Overview and Current Status of Remote Sensing
Applications Based on Unmanned Aerial Vehicles
(UAVs)
Gonzalo Pajares
Abstract
Remotely Piloted Aircraft (
RPA
) is presently in continuous
development at a rapid pace. Unmanned Aerial Vehicles
(
UAVs
) or more extensively Unmanned Aerial Systems (
UAS
)
are platforms considered under the
RPAs
paradigm. Simulta-
neously, the development of sensors and instruments to be
installed onboard such platforms is growing exponentially.
These two factors together have led to the increasing use of
these platforms and sensors for remote sensing applications
with new potential. Thus, the overall goal of this paper is
to provide a panoramic overview about the current status
of remote sensing applications based on unmanned aerial
platforms equipped with a set of specific sensors and instru-
ments. First, some examples of typical platforms used in
remote sensing are provided. Second, a description of sensors
and technologies is explored which are onboard instruments
specifically intended to capture data for remote sensing ap-
plications. Third, multi-
UAVs
in collaboration, coordination,
and cooperation in remote sensing are considered. Finally,
a collection of applications in several areas are proposed,
where the combination of unmanned platforms and sensors,
together with methods, algorithms, and procedures provide
the overview in very different remote sensing applications.
This paper presents an overview of different areas, each inde-
pendent from the others, so that the reader does not need to
read the full paper when a specific application is of interest.
Introduction
Remote sensing refers to the technique of capturing informa-
tion at a distance (remotely) by specific instruments (sen-
sors). Traditionally, remote sensing has been associated with
satellites or manned aircraft with a set of airborne sensors. In
the last decade, the increasing developments and improve-
ments in unmanned platforms, together with the development
of sensing technologies installed onboard of such platforms,
provide excellent opportunities for remote sensing applica-
tions. Indeed, they can offer high versatility and flexibility, as
compared to airborne systems or satellites, and can oper-
ate rapidly without planned scheduling. In remote sensing
operations with high human risk, lives can be safeguarded.
Additionally, they can fly at low altitudes and slowly, with
the ability of acquiring spatial and temporal high resolution
data, representing important advantages against conventional
platforms that have been broadly used over the years.
Watts
et al.
(2012), Dalamagkidis
et al.
(2012), and Ander-
son and Gaston (2013) provided a classification and use of
platforms where an important issue that determines this clas-
sification is the altitude they can fly, ranging from a few meters
up to 9,000 m or more. Micro- and nano- air vehicles can fly
at low attitudes with limited flight duration because of their
battery or energy system’s capabilities. There are vehicles with
the ability to fly at medium and high altitudes with flight dura-
tions ranging from minutes to hours, i.e., from five minutes
to 30 hours. The horizontal range of the different platforms
is also limited by the power of the communications system,
which should ensure contact with a ground station, again
ranging from meters to kilometers. Communications using sat-
ellite input can also be used, expanding the operational range.
There are several different categorizations for unmanned aerial
platforms depending on the criterion applied (Nonami
et al.
,
2010). Perhaps the most extensive and current classifications
can be found in Blyenburgh (2014) with annual revisions.
An auto platform or remotely controlled platform through
a remote station together with a communication system,
including the corresponding protocol, constitutes what is
known an Unmanned Aircraft System (
UAS
) (Gertler, 2012).
According to Yan
et al.
(2009) and Gupta
et al.
(2013),
UAS
are considered as the full system, including the aircraft, the
remote control station and all of the ground support elements,
communication links, air traffic control, and launching and
recovery system, as may be required (this is the opinion of
the Civil Aviation Authority (CAA, 2015)). Unmanned Aerial
Vehicles (
UAVs
) are included in the category of
UAS
, i.e., they
can fly autonomously, although they can be also remotely
controlled (The
UAV
, 2015). From the standpoint of remote
sensing, the equipment of
UAS
is required for capturing
information, which is later conveniently handled (processed,
analyzed, or stored), but the term “
UAV
” is commonly used in
remote sensing. Therefore, in this paper, we will refer to
UAVs
under the perspective of remote sensing operations, includ-
ing drones, gliders, (quad-, hexa-, octo-) copters, helicopters,
balloon-launched gliders, airships, or stratospheric balloon
systems and more broadly, any unmanned vehicle with the
ability to fly auto-controlled using processors onboard, re-
motely controlled with human supervision based on a ground
station (remotely piloted aircraft;
RPA
) or through another aeri-
al vehicle under coordination. Certainly, from a strict point of
view, all these systems should be considered as
RPA
systems,
because they need human supervision; full autonomy is not
generally yet achieved. Nevertheless, as mentioned earlier,
throughout this paper we will refer to them as
UAVs
. This
overview is focused on remote sensing applications based on
small
UAVs
of different categories flying at relatively low alti-
tudes with different take-off and landing systems, including
Vertical-Take-Off-and-Landing (
VTOL
), where
UAVs
operate in
different scenarios and situations. The potential use of
UAVs
Department of Software Engineering and Artificial Intelligence,
Faculty of Informatics, University Complutense of Madrid,
Madrid 28040, Spain (
).
Photogrammetric Engineering & Remote Sensing
Vol. 81, No. 4, April 2015, pp. 281–329.
0099-1112/15/281–329
© 2015 American Society for Photogrammetry
and Remote Sensing
doi: 10.14358/PERS.81.4.281
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
April 2015
281
