Lang Qiao

Academic Appointments

Postdoctoral Researcher                                 

  • Bioproducts and Biosystems Engineering, University of Minnesota, USA     09/2024 – Now
  • Biological System Engineering, University of Wisconsin-Madison, USA       09/2023 – 08/2024

Fields of Interest

High throughput plant phenotyping

  • Monitoring crop phenotype response to stress based on spectral technique: fertilization stress, drought stress or pest and disease stress, etc.
  • Application of multi-source data fusion of different agricultural sensor types in agriculture: hyperspectral, multispectral, RGB, LIDAR etc.

Agricultural remote sensing and artificial intelligence

  • Machine learning for high dimensional data analysis.
  • Data analysis and fusion of different agricultural scales: satellite, UAV, ground (robot, vehicle, handheld).
  • Satellite imagery time series analysis and crop mapping.

Publications

Google Scholar

  1. Qiao, L., Zhao, R., Tang, W., Sun, H., & Li, M., et al. (2022). Estimating maize LAI by exploring deep features of vegetation index map from UAV multispectral images. Field Crops Research, 289. https://doi.org/10.1016/j.fcr.2022.108739
  2. Qiao, L., Gao, D., Zhao, R., Tang, W., An, L., & Li, M., et al. (2022). Improving estimation of LAI dynamic by fusion of morphological and vegetation indices based on UAV imagery. Computers and Electronics in Agriculture, 192. https://doi.org/10.1016/j.compag.2021.106603
  3. Qiao, L., Tang, W., Gao, D., Zhao, R., An, L., & Li, M., et al. (2022). UAV-based chlorophyll content estimation by evaluating vegetation index responses under different crop coverages. Computers and Electronics in Agriculture, 196. https://doi.org/10.1016/j.compag.2022.106775
  4. Lang, Q., Dehua, G., Junyi, Z., Minzan, L., Hong, S., & Junyong, M. (2020). Dynamic Influence Elimination and Chlorophyll Content Diagnosis of Maize Using UAV Spectral Imagery. Remote Sensing, 12(16). https://doi.org/10.3390/rs12162650
  5. QIAO Lang, ZHANG Zhiyong, CHEN Longsheng, SUN Hong, LI Li, LI Minzan. Chlorophyll Content Detection and Distribution Research of Maize Canopy Based on UAV Image[J]. Transactions of the Chinese Society for Agricultural Machinery,2019,50:182-186. https://doi.org/10.6041/j.issn.1000-1298.2019.S0.028
  6. Gao D, Qiao L, Song D, Li Mi, Sun H, An L, Zhao R, Tang W, Qiao J. In-field chlorophyll estimation based on hyperspectral images segmentation and pixel-wise spectra clustering of wheat canopy[J]. Biosystems engineering, 2022,217,41-55 https://doi.org/10.1016/j.biosystemseng.2022.03.003
  7. Dehua Gao, Lang Qiao, Lulu An, Ruomei Zhao, Hong Sun, Minzan Li, Weijie Tang, Nan Wang, Estimation of spectral responses and chlorophyll based on growth stage effects explored by machine learning methods, The Crop Journal, 2022, ISSN2214-5141. https://doi.org/10.1016/j.cj.2022.07.011
  8. Dehua Gao, Lang Qiao, Lulu An, Hong Sun, MinZan Li*, Ruomei Zhao, Weijie Tang, Di Song. Diagnosis of maize chlorophyll content based on hybrid preprocessing and wavelengths optimization[J]. Computers and Electronics in Agriculture,2022,197,106934. https://doi.org/10.1016/j.compag.2022.106934
  9. Song D, Qiao L, Gao D, Li S, Li M, Sun H, Ma J. Development of crop chlorophyll detector based on a type of interference filter optical sensor[J]. Computers and Electronics in Agriculture, 2021,187:106260. https://doi.org/10.1016/j.compag.2021.106260
  10. Ning Liu, Lang Qiao, Zizheng Xing, Minzan Li, Hong Sun, Junyi Zhang, Yao Zhang. Detection of chlorophyll content in growth potato based on spectral variable analysis[J]. Spectroscopy Letters,2020,53(6). https://doi.org/10.1080/00387010.2020.1772827

Teaching Experience

Guest Lecture: BBE 8001, Seminar I (Autumn 2024, University of Minnesota)

Graduate Student Advisor: Eric Yu (Ph.D., Department of Agronomy and Plant Genetics, University of Minnesota)

Teaching Assistant: New Advances in Agricultural Smart Equipment Technology (Spring 2020, China Agricultural University).

Professional Service

Topic Editors: Frontiers in Remote Sensing (Crop Monitoring Using Multisource Satellite and Unmanned Aerial Vehicle Remote Sensing).

Reviewer: Field Crops Research; Computers and Electronics in Agriculture.

Speaker: 2021International Conference on Smart Agriculture Innovation Development; 2024 American Society of Agricultural and Biological Engineers.

Memberships: American Society of Agricultural and Biological Engineers (ASABE).

Skills

Programming Languages: Proficient in Python, MATLAB.

Software: ArcGIS, QGIS, ENVI, MATLAB, PyCharm.

License: Remote Pilot Certificate, Driver license.