Events The 5th International Electronic Conference on Remote Sensing

Event submissions

Published

10.3390/ECRS2023-16294

This submission belongs to the session S1. Remote sensing systems and techniques of the event The 5th International Electronic Conference on Remote Sensing

Published date

16 Nov, 2023

Academic Editor

Luca Lelli

Citation

Reza Shah-Hosseini, Mohammad Aghdami-Nia, Saeid Homayouni, Amirhossein Rostami, Nima Ahmadian, Surrogate Modeling of MODTRAN Physical Radiative Transfer Code Using Deep Learning Regression, in Proceedings of The 5th International Electronic Conference on Remote Sensing, 7 November–21 November 2023, MDPI: Basel, Switzerland, doi: 10.3390/ECRS2023-16294

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Surrogate Modeling of MODTRAN Physical Radiative Transfer Code Using Deep Learning Regression

Mohammad Aghdami-Nia ¹

Reza Shah-Hosseini ²

Saeid Homayouni ³

Amirhossein Rostami ¹

Nima Ahmadian ⁴

1. School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

2. School of Surveying and Geospatial Eng., College of Eng., University of Tehran, Tehran, Iran

3. Centre Eau Terre Environnement, 490 rue de la Couronne, Institut National de la Recherche Scientifique, Quebec City, QC G1K 9A9, Canada

4. Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

Abstract

Keywords

Machine Learning and Deep Learning Regression

Multispectral Remote Sensing

Radiative Transfer Model

Surrogate Model