李文娟

李文娟，女，博士，研究员，博士生导师, 入选中国农业科学院农科英才“优秀青年英才”。智慧农业创新团队骨干，主要从事基于空天地多源遥感技术的农田智能监测技术及应用研究。近年来，主持各类科研项目，在国内外期刊发表学术论文30余篇，其中SCI/EI收录33篇；第一完成人授权国家发明专利6项，已产业转化2项，担任Remote Sensing of Environment、Agricultural and forest meteorology、IEEE Transactions on Geoscience and Remote Sensing、Computers and Electronics in Agriculture等SCI期刊审稿人，Plant Phenomics青年编委、Journal of Remote Sensing客座主编、青年编委、中国农学会智慧农业分会常务委员、中国农学会农业信息分会委员、中国遥感应用协会定量遥感专业委员会委员、国际数字地球学会中国国家委员会青年科学家工作委员会委员等。

【教育经历 】

2018.11–2021.12法国国家农业食品与环境研究院（INRAE） 阿维尼翁大学 农业遥感专业 农学博士

2011.09–2015.07中国科学院大学（中科院地理所） 植被定量遥感专业 理学博士

2008.09–2011.06 兰州大学 草业地理信息学专业 理学硕士

2004.09–2008.07 东北师范大学 地图学与地理信息系统专业 理学学士

【工作履历】

2022.01– 至今 中国农业科学院农业资源与农业区划研究所，智慧农业创新团队，研究员

2017.09–2021.12 法国农业部农业遥感联盟企业HIPHEN，研发科学家

2016.03–2017.08法国国家农业食品与环境研究院（INRAE），博士后

2014.05–2016.02法国国家农业食品与环境研究院（INRAE），研发工程师

【承担项目】

1. 作物-土壤一体化遥感监测模型和方法，中国农业科学院农科英才-优秀青年英才，2025-1至2029-1，项目主持

2. 稻田信息天空地融合与智能监测技术，十四五国家重点研发计划“水稻智慧农场技术创新与集成示范”课题，2023YFD2300500，2023-11至2027-12，课题主持

3. 盐碱地空天地一体化快速识别关键技术及产品，国家盐碱地综合利用技术创新中心“揭榜挂帅”项目，GYJ2023002，2023-11至2026-11，项目主持

4. 多模块综合集成的移动车载一体化多要素数据采集和智能管控系统，十四五国家重点研发计划“高标准农田天空地一体化智慧监管技术与应用”子课题，2022YFB3903501-5，2022-11-01至2026-10-31，子课题主持

5. 顾及雄穗的玉米全生育期LAI和fAPAR无人机遥感反演方法，国家自然科学基金青年科学基金项目，42201388，2023-01-01 至 2025-12-31，项目主持

6. 农作物结构和生理生化参数的无人机遥感提取，中国农业科学院资划所科技创新工程青年英才启动经费， 2022-02 至 2024-12，项目主持

7. 法国国家植物表型学基础设施，法国国家科研署，面向未来项目，2013-01 至 2024-12，骨干

8. 农业物联网， 法国政府及地区FUI，2018-08 至 2021-08，骨干

9. Sentinel-2农田遥感产品P2S2-Crops，法国航天局，2016-01 至 2018-12，骨干 

10. 基于无人机成像系统的新型'端到端 '农业咨询服务，法国政府及地区FUI，2014-03 至 2018-03，骨干

11. 欧盟FP-7项目Imagines，欧盟，2012-11至2016-01，骨干

【代表论文与著作】

1. Fang, H., Zhang, Y., Li, W., & Chen, J. M. (2025). Remote Sensing of Leaf Area Index, FAPAR, and Clumping Index. In Reference Module in Earth Systems and Environmental Sciences (p. B9780443132209000561). Elsevier.

2. Wang, C., Yin, G., Fu, R., Descals, A., Li, W., Weiss, M., et al. (2025). HARMU: A Multiband Sensor Harmonization for Building Virtual Constellations. Application to Landsat 8 and Sentinel-2. IEEE Transactions on Geoscience and Remote Sensing, 63, 1–12.

