Liujun Zhu (朱榴骏)

About Liujun Zhu (朱榴骏)

Liujun Zhu (朱榴骏), With an exceptional h-index of 15 and a recent h-index of 12 (since 2020), a distinguished researcher at Monash University, specializes in the field of Radar, Soil Moisture.

His recent articles reflect a diverse array of research interests and contributions to the field:

Spatial downscaling of SMAP radiometer soil moisture using radar data: Application of machine learning to the SMAPEx and SMAPVEX campaigns

A cross-resolution transfer learning approach for soil moisture retrieval from Sentinel-1 using limited training samples

Calculation of CO2 Emissions from China at Regional Scales Using Remote Sensing Data

基于无人机正射影像的城市居民区植被 分类 DeepLabV3+ 模型改进实验.

Advances in remote/aerial sensing techniques for monitoring soil health.

Projecting live fuel moisture content via deep learning

Time series soil moisture retrieval from SAR data: Multi-temporal constraints and a global validation

Machine Learning Methods for 1 km Soil Moisture Retrieval from Sentinel-1: An Evaluation with Limited Training Samples

Liujun Zhu (朱榴骏) Information

University

Position

___

Citations(all)

684

Citations(since 2020)

578

Cited By

287

hIndex(all)

15

hIndex(since 2020)

12

i10Index(all)

16

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Liujun Zhu (朱榴骏) Skills & Research Interests

Radar

Soil Moisture

Top articles of Liujun Zhu (朱榴骏)

Spatial downscaling of SMAP radiometer soil moisture using radar data: Application of machine learning to the SMAPEx and SMAPVEX campaigns

Science of Remote Sensing

2024/2/21

A cross-resolution transfer learning approach for soil moisture retrieval from Sentinel-1 using limited training samples

Remote Sensing of Environment

2024/2/1

Calculation of CO2 Emissions from China at Regional Scales Using Remote Sensing Data

Remote Sensing

2024/1/31

基于无人机正射影像的城市居民区植被 分类 DeepLabV3+ 模型改进实验.

Geography & Geographic Information Science

2023/5/1

Advances in remote/aerial sensing techniques for monitoring soil health.

2023/4/5

Projecting live fuel moisture content via deep learning

International Journal of Wildland Fire

2023/3/20

Time series soil moisture retrieval from SAR data: Multi-temporal constraints and a global validation

Remote Sensing of Environment

2023/3/15

Machine Learning Methods for 1 km Soil Moisture Retrieval from Sentinel-1: An Evaluation with Limited Training Samples

2023/11/6

Evaluation of the Tau-Omega Model over a Dense Corn Canopy at P-and L-band

IEEE Geoscience and Remote Sensing Letters

2023/9/15

Long‐Term Changes and Influencing Factors of Water Quality in Aquaculture Dominated Lakes Unveiled by Sediment Records and Time Series Remote Sensing Images

Journal of Geophysical Research: Biogeosciences

2022/11

Multi-modal temporal CNNs for live fuel moisture content estimation

Environmental Modelling & Software

2022/10/1

An advanced change detection method for time-series soil moisture retrieval from Sentinel-1

Remote Sensing of Environment

2022/9/15

An improved approach of dry snow density estimation using C-band synthetic aperture radar data

ISPRS Journal of Photogrammetry and Remote Sensing

2022/9/1

Evaluation of the tau-omega model over bare and wheat-covered flat and periodic soil surfaces at P-and L-band

Remote Sensing of Environment

2022/5/1

Impact of random and periodic surface roughness on P-and L-band radiometry

Remote Sensing of Environment

2022/2/1

Live fuel moisture content estimation from MODIS: A deep learning approach

ISPRS Journal of Photogrammetry and Remote Sensing

2021/9/1

On the impact of C-band in place of L-band radar for SMAP downscaling

Remote Sensing of Environment

2020/12/15

Stochastic ensemble methods for multi-SAR-mission soil moisture retrieval

Remote Sensing of Environment

2020/12/15

Soil moisture retrieval depth of P-and L-band radiometry: Predictions and observations

IEEE Transactions on Geoscience and Remote Sensing

2020/10/7

The soil moisture active passive experiments: Validation of the SMAP products in Australia

IEEE Transactions on Geoscience and Remote Sensing

2020/7/21

See List of Professors in Liujun Zhu (朱榴骏) University(Monash University)

Co-Authors

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