Relevant bibliographies by topics / Orbital and aerial sensors

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Orbital and aerial sensors'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Orbital and aerial sensors"

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Pereira, Luciana Escalante, Giancarlo Lastoria, Bruna Semler de Almeida, et al. "APPLICATION OF AERIAL AND ORBITAL SENSOR PHOTOGRAPHS TO IDENTIFY AND DELINEATE WATER BODIES." Boletim de Ciências Geodésicas 23, no. 4 (2017): 591–605. http://dx.doi.org/10.1590/s1982-21702017000400039.

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Abstract: The application of orbital sensors to identify and delineate water bodies was evaluated in this study. Reference aerial photos were used to measure the surface area of three water bodies in São Gabriel do Oeste, MS, Brazil and assess seven sensors commonly used in environmental studies: ALOS-AVNIR, CBERS 2B-CCD, CBERS 2B-HRC, IRS P6-LISS3, LANDSAT-TM, LANDSAT-ETM+, and LANDSAT-OLI. The images were analyzed with the near infrared (NIR) band, and digital processing techniques including image fusion (spatial enhancement), false-color composition, and pre-processed radiometric correction
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Santana, L. S., G. A. e. S. Ferraz, L. M. Santos, et al. "VEGETATIVE VIGOR OF MAIZE CROP OBTAINED THROUGH VEGETATION INDEXES IN ORBITAL AND AERIAL SENSORS IMAGES." Revista Brasileira de Engenharia de Biossistemas 13, no. 3 (2019): 195. http://dx.doi.org/10.18011/bioeng2019v13n3p195-206.

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Olivetti, Diogo, Henrique Roig, Jean-Michel Martinez, et al. "Low-Cost Unmanned Aerial Multispectral Imagery for Siltation Monitoring in Reservoirs." Remote Sensing 12, no. 11 (2020): 1855. http://dx.doi.org/10.3390/rs12111855.

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The recent and continuous development of unmanned aerial vehicles (UAV) and small cameras with different spectral resolutions and imaging systems promotes new remote sensing platforms that can supply ultra-high spatial and temporal resolution, filling the gap between ground-based surveys and orbital sensors. This work aimed to monitor siltation in two large rural and urban reservoirs by recording water color variations within a savanna biome in the central region of Brazil using a low cost and very light unmanned platform. Airborne surveys were conducted using a Parrot Sequoia camera (~0.15 kg
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Borlaf-Mena, Ignacio, Maurizio Santoro, Ludovic Villard, Ovidiu Badea, and Mihai Andrei Tanase. "Investigating the Impact of Digital Elevation Models on Sentinel-1 Backscatter and Coherence Observations." Remote Sensing 12, no. 18 (2020): 3016. http://dx.doi.org/10.3390/rs12183016.

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Spaceborne remote sensing can track ecosystems changes thanks to continuous and systematic coverage at short revisit intervals. Active remote sensing from synthetic aperture radar (SAR) sensors allows day and night imaging as they are not affected by cloud cover and solar illumination and can capture unique information about its targets. However, SAR observations are affected by the coupled effect of viewing geometry and terrain topography. The study aims to assess the impact of global digital elevation models (DEMs) on the normalization of Sentinel-1 backscattered intensity and interferometri
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Maciel, Francine De Oliveira, Clódis De Oliveira Andrades-Filho, Pâmela Boelter Herrmann, Mateus Da Silva Reis, Erli Schneider Costa, and Rodrigo Cambará Printes. "Ambientes de ocorrência do porífero Oncosclera jewelli no Parque Estadual Do Tainhas, Planalto Meridional do RS: uma análise geomorfométrica." Ciência e Natura 43 (March 8, 2021): e41. http://dx.doi.org/10.5902/2179460x40403.

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Tainhas State Park embraces locations of occurrence of freshwater sponge Oncosclera jewelli. Our objective is to indicate the areas of potential occurrence of the species from factors related to the geomorphometric signature of the occurance points along the Tainhas River in the Park and its buffer zone. Connections and data analysis were performed from the construction and manipulation of a geographic database, in SIGs SPRING-5.4.3 and QGIS-2.18, containing: a) MDEs from Topodata, Embrapa and Alos bases, obtained by remote orbitals sensors for the entire study area, and MDE obtained by drone-
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Vargas, Juan Quirós, Juliane Bendig, Alasdair Mac Arthur, et al. "Unmanned Aerial Systems (UAS)-Based Methods for Solar Induced Chlorophyll Fluorescence (SIF) Retrieval with Non-Imaging Spectrometers: State of the Art." Remote Sensing 12, no. 10 (2020): 1624. http://dx.doi.org/10.3390/rs12101624.

