Artikler med krav om offentlig adgang - Jungho ImFå flere oplysninger
Ikke tilgængelige nogen steder: 2
On the use of machine learning based ensemble approaches to improve evapotranspiration estimates from croplands across a wide environmental gradient
Y Bai, S Zhang, N Bhattarai, K Mallick, Q Liu, L Tang, J Im, L Guo, J Zhang
Agricultural and Forest Meteorology 298, 108308, 2021
Krav: National Natural Science Foundation of China, Luxembourg National Research Fund
Spatiotemporal downscaling approaches for monitoring 8-day 30 m actual evapotranspiration
Y Ke, J Im, S Park, H Gong
ISPRS Journal of Photogrammetry and Remote Sensing 126, 79-93, 2017
Krav: National Natural Science Foundation of China
Tilgængelige et sted: 11
Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations
Y Ke, J Im, J Lee, H Gong, Y Ryu
Remote sensing of environment 164, 298-313, 2015
Krav: National Natural Science Foundation of China
Downscaling of MODIS one kilometer evapotranspiration using Landsat-8 data and machine learning approaches
Y Ke, J Im, S Park, H Gong
Remote Sensing 8 (3), 215, 2016
Krav: National Natural Science Foundation of China
Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea
S Park, M Shin, J Im, CK Song, M Choi, J Kim, S Lee, R Park, J Kim, ...
Atmospheric Chemistry and Physics 19 (2), 1097-1113, 2019
Krav: US National Aeronautics and Space Administration
Machine learning approaches for detecting tropical cyclone formation using satellite data
M Kim, MS Park, J Im, S Park, MI Lee
Remote Sensing 11 (10), 1195, 2019
Krav: US National Aeronautics and Space Administration
Comparison of five spatio-temporal satellite image fusion models over landscapes with various spatial heterogeneity and temporal variation
M Liu, Y Ke, Q Yin, X Chen, J Im
Remote Sensing 11 (22), 2612, 2019
Krav: National Natural Science Foundation of China
Zooplankton and micronekton respond to climate fluctuations in the Amundsen Sea polynya, Antarctica
HS La, K Park, A Wåhlin, KR Arrigo, DS Kim, EJ Yang, A Atkinson, ...
Scientific Reports 9 (1), 10087, 2019
Krav: Swedish Research Council, UK Natural Environment Research Council
A deep-learning-based tree species classification for natural secondary forests using unmanned aerial vehicle hyperspectral images and LiDAR
Y Ma, Y Zhao, J Im, Y Zhao, Z Zhen
Ecological Indicators 159, 111608, 2024
Krav: National Natural Science Foundation of China
Towards accurate individual tree parameters estimation in dense forest: optimized coarse-to-fine algorithms for registering UAV and terrestrial LiDAR data
Y Zhao, J Im, Z Zhen, Y Zhao
Giscience & remote sensing 60 (1), 2197281, 2023
Krav: National Natural Science Foundation of China
Multi-Platform LiDAR for Non-Destructive Individual Aboveground Biomass Estimation for Changbai Larch (Larix olgensis Henry) Using a Hierarchical Bayesian …
M Wang, J Im, Y Zhao, Z Zhen
Remote Sensing 14 (17), 4361, 2022
Krav: National Natural Science Foundation of China
Novel Features of Canopy Height Distribution for Aboveground Biomass Estimation Using Machine Learning: A Case Study in Natural Secondary Forests
Y Ma, L Zhang, J Im, Y Zhao, Z Zhen
Remote Sensing 15 (18), 4364, 2023
Krav: National Natural Science Foundation of China
Estimation of shrub willow biophysical parameters across time and space from Sentinel-2 and unmanned aerial system (UAS) data
J Xu, LJ Quackenbush, TA Volk, J Im
Field crops research 287, 108655, 2022
Krav: US Department of Agriculture
Oplysninger om publikation og økonomisk støtte registreres automatisk af et computerprogram