A New Spectral Harmonization Algorithm for Landsat-8 and Sentinel-2 Remote Sensing Reflectance Products Using Machine Learning: A Case Study for the Barents Sea (European Arctic)-Reference-Cited by-同舟云学术

A New Spectral Harmonization Algorithm for Landsat-8 and Sentinel-2 Remote Sensing Reflectance Products Using Machine Learning: A Case Study for the Barents Sea (European Arctic)

Published:2023 Issue: Volume:61 Page:1-19
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Asim Muhammad¹^ORCID,Matsuoka Atsushi²^ORCID,Ellingsen Pal Gunnar³^ORCID,Brekke Camilla¹^ORCID,Eltoft Torbjorn¹^ORCID,Blix Katalin¹^ORCID

Affiliation:

1. Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway

2. Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA

3. Department of Electrical Engineering, UiT The Arctic University of Norway, Narvik, Norway

Funder

The Nansen Legacy [Research Council of Norway (RCN)]

Center for Integrated Remote Sensing and Forecasting for Arctic Operations (CIRFA)

National Aeronautics and Space Administration (NASA) Research Opportunities in Space and Earth Sciences (ROSES) Project

Japan Aerospace Exploration Agency (JAXA) Global Change Observation Mission-Climate

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/09980426.pdf?arnumber=9980426

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