu*, T. Chen. 2014. Detecting leaf nitrogen content in wheat with canopy hyperspectrum under different soil backgrounds. International Journal of Applied Earth Observation and Geoinformation. 32: 114-124.

(27). 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.

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

(29). X. Yao, B. Zhao, YC. Tian, XJ. Liu, J. Ni, WX. Cao, Y. 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)

(30). X. Yao, Y. Zhu, YC. Tian, XJ. Liu, WX. Cao*. 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)

(31). X. Yao, YC. Tian, J. Ni, Y. Zhang, WX. Cao*, Y. Zhu. 2012. Estimation of leaf pigment concentration in rice by near infrared reflectance spectroscopy. Chinese Journal of Analytical Chemistry. 40(4): 589-595. (SCI) (In Chinese)

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

(33). B. Zhao, X. Yao, YC. Tian, XJ. Liu, ST Ata-UI-Karim, J. Ni, WX. Cao, Y. Zhu*. 2014. New critical nitrogen curve based on leaf area index for winter wheat. Agronomy Journal. 106(2): 379-389. (SCI)

(34). ST Ata-UI-Karim, X. Yao, XJ. Liu, WX. Cao, Y. Zhu*. 2013. Development of critical nitrogen dilution curve of japonica rice in yangtze river reaches. Field Crops Research. 149: 149-158. (SCI)

(35). XF. Yao, X. Yao, WQ. Jia, YC. Tian, J. Ni, WX. Cao, Y. Zhu*. 2013. Comparison and inter calibration of vegetation indices from different sensors for monitoring plant nitrogen uptake in wheat. Sensors. 13(3): 3109-3130. (SCI)

(36). XF. Yao, X. Yao, YC. Tian, J. Ni, WX. Cao, Y. Zhu*. 2013. A new method to determine central wavelength and optimal bandwidth for predicting plant nitrogen uptake in wheat. Journal of Integrative Agriculture. 12(5): 101-115. (SCI, IF=0.449)

(37). W. Wang, X. Yao, XJ. Liu, YC. Tian, J. Ni, WX. Cao, Y. Zhu*. 2012. Common spectral bands and optimum vegetation indices for monitoring leaf nitrogen accumulation in rice and wheat. Agricultural Sciences in China. 11(12): 101-108. (SCI)

(38). W. Wang, X. Yao, XF. Yao, YC. Tian, XJ. Liu, J. Ni, WX. Cao, Y. Zhu*. 2012. Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. Field Crops Research. 129: 90-98. (SCI)

(39). YC. Tian, X. Yao, J. Yang, WX. Cao, Hannaway DB, Y. Zhu. 2011. Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance. Field Crops Research. 120: 299-310. (SCI)

(40). YC. Tian, X. Yao, J. Yang, WX. Cao, and Y. Zhu*. 2011. Extracting red edge position parameters from ground-and space-based hyperspectral data for estimation of canopy leaf nitrogen concentration in rice. Plant Production Science. 14(3): 270-281. (SCI)

(41). W. Feng, X. Yao, Y. Zhu, YC. Tian, WX. Cao. 2008. Monitoring leaf nitrogen status with hyperspectral reflectance in wheat. European Journal of Agronomy. (28): 394-404. (SCI)

(42). W. Feng, X. Yao, YC. Tian, WX. Cao, Y. Zhu. 2008. Monitoring leaf pigment status with hyperspectral remote sensing in wheat. Australian Journal of Agricultural Research. (59): 748-760. (SCI)

(43). Y. Zhu, X. Yao, YC. Tian, XJ. Liu, WX. Cao. 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)

(44). YC. Tian, JJ. Zhang, X. Yao, WX. Cao, Y. Zhu*. 2013. Laboratory assessment of three quantitative methods for estimating the organic matter content of soils in China based on visible/near-infrared reflectance spectra. Geoderma. 202-203: 161-170. (SCI)

(45). QC. Chen, YC. Tian, X. Yao, WX. Cao, Y. Zhu*. 2014. Comparison of nitrogen dressing approaches to optimize rice growth. Plant Production Science. Plant. 17: 66-80. (SCI)

(46). X. Yao, Y. Zhu, YC. Tian, W. Feng, WX. Cao*. 2013. Research of the optimum hyperspectral vegetation indices on monitoring the nitrogen content in wheat leaves. Scientia Agricultura Sinica. 42(8): 2716-2725. (In Chinese)

(47). X. Yao, XJ. Liu, W. Wang, J. Ni, WX. Cao, Y. Zhu*. 2011. Optimal bandwidths of sensitive bands for portable nitrogen monitoring instrument in wheat. Transactions of the Chinese Society for Agricultural Machinery. 42(2): 162-167. (EI) (In Chinese)

(48). X. Yao, SP. Tang, WX. Cao, YC. Tian, Y. Zhu*. 2011. Estimating the nitrogen content in wheat leaves by near-infrared reflectance spectroscopy. Chinese Journal of Plant Ecology. 35(8): 844-852. (In Chinese)

