Faculty Member Profile
CONTACT ME
📍 Institute of Geo-Information & Earth Observation
📞 03055450671
📱 03346569580
Dr. Naeem Abbas Malik
Lecturer
Ph.D. Geospatial Science and Engineering (Remote Sensing) (South Dakota State University, USA — 2026)
M.S. Remote Sensing and GIS (National University of Sciences and Technology, Pakistan — 2011)
B.S. Agriculture (Agronomy) (Arid Agriculture University Rawalpindi, Pakistan — 2008)
Specialization
2 years of experience
Affiliation
Institute of Geoinformation and Earth Observation, PMAS Arid Agriculture University Rawalpindi, Murree Road, Rawalpindi 46300
WoS/ ORCID / Google Scholar /Scopus / ResearchGate/Personal Web
ORCID: https://orcid.org/0000-0002-0104-8028
Google Scholar: https://scholar.google.com/citations?user=yVkGU0YAAAAJ
LinkedIn: https://www.linkedin.com/in/naeem-malik-53a52888
Research Group
Crop monitoring and Geo-AI Lab
Research Interest
- Operational crop monitoring at regional to continental scale
- Crop condition and agricultural drought monitoring
- Crop yield anomaly modelling
- Validation of earth observation products
- Precision agriculture
No. of Research Projects
On Going
0
Completed
4
Research Supervision
PhD
0
MPhil/MS/M.Sc.(Hons)
15
Technologies Developed/Patent/IP etc.
Research frameworks and products developed:
• An operational, CONUS-scale framework translating the NASA VIIRS land
surface phenology product into weekly, pixel-level crop progress equivalent
to USDA-NASS Crop Progress Reports for five major crops (published,
ISPRS Journal of Photogrammetry and Remote Sensing, 2026).
• A phenology-aligned, crop-specific Vegetation Condition Index framework
derived from 21 years of MODIS EVI2 for weekly crop-condition and
agricultural drought monitoring.
Area(s) of Consultancy Services
• Crop mapping and monitoring using satellite and UAV imagery
• Crop condition, drought stress and climate-risk assessment
• Validation of remote sensing products against official agricultural statistics
• Precision agriculture: Geospatial decision support systems for enhanced
agricultural productivity
• Training and capacity building in remote sensing, GIS and Geo-AI
Research Papers (Latest Ten)
- Malik, N. A., Zhang, X., Shen, Y., Yang, Z., Ye, Y., & Liu, Y. (2026). Towards operational tracking of weekly crop progress using VIIRS land surface phenology product across the continental United States. ISPRS Journal of Photogrammetry and Remote Sensing, 234, 337–354. doi:10.1016/j.isprsjprs.2026.02.032 (2026)
- Khan, S. N., Iqbal, J., Khan, M. R., Malik, N. A., et al. (2025). Using remotely sensed vegetation indices and multi-stream deep learning improves county-level corn yield predictions. European Journal of Agronomy, 164, 127496. (2025)
- Malik, N. A., & Zhang, X. (2023). Analyzing trend in MODIS-derived crop phenology for corn and soybean in comparison with field-based crop progress data. IEEE IGARSS 2023, 3474–3477. (2023)
- Khan, S. N., Khan, A. N., Tariq, A., Lu, L., Malik, N. A., et al. (2023). County-level corn yield prediction using supervised machine learning. European Journal of Remote Sensing, 56(1), 2253985. (2023)
Books (Latest Ten)
No books listed.
No awards listed.
