Remote sensing, GIS, geospatial data science, machine learning, computer vision, environmental planning, fire spread modeling, natural hazards
MS Civil and Environmental Engineering, Seoul National University
BS Civil and Environmental Engineering, Seoul National University
Minho Kim has a background is in Civil and Environmental Engineering with a focus on remote sensing and GIS. He has a broad interest in remote sensing and GIS applications such as urban remote sensing, land cover mapping, GIScience, image fusion, renewable energy forecasting, and deep learning for sustainable development of cities and the environment. Previous research works include wildfire burn assessment, high resolution land cover classification, spatiotemporal fusion of thermal images, solar power forecasting, and local climate zone classification. His current research focuses on mapping vegetation fuel in the wildland urban interface and identifying wildfire risks. He also researches fire spread models using machine learning for wildfire simulations.
GEOG188/LDARCH C188 Geographic Information Systems (Fall 2022). Lead Instructor.
GEOG188/LDARCH C188 Geographic Information Systems (Fall 2021). Graduate Student Instructor for Professor John Radke.
Advanced Surveying (Spring 2021). Head TA.
Introduction to Geospatial Engineering (Spring 2021). Head TA.
Advanced Remote Sensing: VHR Imagery (Fall 2020). Head TA.
Remote Sensing (Fall 2020). Head TA.
Satellite Image Interpretation (Spring 2020). Head TA.
Leadership for Civil Engineers (Spring 2020). TA.
Spatial Informatics and Systems (Spring 2020). Head TA.
Minho Kim, Jeong, D. & Kim, Y. Local climate zone classification using a multi-scale, multi- level attention network, ISPRS Journal of Photogrammetry and Remote Sensing, 181, (345-366). https://doi.org/10.1016/j.isprsjprs.2021.09.015
Minho Kim, Song, H. & Kim, Y. Direct short-term forecast of photovoltaic power through a comparative study between COMS and Himawari-8 meteorological satellite images in a deep neural network, Remote Sensing, 12(15), (2357). https://doi.org/10.3390/rs12152357
Minho Kim, Jung, M. & Kim, Y. Histogram matching of Sentinel-2 spectral information to enhance Planetscope imagery for effective wildfire damage assessment, Korean Journal of Remote Sensing, 35(4), (517-534). https://doi.org/10.7780/kjrs.2019.35.4.3
Minho Kim, Cho, K., Kim, H. & Kim, Y. Fusion of High Resolution Land Surface Temperature Using Thermal Sharpened Images from Regression-based Urban Indices, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3, (pp247-254). https://doi.org/10.5194/isprs-annals-V-3-2020-247-2020