Supervised conversion from Landsat-8 images to Sentinel-2 images with deep learning
In a specific remote sensing study design, the utilization of images from a particular satellite is necessary. However, the images might be unavailable in a certain time range. Therefore, a conversion method from available remote sensing images at the time range is required. In this paper, we propos...
Gespeichert in:
Veröffentlicht in: | European journal of remote sensing 2021-01, Vol.54 (1), p.182-208 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | In a specific remote sensing study design, the utilization of images from a particular satellite is necessary. However, the images might be unavailable in a certain time range. Therefore, a conversion method from available remote sensing images at the time range is required. In this paper, we proposed machine learning models that are capable to convert Landsat-8 images to Sentinel-2 images. The models are inspired by the advancement of super-resolution model based on Deep learning. The result of this study shows that the proposed models can predict Sentinel-2 images which are quantitatively and qualitatively similar to the original images. |
---|---|
ISSN: | 2279-7254 2279-7254 |
DOI: | 10.1080/22797254.2021.1875267 |