Relevant bibliographies by topics / Aerial photography in oceanography

Contents

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

Academic literature on the topic 'Aerial photography in oceanography'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Aerial photography in oceanography"

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Taylor, Jessica K. D., Robert D. Kenney, Donald J. LeRoi, and Scott D. Kraus. "Automated Vertical Photography for Detecting Pelagic Species in Multitaxon Aerial Surveys." Marine Technology Society Journal 48, no. 1 (January 1, 2014): 36–48. http://dx.doi.org/10.4031/mtsj.48.1.9.

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AbstractMarine aerial surveys are designed to maximize the potential for detecting target species. Collecting data on different taxa from the same platform is economically advantageous but normally comes at the cost of compromising optimal taxon-specific scanning patterns and survey parameters, in particular altitude. Here, we describe simultaneous visual and photographic sampling methods as a proof of concept for detecting large whales and turtles from a single aircraft, despite very different sighting cues. Data were collected for fishing gear, fish, sharks, turtles, seals, dolphins, and whales using two observers and automated vertical photography. The photographic method documented an area directly beneath the aircraft that would otherwise have been obscured from observers. Preliminary density estimates were calculated for five species for which there were sufficient sample sizes from both methods after an initial year of data collection. The photographic method yielded significantly higher mean density estimates for loggerhead turtles, ocean sunfish, and blue sharks (p < 0.01), despite sampling a substantially smaller area than visual scanning (less than 11%). Density estimates from these two methods were not significantly different for leatherback turtles or basking sharks (p > 0.05), two of the largest species included in the analysis, which are relatively easy to detect by both methods. Although postflight manual processing of photographic data was extensive, this sampling method comes at no additional in-flight effort and obtains high-quality digital documentation of sightings on the trackline. Future directions for this project include automating photographic sighting detections, expanding the area covered by photography, and performing morphometric measurement assessments.
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Ekin, Bill. "The Use of GPS for Low-Cost Aerial Block Photography." Journal of Navigation 48, no. 2 (May 1995): 239–48. http://dx.doi.org/10.1017/s0373463300012704.

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Flight trials using an inexpensive Garmin GPS receiver, Century 1 autopilot and a Cessna F172H aircraft to acquire block aerial photography are described. The performance of the whole system in the maintenance of constant sidelap and forward lap in block aerial vertical photography was good. However, the system was not good enough to manoeuvre the aircraft accurately on curved flight paths.
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Magome, Shinya, Tomohiro Yamashita, Takeshi Kohama, Atsushi Kaneda, Yuichi Hayami, Satoru Takahashi, and Hidetaka Takeoka. "Jellyfish patch formation investigated by aerial photography and drifter experiment." Journal of Oceanography 63, no. 5 (October 2007): 761–73. http://dx.doi.org/10.1007/s10872-007-0065-y.

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Curr, R. H. F., A. Koh, E. Edwards, A. T. Williams, and P. Davies. "Assessing anthropogenic impact on Mediterranean sand dunes from aerial digital photography." Journal of Coastal Conservation 6, no. 1 (December 2000): 15–22. http://dx.doi.org/10.1007/bf02730463.

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Estep, K. "Seal sizes and habitat conditions assessed from aerial photography and video analysis." ICES Journal of Marine Science 51, no. 3 (August 1994): 253–61. http://dx.doi.org/10.1006/jmsc.1994.1026.

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Nakashima, Etsuko, Atsuhiko Isobe, Shinya Magome, Shin’ichiro Kako, and Noriko Deki. "Using aerial photography and in situ measurements to estimate the quantity of macro-litter on beaches." Marine Pollution Bulletin 62, no. 4 (April 2011): 762–69. http://dx.doi.org/10.1016/j.marpolbul.2011.01.006.

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Shanmugam, S., and M. Barnsley. "Quantifying landscape-ecological succession in a coastal dune system using sequential aerial photography and GIS." Journal of Coastal Conservation 8, no. 1 (2002): 61. http://dx.doi.org/10.1652/1400-0350(2002)008[0061:qlsiac]2.0.co;2.