3. Zhao, Y., Ma, X., Zhang, Z., Liu, K., Li, W.* (2025). Leveraging Big Earth Data for spatially explicit tracking of the progress on UNSDG15.1.2 and conservation planning. International Journal of Digital Earth, 18(1), 2506186.

4. Ma, Y., Li, W.*, Wang, J., Liu, S., Dong, M., & Shi, Z. (2025). Evaluating the consistency between Sentinel-2 and Planet constellations at field scale: illustration over winter wheat. Precision Agriculture, 26(2), 31.

5. Zhang, W., Li, W.*, Wang, C., Yu, Q., Tang, H., & Wu, W. (2025). A novel index for mapping crop residue covered cropland using remote sensing data. Computers and Electronics in Agriculture, 231, 109995.

6. Li, S., Tang, Z., Ma, K., Wang, Z., & Li, W.*(2025). An efficient retrieval method on Google Earth Engine and comparison with hybrid methods: a case study of leaf area index retrieval. International Journal of Digital Earth, 18(1).

7. 石燕子,李文娟*,李晓彬,杨婷,周兆叶,李旺平 & 吴文斌.(2024).基于多源遥感数据的土壤盐渍化监测研究进展与展望.中国农业信息,36(05),28-41.

8. Cao, H., Ruan, S., Wu, S., Li, W., Zhu, Y., Guo, Y., et al. (2024). A study on parameter calibration of a general crop growth model considering non-foliar green organs. Computers and Electronics in Agriculture, 226, 109362.

9. Ruan, S., Cao, H., Wu, S., Ma, Y., Li, W., Jin, Y., et al. (2024). Rape Yield Estimation Considering Non-Foliar Green Organs Based on the General Crop Growth Model. Plant Phenomics, 6, 0253.

10. Yang, J., Hu, Q., Li, W., Song, Q., Cai, Z., Zhang, X., et al. (2024). An automated sample generation method by integrating phenology domain optical-SAR features in rice cropping pattern mapping. Remote Sensing of Environment, 314, 114387.

11. Wei, Y., Lu, M., Yu, Q., Li, W., Wang, C., Tang, H., & Wu, W. (2024). The normalized difference yellow vegetation index (NDYVI): A new index for crop identification by using GaoFen-6 WFV data. Computers and Electronics in Agriculture, 226, 109417.

12. Li, W.*, Weiss, M., Jay, S., Wei, S., Zhao, N., Comar, A., Lopez-Lozano, R., De Solan, B., Yu, Q., Wu, W.*, Baret, F., (2024). Daily monitoring of Effective Green Area Index and Vegetation Chlorophyll Content from continuous acquisitions of a multi-band spectrometer over winter wheat. Remote Sensing of Environment, 300, 113883.

13. Liu, R., Li, P., Li, Z., Liu, Z., Ding, Y., Li, W.*, & Liu, S. (2023). Bio-Master: Design and Validation of a High-Throughput Biochemical Profiling Platform for Crop Canopies. Plant Phenomics, 5, 0121.

14. Cai, Z., Hu, Q., Zhang, X., Yang, J., Wei, H., Wang, J., Zeng, Y., Yin, G., Li, W., You, L., Xu, B., Shi, Z., (2023). Improving agricultural field parcel delineation with a dual branch spatiotemporal fusion network by integrating multimodal satellite data. ISPRS Journal of Photogrammetry and Remote Sensing, 205, 34–49.

15. Li, H., Yan, K., Gao, S., Ma, X., Zeng, Y., Li, W., ... & Myneni, R. B. (2023). A novel inversion approach for the kernel-driven BRDF model for heterogeneous pixels. Journal of Remote Sensing, 3, 0038.