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Chlorophyll fluorescence (ChlF) information offers a deep insight into the plant physiological status by reason of the close relationship it has with the photosynthetic activity. The unmanned aerial systems (UAS)-based assessment of solar induced ChlF (SIF) using non-imaging spectrometers and radiance-based retrieval methods, has the potential to provide spatio-temporal photosynthetic performance information at field scale. The objective of this manuscript is to report the main advances in the development of UAS-based methods for SIF retrieval with non-imaging spectrometers through the latest
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Nam, Seung Yeob, and Gyanendra Prasad Joshi. "Unmanned aerial vehicle localization using distributed sensors." International Journal of Distributed Sensor Networks 13, no. 9 (2017): 155014771773292. http://dx.doi.org/10.1177/1550147717732920.

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Gruber, Michael, Bernhard Schachinger, Marc Muick, Christian Neuner, and Helfried Tschemmernegg. "GEOMETRIC CALIBRATION AND VALIDATION OF ULTRACAM AERIAL SENSORS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W4 (March 17, 2016): 51–53. http://dx.doi.org/10.5194/isprsarchives-xl-3-w4-51-2016.

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We present details of the calibration and validation procedure of UltraCam Aerial Camera systems. Results from the laboratory calibration and from validation flights are presented for both, the large format nadir cameras and the oblique cameras as well. Thus in this contribution we show results from the UltraCam Eagle and the UltraCam Falcon, both nadir mapping cameras, and the UltraCam Osprey, our oblique camera system. This sensor offers a mapping grade nadir component together with the four oblique camera heads. The geometric processing after the flight mission is being covered by the Ultra
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Gruber, Michael, Bernhard Schachinger, Marc Muick, Christian Neuner, and Helfried Tschemmernegg. "GEOMETRIC CALIBRATION AND VALIDATION OF ULTRACAM AERIAL SENSORS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W4 (March 17, 2016): 51–53. http://dx.doi.org/10.5194/isprs-archives-xl-3-w4-51-2016.

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We present details of the calibration and validation procedure of UltraCam Aerial Camera systems. Results from the laboratory calibration and from validation flights are presented for both, the large format nadir cameras and the oblique cameras as well. Thus in this contribution we show results from the UltraCam Eagle and the UltraCam Falcon, both nadir mapping cameras, and the UltraCam Osprey, our oblique camera system. This sensor offers a mapping grade nadir component together with the four oblique camera heads. The geometric processing after the flight mission is being covered by the Ultra
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Qin, Yuan, David Boyle, and Eric Yeatman. "Efficient and Reliable Aerial Communication With Wireless Sensors." IEEE Internet of Things Journal 6, no. 5 (2019): 9000–9011. http://dx.doi.org/10.1109/jiot.2019.2926249.

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Dissertations / Theses on the topic "Orbital and aerial sensors"

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Justo, Ana Paula. "Sistemas orbitais e a?reos aplicados ? an?lise multi-escala da tect?nica r?ptil atuante na borda sudeste da Bacia do Parna?ba." Universidade Federal do Rio Grande do Norte, 2006. http://repositorio.ufrn.br:8080/jspui/handle/123456789/18838.

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Made available in DSpace on 2015-03-13T17:08:39Z (GMT). No. of bitstreams: 1 AnaPJ_ate_cap4.pdf: 5254385 bytes, checksum: 3ac040e5f9ad13d1d9fc82f32f2f0abf (MD5) Previous issue date: 2006-08-25<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>The tectonics activity on the southern border of Parna?ba Basin resulted in a wide range of brittle structures that affect siliciclastic sedimentary rocks. This tectonic activity and related faults, joints, and folds are poorly known. The main aims of this study were (1) to identify lineaments using several remotesensing systems, (2)
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Trowbridge, Michael Aaron. "Autonomous 3D Model Generation of Orbital Debris using Point Cloud Sensors." Thesis, University of Colorado at Boulder, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1558774.

