IEEE Geoscience and Remote Sensing Magazine - September 2022 - 242

◗ Coleambally irrigation area (CIA) [252] contains 17
Landsat/MODIS pairs from Coleambally Irrigation
Area, Australia, at 25-m spatial resolution. Images were
obtained during a single summer season but have strong
spatial heterogeneity.
◗ Lower Gwydir Catchment (LGC) [252] contains 14
Landsat/MODIS pairs from LGC, Australia, at 25-m
spatial resolution. Images were obtained during a whole
year, which also included a major flood. This renders
the data set ideal for the study of abrupt and unpredictable
changes in time series.
◗ Ar Horqin Banner (AHB) [253] contains 27 Landsat/
MODIS pairs from ARB, China, over a span of five years.
It is intended for the study of phenological changes in
rural areas.
◗ Tianjin [253] contains 27 Landsat/MODIS pairs from
Tianjin, China, over a span of six years. It is intended for
the study of phenological changes in urban areas.
◗ Daxing [253] contains 29 Landsat/MODIS pairs from
Daxing, China, over a span of six years. It is intended for
the study of land cover changes.
◗ The Gaofen Image Data Set [254] contains 150 Gaofen-2
images (RGB and NIR bands) from many regions in China
with 4-m spatial resolution. It is intended for scene
classification and land cover segmentation.
◗ Kelvin's PROBA-V SR Data Set [211] contains 1,160 images
from the PROBA-V satellite (red and NIR bands) from
several locations around the globe at different points in
time. Each data point contains an HR image of 100-m
resolution and several LR images of 300-m resolution.
◗ Kaggle's Draper Satellite Image Chronology [255] contains
1,720 aerial RGB images from California, United
States, over a period of five days.
◗ Diverse Real-World Image SR [256] contains 31,970 LR
image patches including aerial images.
◗ Pavia Center [118] was acquired by reflective optics system
imaging spectrometer (ROSIS) over the city of Pavia,
Italy, in the wavelength range of 430 to 860 nm. It
contains 115 spectral bands and is of size 1,096 # 1,096.
◗ Houston [118] was acquired by an ITRES-compact airborne
spectrographic imager (CASI) 1500 HS sensor
over the campus of the University of Houston and its
neighboring urban areas. Each HS image comprises 144
bands covering the spectral range of 380 to 1,050 nm,
and each band contains 349 # 1,905 pixels with a spatial
resolution of 2.5 m
◗ Los Angeles [118] was acquired over a port in the city
of Los Angeles by the Hyperion sensor mounted on the
Earth Observing-1 (EO-1) satellite. The HS image contains
242 spectral bands with a spatial resolution of 30 m.
◗ Botswana [257] was acquired over the Okavango Delta
in Botswana by the Hyperion sensor mounted on the
EO-1 satellite. The HS image contains 242 spectral bands
with a spatial resolution of 30 m.
◗ Hobart [113], acquired by the IKONOS sensor, represents
an urban and harbor area of Hobart, Australia. The
242
MS sensor is characterized by four bands (RGB and NIR)
and also a PAN channel with band range from 450 to
900 nm. The resolution of MS is 4 m and of PAN is 1 m.
◗ Sundarbans [113], obtained by the QuickBird sensor, represents
a forest area of Sundarbans in India. This data set
provides an HR PAN image with a spectral cover range
from 760 to 850 nm and a resolution of 0.6 m as well as
a four-band (RGB and NIR) MS image with a resolution
of 2.4 m.
◗ Washington DC Mall [139] covers an urban area in the
Washington, D.C., National Mall. The size of the degraded
HS image is 256 # 60 and that of the PAN image is
1,280 # 300.
◗ Moffett Field [139] covers a mixed urban/rural area in
Moffett Field, California. The size of the degraded HS
image is 79 # 37 with 10-m resolution and that of the
PAN image is 395 # 185 with 20-m resolution.
◗ Salinas Scene [139] covers a rural area in Salinas Valley,
California. The size of the degraded HS image is 102 #
43 and that of the PAN image is 510 # 215.
◗ Chikusei [258] was captured by Headwall's Hyperspec
Visible and Near-Infrared, series C imaging sensor over
Chikusei, Ibaraki, Japan, on 29 July 2014. The data set
contains 128 bands in the spectral range of 363-1,018 nm.
The PAN image has 300 # 300 pixels with a spatial resolution
of 2.5 m.
◗ Foster [258] has 33 spectral channels from 400 to 720 nm
with 10 nm per band. The original size of each HS image
in the Foster data set is 1,341 # 1,022.
ADVANCEMENTS IN COMPUTER VISION
Spatial enhancement, or SR, is being thoroughly investigated
in general CV, and a great number of methods have been
proposed that build on previous research and expand the
state of the art. Hence, in the CV field, some informative review
articles have been published in the last couple of years
focusing on CV DL algorithms for image downscaling, such
as [12] and [16]. In this section, we present some of the most
promising and innovative studies in CV published over the
last few years that, to the best of our knowledge, have not
yet been used in an RS context, hoping to provide a source
of inspiration for further applications in the RS field.
Most of the studies found in the literature train models
on synthetic data sets where LR counterparts are synthetically
constructed, usually via a single predefined degradation
algorithm, such as bicubic interpolation. This raises
the question of whether such a model can properly generalize
to real-world images that have undergone arbitrary degradation
processes. To that end, a number of publications
(e.g., SFTMD [259] and DAN [260], [261]) explore deep
networks that are trained to jointly handle the downscaling
task and learn the appropriate blur kernel in an end-toend
fashion. This family of methods is usually referred to
as blind SR.
In some cases, the available data set comprises LR images
that need to be downscaled, along with a number of HR
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE SEPTEMBER 2022
IEEE Geoscience and Remote Sensing Magazine - September 2022

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