16. Yu, Q., Duan, Y., Wu, Q., Liu, Y., Wen, C., Qian, J., Song, Q., Li, W., Sun, J., Wu, W., (2023). An interactive and iterative method for crop mapping through crowdsourcing optimized field samples. International Journal of Applied Earth Observation and Geoinformation, 122, 103409.

17. Li, W.*, Weiss, M., Garric, B., Champolivier, L., Jiang, J., Wu, W., Baret, F., (2023). Mapping Crop Leaf Area Index and Canopy Chlorophyll Content Using UAV Multispectral Imagery: Impacts of Illuminations and Distribution of Input Variables. Remote Sensing 15, 1539, 1-13.

18. Zou, D., Yan, K., Pu, J., Gao, S., Li, W., Mu, X., Knyazikhin, Y., Myneni, R.B., (2022). Revisit the Performance of MODIS and VIIRS Leaf Area Index Products from the Perspective of Time-Series Stability. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15, 8958–8973.

19. Wang, J., Lopez-Lozano, R., Weiss, M., Buis, S., Li, W., Liu, S., Baret, F., Zhang, J., (2022). Crop specific inversion of PROSAIL to retrieve green area index (GAI) from several decametric satellites using a Bayesian framework. Remote Sensing of Environment 278, 113085.

20. Li, W.*, Comar, A., Weiss, M., Jay, S., Lopez-Lozano, R., Simon, M., Colombeau, G., Hemmerle, M., Baret, F., (2021). A double swath configuration for improving throughput and accuracy of trait estimate from UAV images. Plant Phenomics, 2021, 2021: 1-11.

21. Camacho, F., Fuster, B., Li, W., Weiss, M., Ganguly, S., Lacaze, R., Baret, F. (2021). Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations. Remote Sensing of Environment, 260, 112453.

22. Li, W.*, Jiang, J., Baret, F., Comar, A., Hemmerle, M., Weiss, M., Madec, S., Tison, F., Burger, P., (2021). Impact of the reproductive organs on crop BRDF as observed from a UAV. Remote Sensing of Environment, 259, 112433.

23. Wojnowski, W., Wei, S., Li, W., Yin, T., Li, X.-X., Ow, G.L.F., Yusof, M.L.M., Whittle, A.J., (2021). Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations. Remote Sensing, 13, 1069.

24. Li, W.*, Fang, H., Wei, S., Weiss, M., Baret, F., (2021). Critical analysis of methods to estimate the fraction of absorbed or intercepted photosynthetically active radiation from ground measurements: application to rice crops. Agricultural and forest meteorology, 297, 108273.

25. Jay, S., Comar, A., Benicio, R., Beauvois, J., Dutartre, D., Daubige, G., Li, W., Labrosse, J., Thomas, S., Henry, N., Weiss, M., Baret, F., (2020). Scoring Cercospora Leaf Spot on Sugar Beet: Comparison of UGV and UAV Phenotyping Systems. Plant Phenomics, 2020, 1–18.

26. Fang, H., Zhang, Y., Wei, S., Li, W., Ye, Y., Sun, T., Liu, W., (2019). Validation of global moderate resolution leaf area index (LAI) products over croplands in northeastern China. Remote Sensing of Environment, 233, 111377.

27. Fang, H., Liu, W., Li, W., Wei, S., (2018). Estimation of the directional and whole apparent clumping index (ACI) from indirect optical measurements. ISPRS Journal of Photogrammetry and Remote Sensing, 144, 1–13.

28. Li, W.*, Baret, F., Weiss, M., Buis, S., Lacaze, R., Demarez, V., Dejoux, J.-f., Battude, M., Camacho, F., (2017). Combining hectometric and decametric satellite observations to provide near real time decametric FAPAR product. Remote Sensing of Environment, 200, 250-262.

29. Li, W.*, Weiss, M., Waldner, F., Defourny, P., Demarez, V., Morin, D., Hagolle, O., Baret, F., (2015). A generic algorithm to estimate LAI, FAPAR and FCOVER variables from SPOT4_HRVIR and Landsat sensors: Evaluation of the Consistency and Comparison with Ground Measurements. Remote Sensing, 7, 15494-15516.

