Hodgson, A., 2015. Unmanned aerial vehicles for marine mammal
surveys, Cetacean Research Unit, URL:
-
search/research-projects/unmanned-aerial-vehicles-for-marine-
mammal-aerial-surveys/
(last date accessed: 20 February 2015).
Holz, D., M. Nieuwenhuisen, D. Droeschel, M. Schreiber, and S.
Behnke, 2013. Towards multimodal omnidirectional obstacle
detection for autonomous unmanned aerial vehicles,
ISPRS
International Archives of the Photogrammetry, Remote Sensing
and Spatial Information Sciences
, XL-1/W2, pp. 201–206.
Hong, L., Y. Ruan, W. Li, D. Wicker, and J. Layne, 2008. Energy-based
video tracking using joint target density processing with an ap-
plication to unmanned aerial vehicle surveillance,
IET Computer
Vision
, 2(1):1–12.
Honkavaara, E., J. Kaivosoja, J. Mäkynen, I. Pellikka, L. Pesonen,
H. Saari, H. Salo, T. Hakala, L. Markelin, and T. Rosnell, 2012.
Hyperspectral reflectance signatures and point clouds for preci-
sion agriculture by light weight UAV imaging system,
ISPRS
International Archives of the Photogrammetry, Remote Sensing
and Spatial Information Sciences
, I-7:353–358.
Honkavara, E., T. Hakala, H. Saari, L. Markelin, J. Mäkynen, T.
Rosnell, 2012. A process for radiometric correction of UAV im-
age blocks,
Photogrammetrie Fernerkundung Geoinformation
,
doi: 10.1127/1432-8364/2012/0106.
Honkavaara, E., H. Saari, J. Kaivosoja, I. Pölönen, T. Hakala, P. Litkey,
J. Mäkynen, and L. Pesonen, 2013. Processing and assessment of
spectrometric, stereoscopic imagery collected using a light-
weight UAV spectral camera for precision agriculture.
Remote
Sensing
, 5:5006-5039.
Hruska, R., J. Mitchell, M. Anderson, and N.F. Glenn, 2012.
Radiometric and geometric analysis of hyperspectral imagery
acquired from an unmanned aerial vehicle,
Remote Sensing
,
4:2736–2752.
Huang, Y., W.C. Hoffmann, Y. Lan, W. Wu, B.K. Fritz, 2009.
Development of a spray system for an unmanned aerial vehicle
platform,
Applied Engineering in Agriculture
, 25(6):803–809.
Huang, Y., S.J. Thomson, W.C. Hoffmann, Y. Lan, and B.K. Fritz, 2013.
Development and prospect of unmanned aerial vehicle tech-
nologies for agricultural production management.
International
Journal of Agricultural Biology and Engineering
, 6(3):1–10.
Huang, Y., S.Z. Yi, S. Li, S. Shao, and X. Qin, 2011. Design of
highway landslide warning and emergency response systems
based on UAV,
Proceedings of SPIE 8203, Remote Sensing of the
Environment
, 17
th
China Conference on Remote Sensing, 820317,
15 August 2011.
Hugenholtz, C.H., K. Whitehead, T.E. Barchyn, O.W. Brown, B.J.
Moorman, A. LeClair, T. Hamilton, and K. Riddell, 2013.
Geomorphological mapping with a small unmanned aircraft sys-
tem (sUAS): Feature detection and accuracy assessment of a pho-
togrammetrically-derived digital terrain model,
Geomorphology
,
194:16–24.
Humle, T., R. Duffy, D.L. Roberts, C. Sandbrook, F.A. V St. John, and
R.J. Smith, 2014. Biology’s drones: Undermined by fear,
Science
,
344(6190):1351.
Hung, C., Z. Xu, and S. Sukkarieh, 2014. Feature learning based
approach for weed classification using high resolution aerial im-
ages from a digital camera mounted on a UAV,
Remote Sen
sing,
6:12037–12054.
Hunt, E.R., W.D. Hively, S.J. Fujikawa, D.S. Linden, C.S. Daughtry,
and G.W. McCarty, 2010. Acquisition of NIR-green-blue digi-
tal photographs from unmanned aircraft for crop monitoring,
Remote Sensing
, 2:290–305.
Hunt, E.R., W.D. Hively, G.W. McCarty, D.S.T. Daughtry, P.J. Forrestal,
R.J. Kratochvil, J.L. Carr, N.F. Allen, J.R. Fox-Rabinovitz, and
C.D. Miller, 2011. NIR-green-blue high-resolution digital images
for assessment of winter cover crop biomass,
GIScience Remote
Sensing
, 48(1):86–98.
Hunt, E., D. Horneck, P. Hamm, D. Gadler, A. Bruce, R. Turner, C.
