| Comparative assessment of environmental variables and machine learning algorithms for maize yield prediction in the US Midwest Y Kang, M Ozdogan, X Zhu, Z Ye, C Hain, M Anderson Environmental Research Letters 15 (6), 064005, 2020 | 125 | 2020 |
| Corn yield prediction and uncertainty analysis based on remotely sensed variables using a Bayesian neural network approach Y Ma, Z Zhang, Y Kang, M Özdoğan Remote Sensing of Environment 259, 112408, 2021 | 124 | 2021 |
| Field-level crop yield mapping with Landsat using a hierarchical data assimilation approach Y Kang, M Özdoğan Remote sensing of environment 228, 144-163, 2019 | 121 | 2019 |
| How universal is the relationship between remotely sensed vegetation indices and crop leaf area index? A global assessment Y Kang, M Özdoğan, SC Zipper, MO Román, J Walker, SY Hong, ... Remote sensing 8 (7), 597, 2016 | 116 | 2016 |
| OpenET: Filling a critical data gap in water management for the western United States FS Melton, J Huntington, R Grimm, J Herring, M Hall, D Rollison, ... JAWRA Journal of the American Water Resources Association 58 (6), 971-994, 2022 | 113 | 2022 |
| Global assessment of vegetation index and phenology lab (VIP) and global inventory modeling and mapping studies (GIMMS) version 3 products M Marshall, E Okuto, Y Kang, E Opiyo, M Ahmed Biogeosciences 13 (3), 625-639, 2016 | 52 | 2016 |
| A data-driven approach to estimate leaf area index for Landsat images over the contiguous US Y Kang, M Ozdogan, F Gao, MC Anderson, WA White, Y Yang, Y Yang, ... Remote Sensing of Environment 258, 112383, 2021 | 42 | 2021 |
| Early identification of seed maize and common maize production fields using sentinel-2 images T Ren, Z Liu, L Zhang, D Liu, X Xi, Y Kang, Y Zhao, C Zhang, S Li, ... Remote Sensing 12 (13), 2140, 2020 | 33 | 2020 |
| Evaluation of satellite Leaf Area Index in California vineyards for improving water use estimation Y Kang, F Gao, M Anderson, W Kustas, H Nieto, K Knipper, Y Yang, ... Irrigation Science 40 (4), 531-551, 2022 | 21 | 2022 |
| How universal is the relationship between remotely sensed vegetation indices and crop leaf area index? A global assessment, Remote Sens., 8, 597 Y Kang, M Özdoğan, S Zipper, M Román, J Walker, S Hong, M Marshall, ... | 9 | 2016 |
| County-level corn yield prediction using deep transfer learning Y Ma, Y Kang, M Ozdogan, Z Zhang AGU Fall Meeting Abstracts 2019, B54D-02, 2019 | 7 | 2019 |
| Evaluation of the uncertainty in satellite-based crop state variable retrievals due to site and growth stage specific factors and their potential in coupling with crop growth … N Levitan, Y Kang, M Özdoğan, V Magliulo, P Castillo, F Moshary, ... Remote sensing 11 (16), 1928, 2019 | 7 | 2019 |
| Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications JM Volk, JL Huntington, FS Melton, R Allen, M Anderson, JB Fisher, ... Nature Water, 1-13, 2024 | 5 | 2024 |
| OpenET Satellite-based ET Intercomparisons with Ground-based Measurements: Phase II Results J Volk, J Huntington, F Melton, R Allen, M Anderson, C Dunkerly, J Fisher, ... Authorea Preprints, 2022 | 2 | 2022 |
| County-Level Corn Yield Forecast with Deeping Learning and Satellite Data Y Kang | 2 | 2018 |
| A deep transfer learning framework for mapping high spatiotemporal resolution LAI J Zhou, Q Yang, L Liu, Y Kang, X Jia, M Chen, R Ghosh, S Xu, C Jiang, ... ISPRS Journal of Photogrammetry and Remote Sensing 206, 30-48, 2023 | 1 | 2023 |
| CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO2 fertilization Y Kang, M Gaber, M Bassiouni, X Lu, T Keenan Earth System Science Data Discussions 2023, 1-51, 2023 | 1 | 2023 |
| A relational vulnerability analytic: Exploring hybrid methodologies for human dimensions of climate change research in the Himalayas R Chakraborty, AS Daloz, T L’Ecuyer, A Hicks, S Young, Y Kang, M Shah Himalayan Weather and Climate and their Impact on the Environment, 493-524, 2020 | 1 | 2020 |
| Global assessment of Vegetation Index and Phenology Lab (VIP) and Global Inventory Modeling and Mapping Studies (GIMMS) version 3 products. M Marshall, E Okuto, Y Kang, E Opiyo, M Ahmed Biogeosciences Discussions 12 (23), 2015 | 1 | 2015 |
| Developing a Remote Sensed Cover Crop Dataset for the US Midwest using Harmonized Landsat Sentinel (HLS) K Sogomo, Y Kang, T Bowles, F Gao AGU23, 2023 | | 2023 |