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Shanmugam, S., and M. Barnsley. "Quantifying landscape-ecological succession in a coastal dune system using sequential aerial photography and GIS." Journal of Coastal Conservation 8, no. 1 (March 2002): 61–68. http://dx.doi.org/10.1007/bf02806585.

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Uhrin, Amy V., and Philip A. Townsend. "Improved seagrass mapping using linear spectral unmixing of aerial photographs." Estuarine, Coastal and Shelf Science 171 (March 2016): 11–22. http://dx.doi.org/10.1016/j.ecss.2016.01.021.

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Dowdeswell, Julian A., and Toby J. Benham. "A surge of Perseibreen, Svalbard, examined using aerial photography and ASTER high resolution satellite imagery." Polar Research 22, no. 2 (December 2003): 373–83. http://dx.doi.org/10.1111/j.1751-8369.2003.tb00118.x.

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Dissertations / Theses on the topic "Aerial photography in oceanography"

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Wolf, Eric B. "Low-cost large scale aerial photography and the Upland South Folk Cemetery a thesis presented to the Department of Geology and Geography in candidacy for the degree of Master of Science /." Diss., Maryville, Mo. : Northwest Missouri State University, 2006. http://www.nwmissouri.edu/library/theses/WolfEricB/index.htm.

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Thesis (M.S.)--Northwest Missouri State University, 2006.
The full text of the thesis is included in the pdf file. Title from title screen of full text.pdf file (viewed on January 25, 2008) Includes bibliographical references.
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Richards, Daniel L. "Open source UAV platform development for aerial photography." Thesis, California State University, Long Beach, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1587919.

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Aerial photography is an important layer in Geographic Information Systems (GISs), and generally provides the base layer from which many other digital map layers are derived. Capturing these photos from a traditional full-sized airplane is a complex and expensive process. The recent development of Unmanned Aerial Vehicles (UAVs) and associated technology are providing an alternative to the traditional aerial mapping process. UAVs produced by popular commercial vendors are effective at capturing photos, but are highly expensive to acquire, and equally expensive to maintain.

This research project demonstrates the development and successful implementation of a relatively inexpensive ($2000) unmanned aerial vehicle capable of acquiring high-resolution digital aerial photography. The UAV was developed using open source technology and commercially available components. The methods outlined encompass the platform selection, component inventory, design, construction, configuration, implementation, and testing of the UAV, as well as an analysis of the photography produced by the process. This approach can be used by others to implement similar UAV projects.

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Simpson, Andrew David. "DEVELOPMENT OF AN UNMANNED AERIAL VEHICLE FOR LOW-COST REMOTE SENSING AND AERIAL PHOTOGRAPHY." UKnowledge, 2003. http://uknowledge.uky.edu/gradschool_theses/191.

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The paper describes major features of an unmanned aerial vehicle, designed undersafety and performance requirements for missions of aerial photography and remotesensing in precision agriculture. Unmanned aerial vehicles have vast potential asobservation and data gathering platforms for a wide variety of applications. The goalof the project was to develop a small, low cost, electrically powered, unmanned aerialvehicle designed in conjunction with a payload of imaging equipment to obtainremote sensing images of agricultural fields. The results indicate that this conceptwas feasible in obtaining high quality aerial images.
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Gurtner, Alex. "Investigation of fisheye lenses for small UAV aerial photography." Queensland University of Technology, 2008. http://eprints.qut.edu.au/19323/.