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<p> A software prototype for autonomous 3D scanning of uncooperatively rotating orbital debris using a point cloud sensor is designed and tested. The software successfully generated 3D models under conditions that simulate some on-orbit orbit challenges including relative motion between observer and target, inconsistent target visibility and a target with more than one plane of symmetry. The model scanning software performed well against an irregular object with one plane of symmetry but was weak against objects with 2 planes of symmetry. </p><p> The suitability of point cloud sensors and al
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Mathisen, Siri Holthe. "High Precision Deployment of Wireless Sensors from Unmanned Aerial Vehicles." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for teknisk kybernetikk, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-25541.

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AMOS - Centre for Autonomous Marine Operations and Systems - is a research center at the Norwegian University of Science and Technology. One out of the 9 projects in AMOS researches how basic unmanned aerial vehicle (UAV) operations can be performed, and one of these operations is high precision deployment of a payload from a UAV. UAVs are normally used for tasks that are either too dangerous, too inaccessible or too repetitive for humans. These tasks may include sensors to be placed somewhere inaccessible or first aid equipment to be delivered to disaster areas.This Master Thesis describes th
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Cannon, Brandon Jeffrey. "Fault Detection for Unmanned Aerial Vehicles with Non-Redundant Sensors." BYU ScholarsArchive, 2014. https://scholarsarchive.byu.edu/etd/5308.

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To operate, autonomous systems of necessity employ a variety of sensors to perceive their environment. Many small unmanned aerial vehicles (UAV) are unable to carry redundant sensors due to size, weight, and power (SWaP) constraints. Faults in these sensors can cause undesired behavior, including system instability. Thus, detection of faults in these non-redundant sensors is of paramount importance.The problem of detecting sensor faults in non-redundant sensors on board autonomous aircraft is non-trivial. Factors that make development of a solution difficult include both an inability to per
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Sharkasi, Adam Tawfik. "Stereo Vision Based Aerial Mapping Using GPS and Inertial Sensors." Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/32263.

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The robotics field has grown in recent years to a point where unmanned systems are no longer limited by their capabilities. As such, the mission profiles for unmanned systems are becoming more and more complicated, and a demand has risen for the deployment of unmanned systems into the most complex of environments. Additionally, the objectives for unmanned systems are once more complicated by the necessity for beyond line of sight teleoperation, and in some cases complete vehicle autonomy. Such systems require adequate sensory devices for appropriate situational awareness. Additionally, a larg
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Sjanic, Zoran. "Navigation and Mapping for Aerial Vehicles Based on Inertial and Imaging Sensors." Doctoral thesis, Linköpings universitet, Tekniska högskolan, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97317.

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Small and medium sized Unmanned Aerial Vehicles (UAV) are today used in military missions, and will in the future find many new application areas such as surveillance for exploration and security. To enable all these foreseen applications, the UAV's have to be cheap and of low weight, which restrict the sensors that can be used for navigation and surveillance. This thesis investigates several aspects of how fusion of navigation and imaging sensors can improve both tasks at a level that would require much more expensive sensors with the traditional approach of separating the navigation system f
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Strömberg, Erik. "Smoothing and Mapping of an Unmanned Aerial Vehicle Using Ultra-wideband Sensors." Thesis, KTH, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215636.

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Unmanned Aerial Vehicles (UAV), in particular the four-rotor quadrotor, aregaining wide popularity in research as well as in commercial and hobbyist applications.Maneuvrability, low cost, and small size make quadrotors an attractiveoption to full-scale, manned helicopters while opening up new possibilities.These include applications where full-scale helicopters are unsuitable, such ascooperative tasks or operating indoors.Many UAV systems use the Global Positioning System (GPS), IMU (InertialMeasurement Unit) sensors, and camera sensors to observe the UAV’sstate. Depending on the application,
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Trittler, Martin [Verfasser]. "Automatic Landing for Fixed-Wing Unmanned Aerial Vehicles with Optical Sensors / Martin Trittler." Aachen : Shaker, 2018. http://d-nb.info/1162794321/34.

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Rapp, Carl. "Unmanned Aerial Vehicle Positioning Using a Phased Array Radio and GNSS Independent Sensors." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157414.

