In this overview references to papers, authors, products,
organizations, institutions, companies, associations, trade-
marks, newspapers, news agencies, TVs and others, do not
mean author’s endorsement or the University Complutense of
Madrid where the author is employed. There is no discrimi-
nation in any case, since the author has made an exhaustive
search from all available sources of information on the topics
unmanned aerial vehicles (systems) or remotely piloted sys-
tems involved in remote sensing areas and tasks. It has been
researched in preference over the last decade and especially
in the most recent years where there have been significant ad-
vances in remote sensing based on unmanned aerial platforms
Apologize, once again, for any omission.
References
Abdelkader, M., M. Shaqura, C.G. Claudel, and W. Gueaieb, 2013. A
UAV based system for real time flash flood monitoring in desert
environments using Lagrangian microsensors,
Proceedings of
the International Conferenceon Unmanned Aircraft Systems
(ICUAS), 28-31 May, Atlanta, Georgia, pp. 25–34.
Abd-Elrahman, A., 2005. Development of pattern recognition algo-
rithm for automatic bird detection from unmanned aerial vehicle
imagery,
Surveying and Land Information Science
, 65(1):37–46.
Acevo-Herrera, R., A. Aguasca, X. Bosch-Lluis, A. Camps, J. Martínez-
Fernández, N. Sánchez-Martín, and N. Pérez-Gutiérrez, 2010.
Design and first results of an UAV-borne L-band radiometer for
multiple monitoring purposes,
Remote Sens
ing, 2:1662–1679.
Achteren van, T., B. Delauré, J. Everaerts, D. Beghuin, and R. Ligot,
2007. MEDUSA: An ultra-lightweight multi-spectral camera for
a HALE UAV,
Proceedings of SPIE 6744, Sensors, Systems, and
Next-Generation Satellites
, 10 p.
Adams, S., C. Friedland, and M. Levitan, 2010. Unmanned aerial
vehicle data acquisition for damage assessment in hurricane
events,
Proceedings of the 8
th
International Workshop on Remote
Sensing for Disaster Management, 2010
, Tokyo, Japan, 7 p.
AggieAir, 2015. URL:
/
(last date accessed: 20
February 2015).
Aguasca, A., R. Acevo-Herrera, A. Broquetas, J.J. Mallorqui, and X.
Fabregas, 2013. ARBRES: light-weight CW/FM SAR sensors for
small UAVs,
Sensors
, 13:3204–3216.
Agüera, F., F. Carvajal, and M. Pérez, 2011. Measuring sunflower
nitrogen status from an unmanned aerial vehicle-based sys-
tem and an on the ground device,
International Archives of
the Photogrammetry, Remote Sensing and Spatial Information
Sciences
, 14-16 September, Zurich, Switzerland, XXXVIII-1/
C22, UAV-g 2011, Conference on Unmanned Aerial Vehicle in
Geomatics, pp. 33–37.
Ai, M., Q. Hu, J. Li, M. Wang, H. Yuan, and S. Wang, 2015. A Robust
Photogrammetric Processing Method of Low-Altitude UAV
Images,
Remote Sensing
, 7:2302-2333.
AirRobot, 2015. AirRobot GmbH & Co. KG, Projects and co-opera-
tions, URL:
(last
date accessed: 20 February 2015).
Al-Helal, H., and J. Sprinkle 2010. UAV search: Maximizing target ac-
quisition,
Proceedings of the 17
th
IEEE International Conference
and Workshops on Engineering of Computer Based Systems
(ECBS)
, pp. 9–18.
Ambrosia, V.G., S.S. Wegener, D.V. Sullivan, S.V. Buechel, S.E.
Dunagan, J.A. Brass, J. Stoneburner, and S.M. Schoenung, 2003.
Demonstrating UAV-
Acquired Real-Time
thermal data over fires,
Photogrammetric Engineering & Remote Sensing
, 69(4):391–402.
Ambrosia, V.G., and S.S. Wegener, 2009. Unmanned airborne
platforms for disaster remote sensing support,
Geoscience and
Remote Sensing
(P.G.P. Ho, editor), Chapter 5, In-Tech, Croatia,
pp. 91–114.
Ambrosia, V., E. Hinkley, T. Zajkowski, S. Wegener, D. Sullivan, F.
Enomoto, and S. Schoenung, 2009. Lesson learned: Experiences
in UAS sensor operations supporting disaster scenarios (wild-
fires) in the United States,
Proceedings of the 2009 International
Society of Remote Sensing of Environment (ISRSE)
, 04-08 May,
Stresa, Italy, pp. 1–4.