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Aerial photography obtained by UAVs (Unmanned Aerial Vehicles) is an emerging market for civil applications. Small UAVs are believed to close gaps in niche markets, such as acquiring airborne image data for remote sensing purposes. Small UAVs will be able to fly at low altitudes, in dangerous environments and over long periods of time. However, the small lightweight constructions of these UAVs lead to new problems, such as higher agility leading to more susceptibility to turbulence and limitations in space and payload for sensor systems. This research investigates the use of low-cost fisheye lenses to overcome such problems which theoretically makes the airborne imaging less sensitive to turbulence. The fisheye lens has the benet of a large observation area (large field of view) and doesn't add additional weight to the aircraft, like traditional mechanical stabilizing systems. This research presents the implementation of a fisheye lens for aerial photography and mapping purposes, including theoretical background of fisheye lenses. Based on the unique feature of the distortion being a function of the viewing angle, methods used to derive the fisheye lens distortion are presented. The lens distortion is used to rectify the fisheye images before these images can be used in aerial photography. A detailed investigation into the inner orientation of the camera and inertial sensor is given, as well as the registration of airborne collected images. It was found that the attitude estimation is critical towards accurate mapping using low quality sensors. A loosely coupled EKF filter applied to the GPS and inertial sensor data estimated the attitude to an accuracy of 3-5° (1-sigma) using low-cost sensors typically found in small UAVs. However, the use of image stitching techniques may improve the outcome. On the other hand, lens distortion caused by the fisheye lens can be addressed by rectification techniques and removed to a sub-pixel level. Results of the process present image sequences gathered from a piloted aircraft demonstrating the achieved performance and potential applications towards UAVs. Further, an unforeseen issue with a vibrating part in the lens lead to the need for vibration compensation. The vibration could be estimated to ±1 pixel in 75% of the cases by applying an extended Hough transform to the fisheye images.
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Buckley, Craig. "Photomosaicing and automatic topography generation from stereo aerial photography." Thesis, Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/790.

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Gifford, Eric Allan 1965. "Hough transform extraction of cartographic fiducial marks from aerial photography." Thesis, The University of Arizona, 1991. http://hdl.handle.net/10150/277903.

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Cartographic compilation requires precision mensuration. The calibration of mensuration processes is based on specific fiducials. External fiducials, around the exterior frame of the image, must be precisely measured to establish the overall physical geometry. Internal fiducials are provided within the image by placement of cloth panels on the ground at locations whose position is precisely known. Both types of fiducials must be known within the pixel space of a digitized image in order for the feature extraction process to be accurate with respect to delineated features. Precise mensuration of these fiducials requires that a cartographer view the image on a display and use pointing devices, such as a mouse, to pick the exact point. For accurate fiducial location, the required manual operations can be an added time-consuming task in the feature extraction process. Interactive tools which eliminate the precise pointing action for the operator are described in this thesis. The operator is required only to "box-in" the fiducial, using a simple drawing tool, select the fiducial function, and the software of the tool returns the precise location of the fiducial.
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Gombos, Andrew David. "DETECTION OF ROOF BOUNDARIES USING LIDAR DATA AND AERIAL PHOTOGRAPHY." UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_theses/75.

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The recent growth in inexpensive laser scanning sensors has created entire fields of research aimed at processing this data. One application is determining the polygonal boundaries of roofs, as seen from an overhead view. The resulting building outlines have many commercial as well as military applications. My work in this area has created a segmentation algorithm where the descriptive features are computationally and theoretically simpler than previous methods. A support vector machine is used to segment data points using these features, and their use is not common for roof detection to date. Despite the simplicity of the feature calculations, the accuracy of our algorithm is similar to previous work. I also describe a basic polygonal extraction method, which is acceptable for basic roofs.
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Fu, Youtong. "Use Of Small Format Aerial Photography in NPS Pollution Control Applications." Diss., Virginia Tech, 2002. http://hdl.handle.net/10919/26346.