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This thesis studies the possibility to replace the global navigation satellite system (GNSS) with a phased array radio system (PARS) for positioning and navigation of an unmanned aerial vehicle (UAV). With the increase of UAVs in both civilian and military applications, the need for a robust and accurate navigation solution has increased. The GNSS is the main solution of today for UAV navigation and positioning. However, the GNSS can be disturbed by malicious sources, the signal can either be blocked by jamming or modified to give the wrong position by spoofing. Studies have been conducted to
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De, Villiers Hendrik Barney. "Correlation and tracking using multiple radar sensors /." Link to the online version, 2006. http://hdl.handle.net/10019/1006.

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Books on the topic "Orbital and aerial sensors"

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George C. Marshall Space Flight Center., ed. Project ORION: Orbital debris removal using ground-based sensors and lasers. National Aeronautics and Space Administration, George C. Marshall Space Flight Center, 1996.

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Thermal and orbital analysis of earth monitoring sun-synchronous space experiments. National Aeronautics and Space Administration, Langley Research Center, 1990.

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Klimburg-Witjes, Nina, Nikolaus Poechhacker, and Geoffrey C. Bowker, eds. Sensing In/Security: Sensors as Transnational Security Infrastructures. Mattering Press, 2021. http://dx.doi.org/10.28938/9781912729111.

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Sensing In/Security investigates how sensors and sensing practices enact regimes of security and insecurity. It extends long-standing concerns with infrastructuring to emergent modes of surveillance and control by exploring how digitally networked sensors shape securitisation practices. Contributions in this volume examine how sensing devices gain political and epistemic relevance in various forms of in/security, from border control, regulation, and epidemiological tracking, to aerial surveillance and hacking. Instead of focusing on specific sensory devices and their consequences, this volume
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Book chapters on the topic "Orbital and aerial sensors"

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Shimabukuro, Yosio Edemir, and Flávio Jorge Ponzoni. "Orbital Sensors." In Springer Remote Sensing/Photogrammetry. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02017-0_3.

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Orsag, Matko, Christopher Korpela, Paul Oh, and Stjepan Bogdan. "Sensors and Control." In Aerial Manipulation. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61022-1_6.

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Mejias, Luis, John Lai, and Troy Bruggemann. "Sensors for Missions." In Handbook of Unmanned Aerial Vehicles. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-90-481-9707-1_6.

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Valavanis, Kimon P., and George J. Vachtsevanos. "Sensors and Sensing Strategies: Introduction." In Handbook of Unmanned Aerial Vehicles. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-90-481-9707-1_135.

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Liu, Yun-ping, Xian-ying Li, Tian-miao Wang, Yong-hong Zhang, and Ping Mei. "The Stability Analysis of Quadrotor Unmanned Aerial Vechicles." In Wearable Sensors and Robots. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2404-7_30.

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Bryson, Mitch, and Salah Sukkarieh. "UAV Localization Using Inertial Sensors and Satellite Positioning Systems." In Handbook of Unmanned Aerial Vehicles. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-90-481-9707-1_3.

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Aranda, Miguel, Gonzalo López-Nicolás, and Carlos Sagüés. "Control of Mobile Robot Formations Using Aerial Cameras." In Control of Multiple Robots Using Vision Sensors. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57828-6_5.

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Ambrosia, Vincent G., and Thomas Zajkowski. "Selection of Appropriate Class UAS/Sensors to Support Fire Monitoring: Experiences in the United States." In Handbook of Unmanned Aerial Vehicles. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-90-481-9707-1_73.

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Krishna, K. R. "Sensors and Image Processing Computer Software Relevant to Unmanned Aerial Vehicle-Based Technology in Agriculture." In Unmanned Aerial Vehicle Systems in Crop Production. Apple Academic Press, 2019. http://dx.doi.org/10.1201/9780429425264-5.

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Kressel, I., A. Handelman, Y. Botsev, et al. "Health and Usage Monitoring of Unmanned Aerial Vehicles Using Fiber-Optic Sensors." In ICAF 2011 Structural Integrity: Influence of Efficiency and Green Imperatives. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1664-3_37.

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Conference papers on the topic "Orbital and aerial sensors"

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Reid, Donald B. "Orbital gyrocompass evolution." In 2016 DGON Intertial Sensors and Systems (ISS). IEEE, 2016. http://dx.doi.org/10.1109/inertialsensors.2016.7745672.

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Ippolito, Corey, and Ara Nefian. "Object classification from aerial visual imagery." In 2010 Ninth IEEE Sensors Conference (SENSORS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icsens.2010.5689985.

