relevant operations. Automatic detection of heat loss in win-
dows by using autonomous and teleoperated helicopters was
addressed in Martinez-de-Dios and Ollero (2006).
Wefelscheid
et al.
(2011) used an octo-copter (1.5 kg weight
and payload of 500 g) for 3
D
reconstruction of buildings through
a consumer camera with prime lens and weight of 285 g.
Moranduzzo and Melgani (2014a and 2014b) used an
UAV
for automatic detection of cars in visible images, captured by
a commercial camera. Feature extraction and machine learn-
ing based on support vector machines were the approaches
used. Hierarchical image processing operations were applied
expedite the car identification process.
Regarding applications in man-made infrastructures, Feng
et al.
(2009) applied image processing techniques to identify a
road and its geometry from an unmanned fixed-wing platform
with weight of
40 kg, equipped with transmission and storage
capabilities. Metni and Hamel (2007) described the dynamic
of
UAVs
for monitoring of structures and maintenance of
bridges based on simulation results.
Rodriguez-Gonzalvez
et al.
(2014) proposed a methodol-
ogy for a 3
D
reconstruction of complex scenarios applied to
electrical substations and demonstrating that camera-based
systems onboard
UAVs
can compete with laser-based scanners.
An octo-copter was used for such purpose, equipped with a
stabilized platform for a visual commercial camera.
Conclusions and Future Trends
This work provides an overview of papers and publications
on the status of remote sensing applications based on
UAVs
:
extensively
UAS
, as special
RPA
systems. Over 600 studies,
coming from peer-reviewed works and relevant websites have
been reviewed to provide this overview. The proliferation of
repositories and databases containing links to papers, proj-
ects, and publications is overwhelming; the amount of mate-
rial they contain makes it almost impossible for a complete
referencing (Science.gov Alliance, 2015).
The progress made in recent years regarding this topic
to create this overview becomes clear. Indeed, an important
number of proposals have been studied and international
events are held periodically on this topic (ARSS, 2014). This
overview starts with a brief description of platforms and its
use in remote sensing. Sensors technologies, instruments, and
their abilities for capturing information for remote sensing
purposes have also been presented. An extensive review was
carried out through different applications in a variety of areas
where these systems are being adapted to traditional remote
sensing applications.
Some conclusions can be considered after this overview.
First, platforms and sensors are converging towards each oth-
er to accommodate an ever increasing demand for use. Sen-
sors and platforms are being matched in every way; an similar
example of this fusion can be found in the remotely control
applications based on Smart phones (Parrot, 2015). More and
more areas of application appear demonstrating where
UAVs
become efficient. Second, this technology has allowed for the
development of numerous methods, procedures, and strate-
gies specifically adapted for these systems from a unique
perspective of the problem to be solved. Third, successes
obtained together with economical aspects derived from their
relatively low cost are enhancing their use and extending the
range of performance and applications.
For over a decade, Petrie (2001) said the future of
UAVs
looked promising in remote sensing, confirmed more recently
by Tully (2013). In this regard, the relative low cost with
respect to the benefits obtained provides a promising future
projection.
AUVSI
(2015) reported on the economic impact of
UAVs
integration in the United States based on potential mar-
kets, including precision agriculture, safety, and many others.
According to Hambling (2014), the future outlook for
the development of
UAVs
is in cooperation with rapid and
efficient operations. This aspect is of particular interest for
disaster monitoring, where the main goal is to cover the larg-
est area as possible. Surveillance, monitoring, crop pollina-
tion, and traffic control appear as promising areas, all from
the remote sensing point of view. Apart from the above, new
insights and perspectives are continuously appearing as re-
ported in Handwerk (2013).
Miniaturization of
UAVs
can be a part of some roles, from
the point of view of remote sensing, there are some opportu-
nities oriented to the development of very small
UAVs
, like the
ones imitating birds (Betriu, 2014), equipped with legs that
can perch on branches in the trees. Micro-drones (µ-drones)
or micro-air vehicles (MAVs) are insect-sized “aircrafts”
which are being included in the new era of remote sensing.
They were proposed several years ago with promising expec-
tations (Nonami, 2007).
Nevertheless, industrial development will occur in both,
platforms and associated elements, to form the full
UAV
system (remote control station, communication links or air
traffic control) and integrated in the national airspace systems
(Lasica, 2013).
Mass-media and general media are contributing positively
in the dissemination of
UAVs
as future systems in several ap-
plications, including remote sensing. The Guardian (Napoli,
2012), Reuters (Krishnamurthy, 2013), El Mundo (Treceño,
2013), Antena3 TV (2015), and Expansión (2015) are some
examples of general newspapers, news agencies, and TVs.
Specific sites can be found at Energy Global (Rehn, 2014),
Gunderson (2014), or James (2014).
As a result, the population is becoming aware of
UAVs
,
contributing new ideas according to the needs expressed or
detected, while companies are taking on new initiatives and
undertaking new challenges with impact on the economy
(Hall and Coyne, 2014).
Based on some existing studies (
GAU
, 2014), the compound
annual growth rate (
CAGR
) in the
UAV
remote sensing market
is 5.39 percent over the period 2013 to 2018. Due to this in-
crease, it is expected the advent of new applications in remote
sensing with
UAVs
, as well as the improvement and outperfor-
mance of the existing ones (Zhang and Wu, 2014).
Acknowledgments and Disclaimer
Thanks to the following persons, companies and institutions
that kindly and selflessly have provided the material exhib-
ited in the different figures included in this review, allowing
for the illustration of unmanned platforms and results derived
from the remote sensing applications.
They are listed in the order they appear in the paper: (a)
ISCAR-
UCM
Group Madrid, Spain, with special thanks to active mem-
bers J.M. Cruz, J.A. López-Orozco, and E. Besada in the project
entitled
Autonomous System for Locating and Acting in the
Face of Sea Pollutants
(DPI2013-46665-C1), funded by the
Spanish Ministry of Economy and Competition, where
UAVs
and
UGVs
work together and in collaboration; (b) Carto
UAV
, La
Coruña, Spain; (c) AirRobot GmbH & Co. KG, Arnsberg, Ger-
many; (d) QuantaLab-
IAS
-
CSIC
, Cordoba, Spain; (e) A. Arjonilla;
eDroniX, Madrid, Spain; (f) J.R. Martínez-de-Dios and A. Olle-
ro; Robotics, Vision, and Control Group, University of Seville,
Seville, Spain; (g) L. Wallace and A. Lucieer, University of
Tasmania, Australia; and (h) F. López-Granados and J.M. Peña;
Institute for Sustainable Agriculture,
CSIC
-Córdoba, Spain.
Also this document was prepared with economic support
of the European Community, the European Union and
CONACYT
under Grant No.
FONCICYT
93829.
Special thanks to referees for their help, constructive criti-
cism, and suggestions on the original version of this paper.
310
April 2015
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
