Jaese Lee 🌍
Jaese Lee

Graduate Student

IRIS lab

About Me

I specialize in remote sensing (RS), with a focus on passive microwave (PMW) measurements driven by radiative transfer modeling (RTM) and artificial intelligence (AI). My research interests include PMW-based retrieval of soil moisture (SM) and vegetation optical depth (VOD), as well as their environmental applications .

Download CV
Interests
  • AI for RS
  • SM and VOD Retrieval from PMW
  • RS-based Eco-hydrological studies
Education

  • Combined M.S. and Ph.D. Environmental Science and Engineering

    Ulsan Institute of Science and Technology (UNIST)

My Research

I am studying two topics.

(1) SM retrieval accuracy improvement using AI incorporating radiative transfer modeling (Lee et al., 2024b).

(2) Harmonized SM and TB data creation using an AI and RTM (Lee et al., 2024a).

I am currently trying to extend my experience to L-band VOD.

Please reach out to collaborate 😃

Recent Publications
ASCAT2SMAP: image-to-image translation to obtain L-band-like soil moisture from C-band satellite data
ASCAT2SMAP: image-to-image translation to obtain L-band-like soil moisture from C-band satellite data

2024

Improved SMAP Soil Moisture Retrieval Using a Deep Neural Network-Based Replacement of Radiative Transfer and Roughness Model
Improved SMAP Soil Moisture Retrieval Using a Deep Neural Network-Based Replacement of Radiative Transfer and Roughness Model

2024

Improved soil moisture estimation: Synergistic use of satellite observations and land surface models over CONUS based on machine learning
Improved soil moisture estimation: Synergistic use of satellite observations and land surface models over CONUS based on machine learning

2022

Performance of Drought Indices in Assessing Rice Yield in North Korea and South Korea under the Different Agricultural Systems

2022

Detection of Forest Fire Damage from Sentinel-1 SAR Data through the Synergistic Use of Principal Component Analysis and K-means Clustering

2021

See all publications