Utility of multitemporal lidar for forest and carbon monitoring: Tree growth, biomass dynamics, and carbon flux K Zhao, JC Suarez, M Garcia, T Hu, C Wang, A Londo Remote Sensing of Environment 204, 883-897, 2018 | 238 | 2018 |
Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm K Zhao, MA Wulder, T Hu, R Bright, Q Wu, H Qin, Y Li, E Toman, B Mallick, ... Remote sensing of Environment 232, 111181, 2019 | 228 | 2019 |
Estimating snow water equivalent with backscattering at X and Ku band based on absorption loss Y Cui, C Xiong, J Lemmetyinen, J Shi, L Jiang, B Peng, H Li, T Zhao, D Ji, ... Remote Sensing 8 (6), 505, 2016 | 56 | 2016 |
Using stable isotopes to quantify water uptake from different soil layers and water use efficiency of wheat under long-term tillage and straw return practices Z Liu, F Ma, T Hu, K Zhao, T Gao, H Zhao, T Ning Agricultural Water Management 229, 105933, 2020 | 44 | 2020 |
Estimation of high‐resolution near‐surface freeze/thaw state by the integration of microwave and thermal infrared remote sensing data on the Tibetan Plateau T Zhao, J Shi, T Hu, L Zhao, D Zou, T Wang, D Ji, R Li, P Wang Earth and Space Science 4 (8), 472-484, 2017 | 41 | 2017 |
Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine T Hu, EM Toman, G Chen, G Shao, Y Zhou, Y Li, K Zhao, Y Feng ISPRS Journal of Photogrammetry and Remote Sensing 176, 250-261, 2021 | 37 | 2021 |
A continuous global record of near-surface soil freeze/thaw status from AMSR-E and AMSR2 data T Hu, T Zhao, K Zhao, J Shi International Journal of Remote Sensing 40 (18), 6993-7016, 2019 | 33 | 2019 |
Impacts of forest loss on local climate across the conterminous United States: Evidence from satellite time-series observations Y Li, Y Liu, G Bohrer, Y Cai, A Wilson, T Hu, Z Wang, K Zhao Science of the Total Environment 802, 149651, 2022 | 23 | 2022 |
Parameterization of the freeze/thaw discriminant function algorithm using dense in-situ observation network data P Wang, T Zhao, J Shi, T Hu, A Roy, Y Qiu, H Lu International journal of digital earth, 2018 | 22 | 2018 |
High-resolution mapping of freeze/thaw status in China via fusion of MODIS and AMSR2 data T Hu, T Zhao, J Shi, S Wu, D Liu, H Qin, K Zhao Remote Sensing 9 (12), 1339, 2017 | 18 | 2017 |
Assessing long‐term impacts of cover crops on soil organic carbon in the central US Midwestern agroecosystems Z Qin, K Guan, W Zhou, B Peng, J Tang, Z Jin, R Grant, T Hu, MB Villamil, ... Global change biology 29 (9), 2572-2590, 2023 | 16 | 2023 |
Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield T Hu, X Zhang, G Bohrer, Y Liu, Y Zhou, J Martin, Y Li, K Zhao Agricultural and Forest Meteorology 336, 109458, 2023 | 14 | 2023 |
How to better estimate leaf area index and leaf angle distribution from digital hemispherical photography? Switching to a binary nonlinear regression paradigm K Zhao, Y Ryu, T Hu, M Garcia, Y Li, Z Liu, A Londo, C Wang Methods in Ecology and Evolution 10 (11), 1864-1874, 2019 | 13 | 2019 |
Forest loss is significantly higher near clustered small dams than single large dams per megawatt of hydroelectricity installed in the Brazilian Amazon S Nickerson, G Chen, PM Fearnside, CJ Allan, T Hu, LMT de Carvalho, ... Environmental Research Letters 17 (8), 084026, 2022 | 7 | 2022 |
Development and analysis of a continuous record of global near-surface soil freeze/thaw patterns from AMSR-E and AMSR2 data T Hu, T Zhao, J Shi, T Wang, D Ji, AA Bitar, B Peng, Y Cui The Cryosphere Discussions 2016, 1-24, 2016 | 7 | 2016 |
Influence of varying solar zenith angles on land surface phenology derived from vegetation indices: a case study in the harvard forest Y Li, Z Jiao, K Zhao, Y Dong, Y Zhou, Y Zeng, H Xu, X Zhang, T Hu, L Cui Remote Sensing 13 (20), 4126, 2021 | 5 | 2021 |
Different nitrogen fertilizer management practices on crop productivity and environmental outcomes across the US Midwest Z Li, K Guan, T Hu, W Zhou, B Peng, ED Nafziger, RF Grant, Z Jin, J Tang, ... AGU23, 2023 | | 2023 |
SYMFONI: the “system-of-systems” solution to quantify soil carbon and GHG outcomes for the broad US croplands-solidifying the foundation for the US climate-smart agriculture … K Guan, B Peng, T Hu, Z Qin, Z Li, R Qin, L Ye, Z Ma, W Zhou, S Wang, ... AGU23, 2023 | | 2023 |
Quantifying field-level carbon intensity based on cradle to farm-gate life cycle assessment: uncertainty assessment under different management practices for the US Midwestern … Z Qin, K Guan, T Hu, Y Li, B Peng, W Zhou, C Hao, X Liu, RF Grant, L Ye, ... AGU23, 2023 | | 2023 |
Assessing environmental and agronomic benefits of cover crops for the US Corn Belt Z Qin, K Guan, T Hu, W Zhou, B Peng, J Tang, Z Jin, RF Grant, S Mirsky, ... AGU23, 2023 | | 2023 |