Keshav D. Singh, Ph.D.

Image Keshav Singh
Research Scientist (Digital Agriculture)

Remote Sensing, Digital Phenomics and Smart Farming. Mainly working on Proximal and UAV based RGB, Thermal, LiDAR, Multispectral and Hyperspectral Imaging applications in the framework of Precision Agriculture and Plant Phenotyping.

Current research and/or projects

  • Developing a robust digital imaging system for controlled and field-based environments phenotyping to support plant breeding program
  • Engaged in advanced sensors technologies, artificial intelligence (AI) and data-driven decision making to identify complex physiological traits
  • Smart sensing technology to screen stress resistance and stable yielding cultivars in a changing climate (plant phenomics)
  • High-throughput imaging capabilities for safe and effective uses of herbicides and fertilizers in field crops (precision agriculture)
  • Retrieval of bio-chemical and bio-physical parameters from leaf and canopy spectra to estimate plant photosynthesis activity (imaging spectroscopy)
  • RADARSAT and multispectral satellites to characterize vegetation growth dynamics and soil moisture in Canadian prairies
  • My research mainly integrates autonomous systems, AI models (machine/deep learning), and big-data analytics in digital agriculture to develop tools to promote growing crops in smarter and more sustainable way.

Research and/or project statements

Over last ten years, I gained expertise in high-throughput aerial imaging and digital agriculture to study horticulture, oilseed rape, legumes and cereal crop phenomics. We have developed an advanced calibration and imaging methodology to improve robustness of UAV-acquired remote sensing data to identify stress response by crops. As an Agrophysicist and drone pilot my work focuses on image calibration, design of automated sensing system (IoTs), and the development of mobile agriculture robots (phenocart). My research area include Hyperspectral Imaging (HSI) technology for plants health detection, resistance to biotic (pest, disease, weeds) and abiotic (drought, heat, cold) stresses, and nutrient status. It involves agronomic data processing, image-cube analysis, AI algorithms development, crops mapping, big-data and predictive analytics. These innovative sensing approaches will advance the data science over traditional industry to guide sustainable agricultural and management practices to form climate-smart farming system in Canadian agri-food production. I was the lead support to develop Digital Transformation mission priority for AAFC Strategic Plan for Science. Additionally, I provide scientific and technical guidance for developing novel sensors and smart farming infrastructure.

Current projects:

J-002858: Digital imaging technology to characterize herbicides symptomology and to discriminate herbicide-resistant weed biotypes (2022-25)

J-003137: Field sensing phenocart data management and image analysis pipeline development to improve cereal crops characteristics (2023-26)

J-003256: Spectral imaging technology to estimate nitrogen (N) fertilizer use efficiency to optimize grain yield and quality in wheat and canola crop (2023-27)

J-003287: Selection efficiency in dry bean breeding program through high-throughput phenotyping (S-CAP 2023-28)

J-003290: Tools and techniques to develop high-throughput imaging system from aphanomyces/fusarium root rot disease dataset and AI models (2023-28)

Professional activities / interests

  • RPAS (UAV) Drone Pilot (Advanced Operations), Transport Canada
  • Remote sensing methods for mapping and monitoring of vegetation and agricultural crops
  • Sensing crops adaptability to changing environment (sustainable agriculture)
  • Reviewing manuscripts for peer journals (Remote Sensing, Sensors, Drones, Phenomics and Agriculture)
  • Supervising the diverse group of students and researchers

Education and awards


  • Research Ass. (RA) at the University of Saskatchewan, SK, Canada
  • Postdoctoral Fellow (Post-doc) at the University of California- Davis, CA, USA
  • Doctor of Philosophy (Ph.D.) in Hyperspectral Remote Sensing, IIT Bombay, IN
  • Master of Technology (M.Tech.) in Engineering Physics, GGSIP University, IN
  • Master of Science (M.Sc.) in Applied Physics, Delhi University, IN
  • Bachelor of Science (B.Sc.) in Physics (Hons.), Delhi University, IN

Honors and Awards:

  • Member of Logistics Committee, NAPPN Phenomics planning, North America
  • Best Poster Presentation Award, P2IRC Symposium, GIFS, Saskatoon, Canada
  • Best Young Scientist Paper Competition, Agro-Geoinformatics, Fairfax, VA, USA
  • Selected for Greenland GNSS (GNET) Workshop, GSFC, NASA, USA
  • Selected for TUM Research Opportunities Week & DLR, Munich, Germany
  • Awarded Full International Travel Support (ITS), DST, Govt. of India, IN
  • Awarded International Commonwealth Fellowship (DFAIT–GSEP), Canada
  • University Gold Medalist in Engineering Physics, GGSIP University, IN

Professional Certificates:

  • Certificate in Understanding Phenology with Remote Sensing, NASA, USA
  • Attended Philosophy and Practice of University Teaching, USask, Canada
  • Certificate in Drone Technology & GIS for Crop Agriculture, UCANR, UC Davis, CA, USA
  • Certificate in Environmental Monitoring and Research with UAVs, UC Davis, CA, USA
  • Certificate in Food+Ag Entrepreneurship Academy (AGEA’17), UC Davis, CA, USA
  • Certificate in Learner–Centered Teaching, CEE, UC Davis, CA, USA
  • Certificate in Ag Innovation Entrepreneurship Academy (AGEA’16), UC Davis, USA
  • Certificate of HYPERSPECTRA Workshop, IIT Bombay, Mumbai, IN

International experience and/or work

Research Ass. (RA) at the Department of Plant Sciences, University of Saskatchewan, SK, Canada [2018–2020]

Worked on UAV-based multidisciplinary projects which mainly included canola, wheat, and lentil crops phenotyping. My research focused on different canola genotypes seedpods maturity and shattering problem; nitrogen use efficiency (NUE) in canola varieties; wheat cultivars phenotyping and yield prediction strategies using machine learning and statistical models; assessment of wheat stripe-rust in a nursery; evaluating different herbicides responses to dry down the lentils.

Post-doctoral Employee at the College of Agricultural and Environmental Sciences, University of California- Davis, CA, USA [2015–2017]

Worked on the greenhouse and UAV-based Hyperspectral Imaging technology in study of host selection by selected insects/pests and abilities to assess crop health via reflectance profiling in the framework of Precision Agriculture (detection of crop responses to biotic & abiotic stressors). Here, I have studied different horticultural crops and nut-fruit trees grows in the central valley, California. It included strawberry, soybean, tomato, gerbera, rice, almond and walnut orchard.

Assistant Professor at the Department of Physics, JECRC University, Jaipur, IN [Feb.–Jun. 2015]

Taught "Engineering Physics" at Graduate and Post-graduate level

Ph.D. Scholarship at the Indian Institute of Technology, Mumbai by MHRD Government of India, IN [2009–2014]

Thesis: Spectral Unmixing of Hyperspectral Data in the Reflective and Emissive Domain: Terrestrial and Planetary Remote Sensing

Visiting Graduate Student (Ph.D.) Fellowship awarded by International Canadian Commonwealth Fellowship (DFAIT–GSEP), University of Western Ontario, ON, Canada [Mar.–Oct. 2011]

Research Project: Interferometric Synthetic Aperture Radar (InSAR) to study vol­canic eruption in Mount Sinabung, Indonesia using JAXA-ALOS satellite data

Key publications

  1. K.D. Singh, S.D. Noble, P. Ravichandran, K. Halcro, R. Soolanayakanahally, J. Sangha, E. Brauer, K.T. Nilsen, O. Molina, H.S. Randhawa, R. Ortega Polo, C. Workman, S. Pahari, “Unmanned Ground Vehicle for High-throughput Phenotyping to Quantify Field Crops Characteristics”, NAPPN Annual Conference, West Lafayette, Indiana, USA, February, 2024 (Hybrid);

    2024 - View publication details

  2. K.D. Singh, P. Balasubramanian, M. Natarajan, H. Wang and P. Ravichandran, “UAV-based Multispectral Imaging for High-throughput Phenotyping of Dry Bean Breeding Trials”, NAPPN Annual Conference 2024, West Lafayette, Indiana, USA, February, 2024 (Hybrid);

