Fusing Sentinel-2 and Landsat 8 Satellite Images Using a Model-Based Method

被引:10
作者
Sigurdsson, Jakob [1 ]
Armannsson, Sveinn E. [1 ]
Ulfarsson, Magnus O. [1 ]
Sveinsson, Johannes R. [1 ]
机构
[1] Univ Iceland, Fac Elect & Comp Engn, Hjardarhagi 2-6, IS-107 Reykjavik, Iceland
关键词
data fusion; image sharpening; multispectral (MS) multiresolution images; super-resolution; Sentinel-2; Landsat; 8; REMOTE-SENSING DATA; SURFACE REFLECTANCE; RESOLUTION;
D O I
10.3390/rs14133224
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Copernicus Sentinel-2 (S2) constellation comprises of two satellites in a sun-synchronous orbit. The S2 sensors have three spatial resolutions: 10, 20, and 60 m. The Landsat 8 (L8) satellite has sensors that provide seasonal coverage at spatial resolutions of 15, 30, and 60 m. Many remote sensing applications require the spatial resolutions of all data to be at the highest resolution possible, i.e., 10 m for S2. To address this demand, researchers have proposed various methods that exploit the spectral and spatial correlations within multispectral data to sharpen the S2 bands to 10 m. In this study, we combined S2 and L8 data. An S2 sharpening method called Sentinel-2 Sharpening (S2Sharp) was modified to include the 30 m and 15 m spectral bands from L8 and to sharpen all bands (S2 and L8) to the highest resolution of the data, which was 10 m. The method was evaluated using both real and simulated data.
引用
收藏
页数:11
相关论文
共 43 条
[1]   Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis [J].
Aiazzi, B ;
Alparone, L ;
Baronti, S ;
Garzelli, A .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2002, 40 (10) :2300-2312
[2]   Nearshore Bathymetry From Fusion of Sentinel-2 and ICESat-2 Observations [J].
Albright, Andrea ;
Glennie, Craig .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 18 (05) :900-904
[3]  
[Anonymous], USGS EROS Archive - Sentinel-2: Spectral Bands and Resolution
[4]  
[Anonymous], 2002, DATA FUSION DEFINITI
[5]   Constructing 10-m NDVI Time Series From Landsat 8 and Sentinel 2 Images Using Convolutional Neural Networks [J].
Ao, Zurui ;
Sun, Ying ;
Xin, Qinchuan .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 18 (08) :1461-1465
[6]  
Armannsson S. E., 2021, 2021 IEEE INT GEOSCI, P2871, DOI [https://doi.org/10.1109/IGARSS47720.2021.9553346, DOI 10.1109/IGARSS47720.2021.9553346]
[7]   A Comparison of Optimized Sentinel-2 Super-Resolution Methods Using Wald's Protocol and Bayesian Optimization [J].
Armannsson, Sveinn E. ;
Ulfarsson, Magnus O. ;
Sigurdsson, Jakob ;
Nguyen, Han V. ;
Sveinsson, Johannes R. .
REMOTE SENSING, 2021, 13 (11)
[8]   Hyperspectral Remote Sensing Data Analysis and Future Challenges [J].
Bioucas-Dias, Jose M. ;
Plaza, Antonio ;
Camps-Valls, Gustavo ;
Scheunders, Paul ;
Nasrabadi, Nasser M. ;
Chanussot, Jocelyn .
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2013, 1 (02) :6-36
[9]   The Perception-Distortion Tradeoff [J].
Blau, Yochai ;
Michaeli, Tomer .
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, :6228-6237
[10]   Super-Resolving Multiresolution Images With Band-Independent Geometry of Multispectral Pixels [J].
Brodu, Nicolas .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2017, 55 (08) :4610-4617