| Gap Filling of High‐Resolution Soil Moisture for SMAP/Sentinel‐1: A Two‐layer Machine Learning‐based Framework H Mao, D Kathuria, N Duffield, BP Mohanty Water Resources Research 55 (8), 6986-7009, 2019 | 51 | 2019 |
| A Nonstationary Geostatistical Framework for Soil Moisture Prediction in the Presence of Surface Heterogeneity D Kathuria, B Mohanty, M Katzfuss Water Resources Research 55 (1), 729-753, 2019 | 18 | 2019 |
| Identifying barriers to adoption of irrigation scheduling tools in Rio Grande Basin TA Berthold, A Ajaz, T Olsovsky, D Kathuria Smart Agricultural Technology 1, 100016, 2021 | 9 | 2021 |
| Multiscale data fusion for surface soil moisture estimation: a spatial hierarchical approach D Kathuria, BP Mohanty, M Katzfuss Water Resources Research 55 (12), 10443-10465, 2019 | 7 | 2019 |
| First Report of Extended-Spectrum β-Lactamase (blaCTX-M1) and Colistin Resistance Gene mcr-1 in E. coli of Lineage ST648 from Cockroaches in Tunisia S Landolsi, R Selmi, L Hadjadj, A Ben Haj Yahia, K Ben Romdhane, ... Microbiology Spectrum 10 (2), e00036-21, 2022 | 5 | 2022 |
| Enhancing prediction and covariate-driven interpretation of stream flow duration curves using Machine Learning algorithms and surrogate model explanations S Jain, D Kathuria, M Schramm, R Srinivasan AGU Fall Meeting Abstracts 2021, H22A-06, 2021 | 2 | 2021 |
| STARFM-ML: A novel machine learning driven approach to fuse remote sensing data D Kathuria, B Mohanty, K Cawse-Nicholson AGU Fall Meeting Abstracts 2021, B45I-1740, 2021 | 1 | 2021 |
| Leveraging Post-Hoc Model Explanations to Gain Hydrological Insights within Machine Learning Models for Predicting Flow Duration Curves S Jain, D Kathuria, R Srinivasan, M Schramm AGU23, 2023 | | 2023 |
| A Multiscale Spatio-Temporal Big Data Fusion Algorithm from Point to Satellite Footprint Scales D Kathuria, BP Mohanty, M Katzfuss Authorea Preprints, 2023 | | 2023 |
| Remote Sensing of Soil Processes I Poster V Sehgal, B Mohanty, N Gaur, D Kathuria Fall Meeting 2022, 2022 | | 2022 |
| Deciphering the Spectra of Flowers to Map Landscape-scale Blooming Dynamics Y Angel, A Raiho, D Kathuria, PG Brodrick, D Chadwick, F Ochoa, ... AGU Fall Meeting Abstracts 2022, B22D-1446, 2022 | | 2022 |
| Sensitivity analysis on inputs to the DisALEXI algorithm using a Machine Learning interpretability method D Kathuria, K Knipper, S Jain, NE Bambach, AJ McElrone, M Anderson, ... AGU Fall Meeting Abstracts 2022, H55A-14, 2022 | | 2022 |
| Enhancing soil moisture predictions across CONUS using Big Data fusion D Kathuria, B Mohanty, M Katzfuss AGU Fall Meeting Abstracts 2022, H25Q-1306, 2022 | | 2022 |
| MULTISCALE SPATIO-TEMPORAL BIG DATA FUSION OF HYDROLOGICAL VARIABLES FROM POINT TO SATELLITE FOOTPRINT SCALES D Kathuria | | 2021 |
| Linking ECOSTRESS, MODIS and Eddy-covariance for high-resolution daily evapotranspiration D Kathuria, B Mohanty, KA Cawse-Nicholson AGU Fall Meeting Abstracts 2020, H019-03, 2020 | | 2020 |
| Looking beyond physical models and machine learning: Novel insights into soil moisture dynamics using multi-scale Big Data geostatistics B Mohanty, D Kathuria AGU Fall Meeting Abstracts 2020, H002-05, 2020 | | 2020 |
| A novel multiscale multisensor data fusion framework for massive datasets-application to soil moisture estimation D Kathuria, B Mohanty, M Katzfuss AGU Fall Meeting Abstracts 2019, H23J-2008, 2019 | | 2019 |
| Multisensor Multiscale Big Data Fusion of Soil Moisture Observations across Scales D Kathuria, BP Mohanty, M Katzfuss ASA, CSSA and SSSA International Annual Meetings (2019), 2019 | | 2019 |
| Gap filling of high-resolution soil moisture for SMAP/Sentinel-1: a two-layer machine learning-based framework. MHZ Mao HanZi, D Kathuria, N Duffield, BP Mohanty | | 2019 |
| A non-stationary multi-scale data fusion framework for soil moisture estimation D Kathuria, B Mohanty, M Katzfuss AGU Fall Meeting Abstracts 2018, H51V-1618, 2018 | | 2018 |
Mohanty, Binayak P.Professor, Texas A&M UniversityVerified email at tamu.edu