Ambrosia, V., S. Buechel, S. Wegener, D. Sullivan, F. Enomoto, E.
Hinkley, and T. Zajkowski, 2011. Unmanned airborne systems
supporting disaster observations: Near-real-time data needs,
International Archives of the Photogrammetry, Remote Sensing
and Spatial Information Sciences
, 144:1–4.
Ambrosia, V.G., S. Wegener, T. Zajkowski, D.V., Sullivan, S. Buechel,
F. Enomoto, E.A. Hinkley, B. Lobitz, and S. Schoenung, 2011.
The Ikhana UAS western states fire imaging missions: From con-
cept to reality (2006-2010),
Geocarto Int
e
rnational
, 26(2):85–101.
Amici, S., S. Turci, S. Giammanco, L. Spampinato, and F. Giulietti,
2013. UAV thermal infrared remote sensing of an Italian mud
volcano,
Advances in Remote Sensing
, 2:358–364.
Anderson, K., and K.J. Gaston, 2013. Lightweight unmanned aerial
vehicles will revolutionize spatial ecology,
Frontiers in Ecology
and the Environment
, 11(3):138–146.
Antena3 TV, 2015. Aviones no tripulados, la próxima revolución
aeronáutica (Drones aircraft, the next revolution), URL:
http://
-
proxima-revolucion-aeronautica_2012072900111.html
, URL:
(last date
accessed: 20 February 2015).
Antonio, P., F. Grimaccia, and M. Mussetta, 2012. Architecture and
methods for innovative heterogeneous wireless sensor network
applications,
Remote Sens
ing, 4:1146–1161.
Ariff, M.F.M., A.K. Chong, Z. Majid, and H., Setan, 2013. Geometric
and radiometric characteristics of a prototype surveillance sys-
tem,
Measurement
, 46:610–620.
Arnold, T., M. Biasio, A. Fritz, A. Frank, and R. Leitner, 2012. UAV-
based multi-spectral environmental monitoring,
Proceedings
of the SPIE 8360, Airborne Intelligence, Surveillance,
Reconnaissance (ISR) Systems and Applications
, IX, 836005.
Arnold, T., M. De Biasio, A. Fritz, and R. Leitner, 2013. UAV-based
measurement of vegetation indices for environmental moni-
toring,
Proceedings of the 2013 International Conference on
Sensing Technology
(ICST), 03-05 December, Wellington, New
Zealand, pp. 704–707.
Atzberger, C., 2013. Advances in remote sensing of agriculture:
Context description, existing operational monitoring systems
and major information needs,
Remote Sens
ing, 5:949-981.
AUVSI, 2015. Association for Unmanned Vehicle Systems
International, URL:
/
(last date
accessed: 20 February 2015).
Aylor, D.E., D.G. Schmale III, E.J. Shields, M. Newcomb, and C.J.
Nappo, 2011. Tracking the potato late blight pathogen in the
atmosphere using unmanned aerial vehicles and Lagrangian
modeling,
Agricultural and Forest Meteorology
, 151:251-260.
Baer, D.S., J.B. Paul, M. Gupta, and A. O’Keefe, 2002. Sensitive
absorption measurements in the near-infrared region using
off-axis integrated-cavity-output spectroscopy,
Applied Physics
,
B75:261–265.
Baiocchi, V., D. Dominici, and M. Mormile, 2013. UAV applica-
tion in post-seismic environemnt,
International Archives of
the Photogrammetry, Remote Sensing and Spatial Information
Sciences
, XL-1/W2:21–25.
Bala, M., 2014. UAVs suggested to prevent elephant deaths by trains,
22 January, 2014, URL:
-
gested-prevent-elephant-deaths-trains/
(last date accessed: 20
February 2015).
Baluja, J., M.P. Diago, P. Balda, R. Zorer, M. Meggio, F. Morales, and J.
Tardaguila, 2012. Assessment of vineyard water status variability
by thermal and multispectral imagery using an unmanned aerial
vehicle (UAV).
Irrigation Sci
ence, 30:511–522.
Barasona, J.A., M. Mulero-Pázmány, P. Acevedo, J.J. Negro, M.J.
Torres, C. Gortázar, and J. Vicente, 2014. Unmanned aircraft
systems for studying spatial abundance of ungulates: Relevance
to spatial epidemiology,
Plos ONE
, 9(12):e115608.
Barreiro, A., J.M. Domínguez, A.J.C. Crespo, H. González-Jorge, D.
Roca, and M. Gómez-Gesteira, 2014. Integration of UAV photo-
grammetry and SPH modelling of fluids to study runoff on real
terrains,
Plos ONE
, 9(11):e111031.
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