| An overview of current and potential applications of thermal remote sensing in precision agriculture S Khanal, J Fulton, S Shearer Computers and electronics in agriculture 139, 22-32, 2017 | 668 | 2017 |
| Remote sensing in agriculture—accomplishments, limitations, and opportunities S Khanal, K Kc, JP Fulton, S Shearer, E Ozkan Remote Sensing 12 (22), 3783, 2020 | 369 | 2020 |
| Anaerobic digestion for bioenergy production: Global status, environmental and techno-economic implications, and government policies J Vasco-Correa, S Khanal, A Manandhar, A Shah Bioresource technology 247, 1015-1026, 2018 | 348 | 2018 |
| Integration of high resolution remotely sensed data and machine learning techniques for spatial prediction of soil properties and corn yield S Khanal, J Fulton, A Klopfenstein, N Douridas, S Shearer Computers and electronics in agriculture 153, 213-225, 2018 | 294 | 2018 |
| Forest ecosystem vulnerability assessment and synthesis for northern Wisconsin and western Upper Michigan: a report from the Northwoods Climate Change Response Framework project MK Janowiak, LR Iverson, DJ Mladenoff, E Peters, KR Wythers, W Xi, ... Gen. Tech. Rep. NRS-136. Newtown Square, PA: US Department of Agriculture …, 2014 | 71 | 2014 |
| Autonomic computing challenges in fully autonomous precision agriculture J Boubin, J Chumley, C Stewart, S Khanal 2019 IEEE international conference on autonomic computing (ICAC), 11-17, 2019 | 61 | 2019 |
| Techno‐economic analysis of a production‐scale torrefaction system for cellulosic biomass upgrading A Shah, MJ Darr, D Medic, RP Anex, S Khanal, D Maski Biofuels, Bioproducts and Biorefining 6 (1), 45-57, 2012 | 61 | 2012 |
| Whole-field reinforcement learning: A fully autonomous aerial scouting method for precision agriculture Z Zhang, J Boubin, C Stewart, S Khanal Sensors 20 (22), 6585, 2020 | 56 | 2020 |
| Assessing the efficacy of machine learning techniques to characterize soybean defoliation from unmanned aerial vehicles Z Zhang, S Khanal, A Raudenbush, K Tilmon, C Stewart Computers and Electronics in Agriculture 193, 106682, 2022 | 44 | 2022 |
| Nitrogen balance in Iowa and the implications of corn-stover harvesting S Khanal, RP Anex, BK Gelder, C Wolter Agriculture, ecosystems & environment 183, 21-30, 2014 | 36 | 2014 |
| Assessment of the spatial and temporal patterns of cover crops using remote sensing K KC, K Zhao, M Romanko, S Khanal Remote Sensing 13 (14), 2689, 2021 | 31 | 2021 |
| A techno-environmental overview of a corn stover biomass feedstock supply chain for cellulosic biorefineries A Shah, M Darr, S Khanal, R Lal Biofuels 8 (1), 59-69, 2017 | 30 | 2017 |
| Implications of biofuel policy‐driven land cover change for rainfall erosivity and soil erosion in the United States S Khanal, RP Anex, CJ Anderson, DE Herzmann, MK Jha Gcb Bioenergy 5 (6), 713-722, 2013 | 30 | 2013 |
| Techno-economic analysis of a recirculating tilapia-lettuce aquaponics system N Zappernick, KV Nedunuri, KR Islam, S Khanal, T Worley, SL Laki, ... Journal of Cleaner Production 365, 132753, 2022 | 26 | 2022 |
| Regional climate impacts of a biofuels policy projection CJ Anderson, RP Anex, RW Arritt, BK Gelder, S Khanal, DE Herzmann, ... Geophysical Research Letters 40 (6), 1217-1222, 2013 | 20 | 2013 |
| Assessing the impact of agricultural field traffic on corn grain yield using remote sensing and machine learning S Khanal, A Klopfenstein, KC Kushal, V Ramarao, J Fulton, N Douridas, ... Soil and Tillage Research 208, 104880, 2021 | 19 | 2021 |
| Techno-ecologically synergistic food–energy–water systems can meet human and ecosystem needs K Lee, S Khanal, BR Bakshi Energy & environmental science 14 (7), 3700-3716, 2021 | 18 | 2021 |
| Integrating aerial images for in-season nitrogen management in a corn field S Khanal, J Fulton, N Douridas, A Klopfenstein, S Shearer computers and electronics in agriculture 148, 121-131, 2018 | 18 | 2018 |
| Identification and classification of critical soil and water conservation areas in the Muskingum River basin in Ohio SK Rattan Lal, Gehendra Kharel, John Fulton Journal of Soil and Water Conservation 73 (2), 213-226, 2018 | 17 | 2018 |
| Climate change impacts on crop yields: A review of empirical findings, statistical crop models, and machine learning methods T Hu, X Zhang, S Khanal, R Wilson, G Leng, EM Toman, X Wang, Y Li, ... Environmental Modelling & Software, 106119, 2024 | 16 | 2024 |
John P. FultonProfessor, The Ohio State UniversityVerified email at osu.edu