An Introduction to Remotely Sensed Data Analysis - Sampling Spatial Units for Agricultural Surveys - page 70

Sentinel missions of ESA (see http://www.esa.int/Our_Activities/Observing_the_
Earth/Copernicus/Overview4 ).
Proba-V (V stands for vegetation) is a small satellite that uses a redesigned
version of the vegetation imaging instruments previously on board France

s Spot-4
and Spot-5 satellites, which have been observing the Earth since 1998. It is
currently operated by ESA. It was launched very recently (May 7, 2013) to fill
the gap between the end of the SPOT missions and the upcoming Sentinel project.
However, because of the change in the Sentinel project

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s satellites, Proba-V will
assure the continuation of the VEGETATION program. Proba-V will support
applications such as land use, worldwide vegetation classification, crop monitoring,
famine prediction, food security, disaster monitoring, and biosphere studies. Proba-
V data will be available at a spatial resolution of 100 m.
The first Sentinel satellite was launched on April 3, 2014. It was specifically
created for the operational needs of the Copernicus program. Copernicus project
will provide accurate, timely, and easily accessible information to improve envi-
ronmental management. The Sentinel project is composed of five missions; the
latest is scheduled for 2020.
Other important sensors that will be launched in the near future are VEN

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S (see
http://smsc.cnes.fr/VENUS/index.htm ) and the hyperspectral HyspIRI (see http://
hyspiri.jpl.nasa.gov/ ).
It is evident from this brief review that the availability of data has been
increasing over the last few decades. In particular, it is worth noting that satellite
sensors provide images with very different spectral, spatial, temporal, and radio-
metric characteristics. Therefore, it is possible to choose an appropriate data type
for the purpose of the analysis. These characteristics represent a synopsis of the
main advantages and drawbacks of each satellite. The different features of the data
collected by the operational and near future satellite payloads described in this
section are summarized in Tables 4.1 and 4.2 .
Many image processing and analysis techniques have been developed to aid the
interpretation of RS images, and to extract information. The choice of specific
techniques or algorithms depends on the aim of each individual research project.
Image processing procedures can be divided into three broad categories: image
restoration, image enhancement, and the thematic extraction of information.
To aid the interpretation, initial data pre-processing is typically used to correct
for any distortion caused by the imaging system

μ

s characteristics and imaging
conditions. The next subsection discusses image restoration, with a particular
focus on the problem of geometric and radiometric corrections.

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4.3 Geometric and Radiometric Corrections

An ideal RS system has not yet been developed, because of imperfections in
technologies and the complexity of the morphological structure of the Earth. In
fact, it is possible to make different errors when acquiring data, which weakens the