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An automated procedure was developed to identify and extract confined poultry facilities from color 35-mm slide imagery collected by the United States Department of Agriculture/Farm Service Agency (USDA/FSA). The imagery is used by the USDA/FSA to monitor compliance with various farm support programs and to determine crop production acreage within a given county. The imagery is generally available for all counties within the state on an annual basis. The imagery, however, is not flown to rigid specifications as flight height, direction, and overlap can vary significantly. The USDA/FSA attempts to collect imagery with reasonably clear skies, as visual interpretations could be drastically impacted by cloudiness. The goal of this study was to develop procedures to effectively utilize this imagery base to identify and extract poultry facilities using automated techniques based on image processing and GIS. The procedure involved pre-screening the slides to determine coverage, geopositioning to USGS quadrangle base, color scanning to convert slide image to a digital format and archiving each data file with a naming convention that would allow rapid retrieval in later analysis. Image processing techniques were developed for identifying poultry facilities based on spectral characteristics. GIS tools were used to select poultry facilities from an array of features with similar spectral characteristics. A training data set was selected from which the spectral characteristics of poultry facilities were analyzed and compared with background conditions. Poultry facilities were found to have distinguishable characteristics. Descriptive statistics were used to define the range of spectral characteristics encompassing poultry facilities. Thresholding analyses were then utilized to eliminate all image features with spectral characteristics outside of this range. Additional analyses were made to remove noise in the spectral image due to the sun angle, line of sight of camera, variation in roof reflectance due to rust and/or aging, shading by trees, etc. A primary objective in these analyses was to enhance the spectral characteristics for the poultry facility while, at the same time, retaining physical characteristics, i.e. the spectral characteristic is represented by a single blue color with a high brightness value. The techniques developed to achieve a single blue color involved the use of Principal Component Analysis (PCA) on the red color band followed by RGB to Hue and RGB to Saturation analyses on the red and green color bands, respectively, from the resulting image. The features remaining from this series of analyses were converted into polygons (shape file) using ArcView GIS, which was then used to calculate the area and perimeter of each polygon. The parameters utilized to describe the shape of a poultry house included width, length, compactness, length-width ratio, and polygon centroid analysis. Poultry facilities were found to have an average width of approximately 12.6m with a low standard deviation indicating that the widths of all houses were very similar. The length of poultry facilities ranged from 63m to 261m with and average length of 149m. The compactness parameter, which also is related to length and width, ranged from 30 to 130 with a mean value of approximately 57. The shape parameters were used by ArcView GIS to identify polygons that represent poultry facilities. The order of selection was found to be compactness followed by length-width ratio and polygon centroid analysis. A data set that included thirty 35-mm slide images randomly selected from the Rockingham County data set, which contained over 2000 slides, was used to evaluate the automated procedure. The slides contained 182 poultry houses previously identified through manual procedures. Seven facilities were missed and 175 were correctly identified. Ninety-seven percent (97%) of existing poultry facilities were correctly identified which compares favorably with the 97 % accuracy resulted by manual procedures. . The manual procedure described by Mostaghimi, et. al.(1999) only gave the center coordinates for each poultry facility. The automated procedure not only gives the center coordinate for each poultry building but also gives estimates for geometric parameters area, length and width along with an estimate of the capacity of building (i.e. number of birds), and waste load generated by birds including nutrient and bacteria content. The nutrient and bacteria load generated by each poultry facility is important information for conducting TMDL studies currently being developed for impaired Virginia streams. The information is expected to be very helpful to consultants and state agencies conducting the studies. Agricultural support agencies such as USDA/NRCS and USDA/FSA, Extension Service, consultants, etc. will find the information very helpful in the development of implementation plans designed to meet TMDL target water quality goals. The data also should be useful to Water Authorities for selection of appropriate treatment of water supplies and to county and local government jurisdictions for developing policies to minimize the degradation of water supplies.
Ph. D.
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Taylor, Jeremy. "Iron Age and Roman landscapes in the East Midlands : a case study in integrated survey." Thesis, Durham University, 1996. http://etheses.dur.ac.uk/1566/.

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Millinor, William A. "Digital Vegetation Delineation on Scanned Orthorectified Aerial Photography of Petersburg National Battlefield." NCSU, 2000. http://www.lib.ncsu.edu/theses/available/etd-20001123-131211.

