An Introduction to Remotely Sensed Data Analysis - Sampling Spatial Units for Agricultural Surveys - page 72

Table 4.2 Main characteristics of some near future satellite sensors
Spatial
resolution

Swath
(km)

Revisit days at
nadir

Off-nadir
pointing Channels

1 (40 N Lat) Yes

WorldView-3 (multi.)
[2014]

1.24 m 8 13.1 <

WorldView-3 (pan.) 31 cm 1

WorldView-3
(SWIR)

3.70 m 8

WorldView-3
(CAVIS)

30 m 12

Sentinel-2 [2014] 10 m 4 290 < 5 at equator Yes

20 m 6

60 m 3

Sentinel-3 (SLSTR)
[2014]

500 m-1 km 11 1,420 < 1 at equat. Yes

Sentinel-3 (OLCI) 300 m 21 1,270 < 2 at equat. Yes

Sentinel-3 (SRAL) 300 m 2 modes > 2 27 No

VEN S-VM1 [2014] 5.3 m 12 27.5 2 Yes

μ

HyspIRI (VSWIR) 60 m 220 145 19 Yes

HyspIRI (TIR) 60 m 8 600 5 No

quality of the observed images. RS images are typically recorded at a great distance
from the Earth s surface. As a consequence, electromagnetic energy must pass

through the atmosphere before it reaches the sensor. As a function of the wave-
lengths under consideration and the atmospheric conditions, the energy may be
substantially modified. The sensor may also modify the characteristics of the data.
Additionally, when the image is being scanned the satellite is following an orbit and
the Earth is moving. Consequently, a variety of systematic and apparently random
disturbances can degrade the image quality. Therefore, in the presence of these
degradations, it is necessary to correct the image so that it may be immediately
available to the analysts and used for practical purposes.
Image restoration is typically performed with reference to its physical charac-
teristics, and concerns the correction of distortions and errors that occur while the
sensor is acquiring the image. This is a process that is particularly analyzed by
physicists and engineers (Jensen 2004 ; Richards and Jia 2006 ). The aim of these
image restoration techniques is to produce a new image that is as close as possible
to the characteristics of the radiant energy emitted or reflected from the ground
scene. The most common distortions in RS images are due to radiometric and
geometric errors.
Radiometric errors can be caused by the dispersion of radiant energy by the
atmosphere and the sensors. The effect is a distortion of the measurement of the
brightness of the pixels in an image. Two different types of radiometric distortion
can generally affect the measured brightness values. First, it is possible that the
relative distribution of brightness in a fixed band of an image can be different to the

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