| Use of cyclone global navigation satellite system (CyGNSS) observations for estimation of soil moisture H Kim, V Lakshmi Geophysical Research Letters 45 (16), 8272-8282, 2018 | 214 | 2018 |
| Global-scale assessment and combination of SMAP with ASCAT (active) and AMSR2 (passive) soil moisture products H Kim, R Parinussa, AG Konings, W Wagner, MH Cosh, V Lakshmi, ... Remote Sensing of Environment 204, 260-275, 2018 | 207 | 2018 |
| Impact of soil moisture on dust outbreaks in East Asia: Using satellite and assimilation data H Kim, M Choi Geophysical Research Letters 42 (8), 2789-2796, 2015 | 100 | 2015 |
| Global scale error assessments of soil moisture estimates from microwave-based active and passive satellites and land surface models over forest and mixed irrigated/dryland … H Kim, JP Wigneron, S Kumar, J Dong, W Wagner, MH Cosh, DD Bosch, ... Remote Sensing of Environment 251, 112052, 2020 | 97 | 2020 |
| Dust emission modeling using a new high‐resolution dust source function in WRF‐Chem with implications for air quality SP Parajuli, GL Stenchikov, A Ukhov, H Kim Journal of Geophysical Research: Atmospheres 124 (17-18), 10109-10133, 2019 | 80 | 2019 |
| Does AMSR2 produce better soil moisture retrievals than AMSR-E over Australia? E Cho, CH Su, D Ryu, H Kim, M Choi Remote Sensing of Environment 188, 95-105, 2017 | 59 | 2017 |
| Evaluation of the soil water content using cosmic-ray neutron probe in a heterogeneous monsoon climate-dominated region HH Nguyen, H Kim, M Choi Advances in Water Resources 108, 125-138, 2017 | 54 | 2017 |
| Evaluating the patterns of spatiotemporal trends of root zone soil moisture in major climate regions in East Asia M Zohaib, H Kim, M Choi Journal of Geophysical Research: Atmospheres 122 (15), 7705-7722, 2017 | 54 | 2017 |
| Assessment of drought conditions over Vietnam using standardized precipitation evapotranspiration index, MERRA-2 re-analysis, and dynamic land cover MH Le, H Kim, H Moon, R Zhang, V Lakshmi, LB Nguyen Journal of Hydrology: Regional Studies 32, 100767, 2020 | 49 | 2020 |
| Detecting global irrigated areas by using satellite and reanalysis products M Zohaib, H Kim, M Choi Science of the Total Environment 677, 679-691, 2019 | 47 | 2019 |
| Field evaluation of portable soil water content sensors in a sandy loam H Kim, MH Cosh, R Bindlish, V Lakshmi Vadose Zone Journal 19 (1), e20033, 2020 | 34 | 2020 |
| Development and assessment of the sand dust prediction model by utilizing microwave‐based satellite soil moisture and reanalysis datasets in East Asian desert areas H Kim, M Zohaib, E Cho, YH Kerr, M Choi Advances in Meteorology 2017 (1), 1917372, 2017 | 33 | 2017 |
| Global dynamics of stored precipitation water in the topsoil layer from satellite and reanalysis data H Kim, V Lakshmi Water Resources Research 55 (4), 3328-3346, 2019 | 31 | 2019 |
| First attempt of global-scale assimilation of subdaily scale soil moisture estimates from CYGNSS and SMAP into a land surface model H Kim, V Lakshmi, Y Kwon, SV Kumar Environmental Research Letters 16 (7), 074041, 2021 | 25 | 2021 |
| Rain-gauge network evaluations using spatiotemporal correlation structure for semi-mountainous regions Y Jung, H Kim, J Baik, M Choi TAO: Terrestrial, Atmospheric and Oceanic Sciences 25 (2), 267, 2014 | 22 | 2014 |
| Intercomparison of downscaling techniques for satellite soil moisture products D Kim, H Moon, H Kim, J Im, M Choi Advances in Meteorology 2018 (1), 4832423, 2018 | 18 | 2018 |
| True global error maps for SMAP, SMOS, and ASCAT soil moisture data based on machine learning and triple collocation analysis H Kim, W Crow, X Li, W Wagner, S Hahn, V Lakshmi Remote Sensing of Environment 298, 113776, 2023 | 15 | 2023 |
| Assessment and combination of SMAP and Sentinel-1A/B-derived soil moisture estimates with land surface model outputs in the Mid-Atlantic Coastal Plain, USA H Kim, S Lee, MH Cosh, V Lakshmi, Y Kwon, GW McCarty IEEE Transactions on Geoscience and Remote Sensing 59 (2), 991-1011, 2020 | 15 | 2020 |
| Spatial composition of AMSR2 soil moisture products by conditional merging technique with ground soil moisture data D Kim, J Lee, H Kim, M Choi Stochastic Environmental Research and Risk Assessment 30, 2109-2126, 2016 | 15 | 2016 |
| A Bayesian machine learning method to explain the error characteristics of global-scale soil moisture products H Kim, WT Crow, W Wagner, X Li, V Lakshmi Remote Sensing of Environment 296, 113718, 2023 | 14 | 2023 |
Venkataraman LakshmiUniversity of VirginiaZweryfikowany adres z virginia.edu