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Starodubov, Dmitry S., Kyle McCormick, Michael Dellosa, Leo Volfson, and Emery Erdelyi. "Facility for orbital material processing." In Sensors and Systems for Space Applications XI, edited by Khanh D. Pham and Genshe Chen. SPIE, 2018. http://dx.doi.org/10.1117/12.2305830.

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Weng, Yi, and Zhongqi Pan. "Orbital-Angular-Momentum-based Image Sensor using High Resolution Photoacoustic Tomography." In Optical Sensors. OSA, 2015. http://dx.doi.org/10.1364/sensors.2015.ses1b.3.

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Bhatia, Laksh, David Boyle, and Julie A. McCann. "Aerial Interactions with Wireless Sensors." In SenSys '18: The 16th ACM Conference on Embedded Networked Sensor Systems. ACM, 2018. http://dx.doi.org/10.1145/3274783.3275189.

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Niederriter, R. D., M. E. Siemens, and J. T. Gopinath. "Fiber Optic Sensors Based on Orbital Angular Momentum." In CLEO: Science and Innovations. OSA, 2015. http://dx.doi.org/10.1364/cleo_si.2015.sm1l.5.

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Navnit, Abhinav, Deeksha Devendra, Anushka Tiwari, and Aftab M. Hussain. "KiteCam – a novel approach to low-cost aerial surveillance." In 2020 IEEE SENSORS. IEEE, 2020. http://dx.doi.org/10.1109/sensors47125.2020.9278918.

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Nag, Sreeja, Jaewoo Jung, and Karishma Inamdar. "Communicating with unmanned aerial swarm automatic dependent surveillance transponders." In 2017 IEEE SENSORS. IEEE, 2017. http://dx.doi.org/10.1109/icsens.2017.8234227.

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Minwalla, Cyras, Mussie Tekeste, Kyle Watters, et al. "Modeling a prototype optical collision avoidance sensor for unmanned aerial vehicles." In 2010 Ninth IEEE Sensors Conference (SENSORS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icsens.2010.5690422.

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Daniel, Kai, Sebastian Rohde, Niklas Goddemeier, and Christian Wietfeld. "RF-based connectivity management of aerial sensor networks for 3D coverage optimization." In 2010 Ninth IEEE Sensors Conference (SENSORS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icsens.2010.5690284.

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Reports on the topic "Orbital and aerial sensors"

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Shima, Tal, Pantelis Isaiah, and Yoav Gottlieb. Motion Planning and Task Assignment for Unmanned Aerial Vehicles Cooperating with Unattended Ground Sensors. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada619854.

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Barrowes, Benjamin, Dan Glaser, Brian Quinn, Mikheil Prishvin, and Fridon Shubitidze. Unmanned aerial systems electromagnetic induction sensor development : evaluation of commercial-off-the-shelf unmanned aerial system motor interference and mitigation in airborne electromagnetic induction sensors. Engineer Research and Development Center (U.S.), 2019. http://dx.doi.org/10.21079/11681/34104.

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Berney, Ernest, Andrew Ward, and Naveen Ganesh. First generation automated assessment of airfield damage using LiDAR point clouds. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40042.

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This research developed an automated software technique for identifying type, size, and location of man-made airfield damage including craters, spalls, and camouflets from a digitized three-dimensional point cloud of the airfield surface. Point clouds were initially generated from Light Detection and Ranging (LiDAR) sensors mounted on elevated lifts to simulate aerial data collection and, later, an actual unmanned aerial system. LiDAR data provided a high-resolution, globally positioned, and dimensionally scaled point cloud exported in a LAS file format that was automatically retrieved and pro
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Berney, Ernest, Naveen Ganesh, Andrew Ward, J. Newman, and John Rushing. Methodology for remote assessment of pavement distresses from point cloud analysis. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40401.

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The ability to remotely assess road and airfield pavement condition is critical to dynamic basing, contingency deployment, convoy entry and sustainment, and post-attack reconnaissance. Current Army processes to evaluate surface condition are time-consuming and require Soldier presence. Recent developments in the area of photogrammetry and light detection and ranging (LiDAR) enable rapid generation of three-dimensional point cloud models of the pavement surface. Point clouds were generated from data collected on a series of asphalt, concrete, and unsurfaced pavements using ground- and aerial-ba
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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-c
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