30. Li, W.*, Fang, H. (2015). Estimation of direct, diffuse, and total FPAR from Landsat surface reflectance data and ground-based estimates over six FLUXNET sites. Journal of Geophysical Research: Biogeosciences, 120, 96-112.

31. Waldner, F., Lambert, M.-J., Li, W., Weiss, M., Demarez, V., Morin, D., Marais-Sicre, C., Hagolle, O., (2015). Land cover and crop type classification along the season based on biophysical variables retrieved from multi-sensor high-resolution time series. Remote Sensing, 7, 10400-10424.

32. Fang, H., Li, W., Wei, S., Jiang, C. (2014). Seasonal variation of Leaf Area Index over paddy rice fields in NE China: Intercomparison of destructive sampling, LAI-2200, digital hemispherical photography (DHP), and AccuPAR methods. Agricultural and forest meteorology, 198-199, 126-141.

33. Fang, H., Li, W., Myneni, R.B. (2013). The impact of potential land cover misclassification on MODIS Leaf Area Index (LAI) estimation: A statistical perspective. Remote Sensing, 5, 830-844.

34. Fang, H., Jiang, C., Li, W., Wei, S., Baret, F., Chen, J.M., Garcia-Haro, J., Liang, S., etc (2013). Characterization and intercomparison of global moderate resolution leaf area index (LAI) products: Analysis of climatologies and theoretical uncertainties. Journal of Geophysical Research: Biogeosciences, 118, 529-548.

35. 李文娟,九次力,谭忠厚,马轩龙 & 陈全功.(2012).青海省草地生产力及草畜平衡状况研究.资源科学,34(02),367-372. 

36. 李文娟,马轩龙 & 陈全功.(2009).青海省海东、海北地区草地资源产量与草畜平衡现状研究.草业学报,18(05),270-275.

37. 马轩龙,李文娟 & 陈全功.(2009).基于GIS与草原综合顺序分类法对甘肃省草地类型的划分初探.草业科学,26(05),7-13.

【专利和标准】

1. 李文娟; 吴文斌; 宋茜; 余强毅 ; 一种评估育种田间小区样地质量的方法和系统, 2023-10-03, 中 国, ZL202211410253.7

2. 李文娟; 吴文斌; 余强毅 ; 一种支持多型号多光谱相机数据全自动处理的方法和系统, 2023-07-04, 中国, ZL202211273396.8

3. 李文娟; 吴文斌; 余强毅; 宋茜 ; 一种融合物联网和卫星生成时空连续农作物参数的方法和系统, 2023-06-13, 中国, ZL202211464074.1

4. 李文娟; 吴文斌; 余强毅 ; 一种基于微型光谱仪连续观测提取农作物叶面积指数和叶绿素含量的方法, 2022-12-27, 中国, ZL202211314999.8

5. 李文娟; 吴文斌; 吴尚蓉; 一种基于多源遥感数据的农作物估产的方法和系统, 2024-01-12, 中国, ZL202410044724.X

6. 吴文斌; 李文娟; 余强毅; 段玉林; 一种获取农田空间分布异质性的方法和系统, 2024-01-15, 中国, ZL202410055638.9

7. 徐嘉淇;李文娟; 一种基于几何特征的轨迹数据版权保护方法, 2024-02-20,中国, ZL2023 1 1525758.2

8. 李文娟; 吴文斌; 余强毅; 段玉林 ; 一种基于多源遥感数据评估农作物衰落速率的方法和系统, 2024-12-10, 中国, ZL202410044634.0

【联系方式】

（1）研究方向：基于空天地多源遥感技术的农田智能监测技术及应用

（2）电话：010-82108654

（3）邮箱：liwenjuan01@caas.cn

（4）通讯地址：北京市海淀区中关村南大街12号，科海福林，302