    2024 - View publication details

  3. Rajabi, R., Zehtabian, A., Singh, K.D., Tabatabaeenejad, A., Ghamisi, P. and Homayouni, S., "Editorial: Hyperspectral Imaging in Environmental Monitoring and Analysis”, Front. Environ. Sci.", Vol. 11, 2023, doi: 10.3389/fenvs.2023.1353447

    2023 - View publication details

  4. Wang, H., Singh, K.D., Poudel, H., Ravichandran, P., Natarajan, M., and Eisenreich, B., "Estimation of Crop Height and Digital Biomass from UAV-based Multispectral Imagery", 13th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS, IEEE), Athens, Greece, Oct.-Nov. 2023,

    2023 - View publication details

  5. Singh, K.D., Natarajan, M., Gill, K., Ravichandran, P., Wang. H., and Geddes, C.M., "Digital Imaging System for High-Throughput Plant Phenotyping using Raspberry Pi Computers", 13th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS, IEEE), Athens, Greece, Oct.-Nov. 2023,

    2023 - View publication details

  6. Hongquan Wang, Keshav Singh, and Prabahar Ravichandran, "Compact-Polarimetric SAR Decompositions for Soil Moisture Retrievals using RADARSAT Constellation Mission Data", 11th International Conference of Agro-Geoinformatics, Wuhan, China, July 2023

    2023 - View publication details

  7. Prabahar Ravichandran, Keshav D. Singh, Charles M. Geddes, Breanne Tidemann, Eric Johnson, Steve Shirtliffe, Thomas K. Turkington, and Manoj Natarajan, "Utilizing Hyperspectral Imaging Technology to Characterize Herbicide Phytotoxicity in Oat and Mustard", 11th International Conference of Agro-Geoinformatics, Wuhan, China, July 2023

    2023 - View publication details

  8. Prabahar Ravichandran, Keshav D. Singh, Charles M. Geddes, Manoj Natarajan, Austin Jaster, and Hongquan Wang, "Proximal Hyperspectral Imaging to Classify Herbicide-Resistant and -Susceptible Kochia (Bassia Scoparia)", 11th International Conference of Agro-Geoinformatics, Wuhan, China, July 2023

    2023 - View publication details

  9. Yoosefzadeh-Najafabadi, M., Singh, K.D., Pourreza, A., Sandhu, K.S., Adak, A., Murray, S.C., Eskandari, M., and Rajcan, I., “Remote and Proximal Sensing: How Far Has It Come to Help Plant Breeders?”, Advances in Agronomy, V 181, 2023

    2023 - View publication details

  10. Natarajan, M., Singh, K.D., George, J., and Ragupathy, R., “Developing a Low-cost Digital Imaging System for Plant Phenotyping using Raspberry Pi Computers”, ISCB-ISMB Digital Agriculture Conference, Jul. 2022, Madison, Wisconsin, USA, Abstract # 921. (Virtual Online)

    2022 - View publication details

  11. Ansari, K., Bae, T.-S., Singh, K.D., Aryal, J. (2022). Multivariate singular spectrum analysis of seismicity in the space–time-depth-magnitude domain: insight from eastern Nepal and the southern Tibetan Himalaya. Journal of Seismology, [online] 26(1), 147-166.

    2022 - View publication details

  12. Torres-Tello, J.W., Ko, S., Singh, K.D., Shirtliffe, S.J. (2021). Corrigendum to ‘A novel approach to identify the spectral bands that predict moisture content in canola and wheat’ [biosystems engineering 210 (2021) 91–103](S1537511021001884)(10.1016/j.biosystemseng.2021.08.004). Biosystems Engineering, [online] 211

    2021 - View publication details

Research facility

5403 1st Avenue South
Lethbridge, AB T1J 4B1


  • Member of Canadian Society of Agronomy (CSA)
  • Member of Drone Pilot Association of Canada (DPAC)
  • Member of Canadian Remote Sensing Society (CRSS)
  • Member of Technical Science Advisory Committee (TSAC)
  • Member of North American Plant Phenotyping Network (NAPPN)
  • Member of Institute of Electrical and Electronics Engineers (IEEE)
  • Member of Canadian Agri-food Automation and Intelligence Network (CAAIN)



Other languages

Hindi, Punjabi