Publications & Manuscripts
Published papers, submitted manuscripts, and conference presentations.
Submitted / Drafted
Rathore, J., Deepak R. Joshi, Ali Dadkhah, Donna M. Rizzo, Olga Walsh, David Clay, Maaz Gardezi. On-farm Early-Season Crop Stress Detection and Yield Impact Mapping Using Random Forest. (Drafted)
Deepak R. Joshi, Jitender Rathore, David Mulla, Ahmed Harb Rabia, Skye Brugler, Pappu Yadav. Machine Learning and Artificial Intelligence-driven solutions in precision agriculture. (Submitted)
Rathore, J., Deepak R. Joshi, Ali Dadkhah, Donna M. Rizzo, Olga Walsh, David Clay, Maaz Gardezi (2025). On-Farm Soybean Yield Estimation Using Earth Observation Data and Machine Learning Algorithms. Computers and Electronics in Agriculture. (Submitted, under review)
Rathore, J., Deepak R. Joshi, Ali Dadkhah, Donna M. Rizzo, Olga Walsh, David Clay, Maaz Gardezi (2025). Predicting on-farm low and high yield zones with Sentinel-2, random forest, and spatial clustering. (Drafted)
Published / Accepted
Mehla, M. K., Kothari, M., Singh, P. K., Bhakar, S. R., Yadav, K. K., Rathore, J., et al. (2025). Basin scale impacts of nitrogenous fertilizer use on croplands from a grey water footprint perspective. Discover Water.
Fikriyah, V. N., Darvishzadeh, R., Laborte, A., Rathore, J., & Nelson, A. (2025). Temporal backscatter characterisation of ratoon rice crops based on Sentinel-1 intensity data. GIScience & Remote Sensing, 62(1). https://doi.org/10.1080/15481603.2025.2455081
Rathore, J., Kumari, S., Tripathy, P., Mahto, S. S., & Lal, P. (2025). 2024 Brazil Floods: Mapping the extent and impacts in Eastern Rio Grande do Sul using geospatial techniques. Natural Hazards Research.
Gardezi, M., Abuayyash, H., Adler, P. R., Alvez, J. P., Anjum, R., Badireddy, A. R., Rathore, J., et al. (2024). The role of living labs in cultivating inclusive and responsible innovation in precision agriculture. Agricultural Systems, 216, 103908.
Kumar, R., Sharma, A., Rathore, J., Negi, A., Sharma, K.K., Patel, S. (2024). Climate-Induced Vulnerability, Adaptation, and Mitigation Strategies: A Case Study of Chamoli District, Garhwal Himalayas. Climate Change and Human Adaptation in India. Springer, Sustainable Development Goals Series.
Rathore, J., Kumar, R., Bora, S., Pal, R., Pandey, B. W., & Singh, V. (2022). Determining land use and land cover change and its effect on land surface temperature in Nainital district. International Journal of Ecology and Environmental Sciences, 48(1), 51–57.
Conferences & Presentations
Rathore, J., Joshi, D., Dadkhah, A., Kumari, S., Gardezi, M., Walsh, O., Clay, D. E. Employing random forest, support vector machine learning models, and PlanetScope satellite data to predict crop yield on the farm. AGU 2024.
Rathore, J., Joshi, D., Abuayyash, H., Kumari, S., Gardezi, M., Walsh, O., Clay, D. E. (2024). Co-designing a Zone-Specific On-farm Digital Support System for Crop Yield Prediction. AGU Fall Meeting, Poster GC21J-0009.
Gardezi, M., Adler, P. R., Abuayyash, H., Alvez, J., Badireddy, A. R., Anjum, R., Rathore, J., et al. (2024). Promoting Responsible Innovation in Precision Agriculture through Living Labs. AGU 2024.
Rathore, J., Kumari, S., Khulal, A., Walsh, O. S., Gardezi, M., McClintick-Chess, J., et al. (2024). The Investigation of Grain Yield Quantity of Different Wheat Varieties at the Micro-Climate Level. ASA, CSSA, SSSA International Annual Meeting.
Rathore, J., Gardezi, M., Walsh, O., Joshi, D., Kumari, S., Clay, D. (2024). Feasibility of PlanetScope satellite data and random forest machine learning model for soybean yield prediction at the last three growth stages. 16th International Conference on Precision Agriculture, Manhattan, Kansas.
Rathore, J. (2023). Quantification of extreme weather effects on hilly mountain regions using satellite remote sensing: A case study from Chamoli District. AGU Fall Meeting 2023, San Francisco, CA.
Rathore, J., Joshi, D., Posadas, B., Gardezi, M., Clay, D. (2023). High-resolution satellite imagery and machine learning for Soybean yield prediction. SPES Symposium, Virginia Tech.
Rathore, J., Chandel, A., Langston, D. (2023). Quantifying sclerotinia blight severity and effective management application strategy in peanuts using multispectral imaging techniques. AI in Agriculture Conference, Orlando, Florida. [First Place]
Rathore, J., Chandel, A., Balota, M. (2023). Peanut crop maturity prediction using machine learning and multispectral imagery. CAIA Big Event, Virginia Tech. [Second Place]