Spinelli, and J. Brungardt, 2014. Detection of nitrogen deficiency
in potatoes using small unmanned aircraft systems,
Proceedings
of the 12
th
International Conference on Precision Agriculture
2014
, 20-23 July 2014, Sacramento, California.
INTA, 2015. National Institute for Aerospace Technology “Esteban
Terradas,” URL:
.
aspx?Id=1&SubId=3
(last date accessed: 20 February 2015).
Immerzeel, W.W., P.D.A. Kraaijenbrink, J.M. Shea, A.B. Shrestha,
F. Pellicciotti, M.F.P. Bierkens, and S.M. de Jong, 2014. High-
resolution monitoring of Himalayan glacier dynamics using
unmanned aerial vehicles,
Remote Sensing of Environment
,
150:93–103.
Inoue, T., S. Nagai, S. Yamashita, H. Fadaei, R. Ishii, K. Okabe, H.
Taki, Y. Honda, K. Kajiwara, and R. Suzuki, 2014 Unmanned
aerial survey of fallen trees in a deciduous broadleaved forest in
eastern Japan,
PLos ONE
, 9(10):e109881.
Ishihama, F., Y. Watabe, and H. Oguma, 2012. Validation of a high-res-
olution, remotely operated aerial remote-sensing system for the
identification of herbaceous plant species,
Applied Vegetation
Science
, 15(3):383–389.
ISCAR-UCM Group, 2015.
(last date accessed: 20 February 2015).
Israel, M., 2011. A UAV-based roe deer fawn detection system,
Conference on Unmanned Aerial Vehicle in Geomatics,
ISPRS
International Archives of the Photogrammetry, Remote Sensing
and Spatial Information Sciences
, 14-16, September 2011,
Zurich, Switzerland, XXXVIII-1/C22, pp. 11-55, UAV-g 2011.
James, G., 2012. Spatial intelligence UAV: A new revolution in remote
sensing, 2012,
URL:
/
uav-new-revolution-in-remote-sensing.html
(last date accessed:
20 February 2015).
Jannoura, R., K. Brinkmann, D. Uteau, C. Bruns, and R.G. Joergensen,
2015. Monitoring of crop biomass using true colour aerial pho-
tographs taken from a remote controlled hexacopter,
Biosystems
Engineering
, 129:341–351.
Jensen, T., A. Apan, F. Young, and L. Zeller, 2007. Detecting the at-
tributes of a wheat crop using digital imagery acquired from a
low-altitude platform, computers and electronics in agriculture,
59 (1-2):66–77.
Jensen, A.M., M. Baumann, and Y. Chen, 2008. Low-cost multispec-
tral aerial imaging using autonomous runway-free small flying
wing vehicles,
Proceedings of the IEEE International Geoscience
and Remote Sensing Symposium (IGARSS)
, 07-11 July 2008,
Boston, Massachusetts, Vol. 5, pp. 506–509, URL:
tialintel.blogspot.com.es/2012/09/uav-new-revolution-in-remote-
sensing.html
(last date accessed: 20 February 2015).
Jensen, A.M., Y. Chen, M. McKee, T. Hardy, and S.L. Barfuss, 2009.
AggieAir - A low-cost autonomous multispectral remote sensing
platform: New developments and applications,
Proceedings of
the 2009 IEEE International Geoscience and Remote Sensing
Symposium
, 12-17 July 2009, Cape Town, South Africa, pp.
995–998.
Jensen, A.M., T. Hardy, M. McKee, and Y.Q. Chen, 2011. Using a mul-
tispectral autonomous unmanned aerial remote sensing platform
(AggieAir) for riparian and wetland applications,
Proceedings
of the IEEE International Geoscience and Remote Sensing
Symposium (IGARSS)
, 24-29 July 2011, Vancouver, Canada, pp.
3413–3416.
Jensen, R.R., A.J. Hardin, P.J. Hardin, and J.R. Jensen, 2011. A new
method to correct pushbroom hyperspectral data using linear
features and ground control points,
GIScience and Remote
Sens
ing, 48(3):416–431.
Jensen, A.M., D. Morgan, Y. Chen, S. Clemens, and T. Hardy, 2009.
Using multiple open source low-cost unmanned aerial vehicles
(UAV) for 3D photogrammetry and distributed wind mea-
surement,
Proceedings of the ASME/IEEE 2009 International
Conference on Mechatronic and Embedded Systems and
Applications, 20
th
Reliability, Stress Analysis, and Failure
Prevention Conference
, Vol. 3, pp. 629–634.
Jensen, A.M., B.T. Neilson, M. McKee, and Y. Chen, 2012. Thermal
remote sensing with an autonomous unmanned aerial remote
sensing platform for surface stream temperatures,
Proceedings of
the IEEE International Geoscience Remote Sensing Symposium
(
IGARSS
), Munich, Germany, pp. 5049–5052.
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