(49). X. Yao, YC. Tian, XJ. Liu, WX. Cao, Y. Zhu*. 2010. Comparative study on monitoring canopy leaf nitrogen status on red edge position with different algorithms in wheat. Scientia Agricultura Sinica. 43(13): 2661-2667. (In Chinese)

(50). X. Yao, XJ. Liu, W. Wang, YC. Tian, WX. Cao, Y. Zhu*. 2010. Estimation of optimum normalized difference spectral index for nitrogen accumulation in wheat leaf based on reduced precise sampling method. Chinese Journal of Applied Ecology. 21(12): 3175-3182. (In Chinese)

(51). X. Yao, Y. Zhu, W. Feng, YC. Tian, WX. Cao*. 2009. Exploring novel hyperspectral band and key index for leaf nitrogen accumulation in wheat. Spectroscopy and Spectral Analysis. 29(8): 2191-2195. (SCI/EI) (In Chinese)

(52). X. Yao, HB. WU, Y. Zhu, YC. Tian, ZG. Zhou, WX. Cao*. 2007. Relationship between pigment concentrations and hyperspectral parameters in functional leaves of cotton. Cotton Science. 19(4): 267-272. (In Chinese)

(53). X. Yao, XM. Bian, HG. Peng, WX. Cao, Y. Zhu, WJ. Zhang*. 2007. ARIMA time series modeling and applying on fresh agricultural products. System Sciences and Comprehensive Studies in Agriculture. 2007.23(1): 89-94. (In Chinese)

(54). J. Ni, X. Yao, YC. Tian, WX. Cao, Y. Zhu*. 2013. Design and experiments of portable apparatus for plant growth monitoring and diagnosis. Transactions of the Chinese Society of Agricultural Engineering. 29(6): 150-156. (EI) (In Chinese)

(55). YS. Zhang, X. Yao, YC. Tian, WX. Cao, Y. Zhu*. 2010. Estimating leaf nitrogen content with near infrared reflectance spectroscopy in rice. Chinese Journal of Plant Ecology. 34(6): 704-712. (In Chinese)

(56). W. Feng, X. Yao, YC. Tian, Y. Zhu, YX. Li, WX. Cao*. 2008. Monitoring the sugar to nitrogen ratio in wheat leaves with hyperspectral remote sensing. Scientia Agricultura Sinica. 41(6): 1630-1639. (In Chinese)

(57). W. Feng, X. Yao, YC. Tian, Y. Zhu, XJ. Liu, and WX. Cao*. 2008. Predicting grain protein content with canopy hyperspectral remote sensing in wheat. Acta Agronomica Sinica. 33(12): 1935-1942. (In Chinese)

(58). Y. Zhu, X. Yao, YC. Tian, DQ. Zhou, YX. Li, WX. Cao*. 2006. Quantitative relationship between leaf nitrogen accumulation and canopy reflectance spectra in rice and wheat. Journal of Plant Ecology. 30(6): 983-990. (In Chinese)

(59). HG. Peng, X. Yao, Y. Zhu, WX. Cao*. 2005. Design and implementation of a knowledge model system for decision making on cropping system. Journal of Nanjing Agricultural University. 28 (2): 125-128. (In Chinese)

(60). J. Ni, TT. Wang, X. Yao, WX. Cao, Y. Zhu*. 2013. Design and experiments of multi-spectral sensor for rice and wheat growth information. Transactions of the Chinese Society for Agricultural Machinery. 44(5): 207-212. (EI). (In Chinese)

(61). YC. Tian, JJ. Zhang, X. Yao, WX. Cao, Y. Zhu*. 2012. Quantitative modeling method of soil organic matter content based on near-infrared photo acoustic spectroscopy. Transactions of the Chinese Society of Agricultural Engineering. 28(1): 145-152. (EI) (In Chinese)

Monograph & Textbook

(1). Monograph: Spectral Sensing of Crop Growth. Science Press. 2020. (Co-editor)

(2). Monograph: 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. (One chapter)

(3). Textbook: An Introduction to Agricultural Information Technology. Agricultural Science and Technology Press. China. 2009. (Co-editor)

(4). Monograph: Digital Farming Technology. Science Press. 2008. (Co-editor)

Teaching Experience

l Agricultural Remote Sensing (Graduate, Teaching in English)

l Advanced Crop Informatics (Graduate)

l Research Progress on Information Agriculture (Graduate)

l Crop High Yield Theory and Technology (Graduate)

l Agricultural Remote Sensing (Undergraduate)

l Introduction to Information Agriculture (Undergraduate)

Research Experience

n Principal investigator

Ø National Key Research and Development Program of China, Research on advanced remote sensing monitoring method of agricultural conditions under GEOGLAM framework

Ø National Natural Science Foundation, Mechanism and method for estimating the productivity with solar-induced chlorophyll fluorescence under the stress of high temperature and drought in wheat

Ø Key Research and Development Program of Jiangsu Province, Research and development of high-throughput acquisition technology and system in rice and wheat crop phenotypes

Ø National Natural Science Foundation, Detecting leaf nitrogen status on the sun-induced chlorophyll fluorescence (SIF) in wheat

Ø National Natural Science Foundation, Spectral monitoring mechanism and estimating model for post-heading leaf senescence in wheat

Ø Natural Science Foundation of Jiangsu Province, Study on non-destructive monitoring of water status in wheat using hyperspectra

Ø Natural Science Foundation of Jiangsu Province, Detection of wheat senescence under heat stress at heading stage from leaf reflectance spectra

Ø National Science and Technology Support Plan, Development and application of new sensors for diagnosis of crop nutrition

Ø National High-tech R&D (863) Plan, Development and application of smart management technology for safe crop production

Ø Science and Technology Support Plan of Jiangsu Province, Research and development of rice growth sensing and smart management technology

Invention Patents

(1). A method for constructing estimation model of leaf area index with three-band vegetation index in wheat (1/8)

(2). A method for establish quantitative model of leaf dry weight with continuous wavelet analysis in wheat (1/10)

(3). A method for crop growth monitoring with remote sensing images space-time fusion in field scale(4/7)

(4). A method for estimation above-ground biomass with unmanned aerial vehicle multi-spectral image in rice (4/6)

(5). Field crop phenotype monitoring robot (6/9)

(6). Crop growth sensing apparatus and method supporting agricultural machinery variable quantity fertilization operations (6/9)

(7). A model and method for monitoring water content with different PNC levels in wheat plants (2/7)

(8). A model for monitoring leaf nitrogen content with canopy hyperspectra as influenced by soil background in wheat (1/7)

(9). A method for determining the core band of the shoot uptake nitrogen with hyperspectra in wheat (1/7)

(10). A method for monitoring leaf equivalent water thickness with hyperspectrum in wheat (1/7)

(11). A method for monitoring sugar nitrogen ratio with near infrared spectrum in wheat (2/7)

(12). A method for estimating leaf nitrogen concentration with three-bands vegetation index in rice and wheat (2/7)

(13). A method for estimating plant water content with hyperspectrum in wheat leaves (2/8)

(14). A method for estimating plant water content under different nitrogen treatments in wheat (2/7)

Presentations & Poster

l Poster Presentation: Estimating canopy nitrogen status from hyperspectral parameters of single leaves in wheat. Annual Meeting of the ASA, CSSA, SSA, Oct. 31 - Nov. 3, 2010. Long Beach, CA.

l Oral Presentation: Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. The 5^th High Level Forum of the International Agricultural Science. Nov. 30^th, 2012. Beijing, China.

l Poster Presentation: A new method to determine central wavelength and optimal bandwidth for predicting plant nitrogen uptake in wheat. Annual Meeting of the ASA, CSSA, SSA, Oct. 21 - 24, 2012, Cincinnati, OH.

l Poster Presentation: Using the leaf area index to quantify the critical nitrogen dilution curve for winter wheat in eastern China; Monitoring leaf nitrogen content in wheat with canopy hyperspectra. Annual Meeting of the ASA, CSSA, SSA, Nov 3-6, 2013. Tampa, FL.

l Poster Presentation: Estimation of leaf dry weight using hyperspectral vegetation indices and continuous wavelet analysis for wheat canopies. Annual Meeting of the ASA, CSSA, SSA, Nov. 2-5, 2014, Long Beach, CA.

l Poster Presentation: Estimating leaf area index in rice and wheat with continuous wavelet analysis. 2015 IGARSS, July. 26 - 31, 2015, Milan, Italy.

l Poster Presentation: Monitoring Chlorophyll Fluorescence Parameters at Canopy and Leaf Scales on Hyperspectral Reflectance in Wheat. IGARSS, 2016. June. 10 - 14, Beijing, China.

l Oral Presentation: Estimation of Wheat LAI at Middle to High Levels using Unmanned Aerial Vehicle Narrowband Multispectral Imagery. APPPcon, 2018. March.24-26, Nanjing, China

Award & Honors

l 2021 International Des Inventions Geneve, - silver award (3^th)

l 2018 National Outstanding Returned Overseas Chinese Talents, NAU

l 2016 Outstanding Award of Jiangsu Geography Union, Jiangsu, China

l 2015 Second Class Award of National Science and Technology Advancement (4^th participant), State Counsel of China, Number: 2015-J-R04

l 2014 First Class Award of Science and Technology Advancement for Chinese Universities (4^nd participant), Ministry of Education of China, Number: 2014-04

l 2008 Second Class Award of National Science and Technology Advancement (9^th participant), State Counsel of China, Number: 2008-J-251-1-22-R09

l 2007 First Class Award of Science and Technology Advancement for Chinese Universities (8^nd participant), Ministry of Education of China, Number: 2007-173

Memberships

l Editorial Committee of International Journal of Precision Agriculture Aeronautics IEEE

l Editorial Board Member of Journal of Remote Sensing

l Geoscience and Remote Sensing Society

l Union of RS and GIS in Jiangsu province, China

Last update: MARCH. 31, 2023.