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I developed a new methodology to produce an orthorectified mosaic and a vegetation database of Petersburg National Battlefield using mostly digital methods. Both the mosaic and the database meet National Map Accuracy Standards and proved considerably faster than traditional aerial photograph interpretation methods. I classified vegetation polygons to the formation level using the Nature Conservancy?s National Vegetation Classification System. Urban areas were classified using Mitchell?s Classification Scheme for Urban Forest Mapping with Small-Scale Aerial Photographs. This method reduced the production time by 2/3, compared to traditional methods. It also reduced the chance of user error because re-tracing of the linework is not required.

My method started with scanning 75 aerial color IR photos, provided by Petersburg National Battlefield, at 600 dpi. Erdas Imagine was used to rectify the images using United States Geological Service (USGS) Digital Elevation Models (DEM) and black and white USGS Digital Orthophoto Quarter Quadrangles (DOQQ) as reference. The images were then mosaiced to create a seamless color infrared orthorectified basemap of the park. The vegetation polygons were drawn onscreen using ArcMap from Environmental Systems Research Institute, Inc. (ESRI) with the color, orthorectified mosaic as a background image. Stereo pairs of the aerial photos were referenced as needed for clarification of the vegetation. I used a minimum mapping unit (mmu) of 0.2 hectares, which exceeds guidelines defined by the United States Geological Survey ? National Park Service Vegetation Mapping Program. This methodology is easily learned quickly and has already been applied to several other studies.

The production of an orthorectified mosaic, created during the process, from the aerial photographs greatly increases the value of the photographs at little additional cost to the user. The orthorectified basemap can then be used as a backdrop for existing data layers or it can be used to create new GIS data layers. I used a minimum mapping unit (mmu) of 0.2 hectare, which exceeds guidelines defined by the United States Geological Survey-National Park Service Vegetation Mapping Program

Traditionally, vegetation polygons are delineated on acetate for each photograph. The linework on the acetates is then transferred to a basemap using a zoom transfer scope or other transfer instrument. The linework is traced again to digitize it for use in a GIS program. This process is time consuming, and the linework is drawn three times. The redundant tracing increases the chance of user error. My new methodology requires that polygons be delineated only once. I wanted to avoid using the zoom transfer scope and to avoid the redundant linework.

A total of 228 polygons were delineated over 20 separate vegetation and land cover classes with an overall thematic accuracy of 87.42% and a Kappa of .8545. Positional accuracy was very good with a RMSE of 1.62 meters in the x direction and 2.81 meters in the y direction. The Kappa and RMSE values compare favorably with accuracies obtained using traditional vegetation mapping methods.

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Books on the topic "Aerial photography in oceanography"

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Methods of satellite oceanography. Berkeley: University of California Press, 1985.

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Aerial photography. New York: Amphoto, 1990.

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Lloyd, Harvey. Aerial photography. New York: Amphoto, 1990.

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Burns, Joanne. Aerial photography. Wollongong University, N.S.W: Five Islands Press, 1999.

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Banner, Katharine. Aerial photography: Poems. Marton: Mudfog Press, 2003.

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Cottrell, Mark. Kite aerial photography. London: The Kite Store, 1987.

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E, Read Roger, ed. Manual of aerial photography. London: Focal Press, 1986.

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Warner, W. S. Small format aerial photography. Caithness: Whittles, 1996.

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United States. Bureau of Land Management. Denver Service Center, ed. Special aerial photography specifications. Denver, Colo: U.S. Dept. of the Interior, Bureau of Land Management, Service Center, 1987.

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Graham, Ron. Manual of aerial photography. London: Focal, 1986.

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Book chapters on the topic "Aerial photography in oceanography"

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Schmidt, Dietmar, and Friedrich Kühn. "Aerial Photography." In Environmental Geology, 23–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74671-3_3.

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Guthrie, Richard. "Aerial Photography." In Encyclopedia of Earth Sciences Series, 8–13. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73568-9_7.

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Guthrie, Richard. "Aerial Photography." In Selective Neck Dissection for Oral Cancer, 1–6. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-12127-7_7-1.

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Guthrie, Richard. "Aerial Photography." In Selective Neck Dissection for Oral Cancer, 1–6. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-12127-7_7-2.

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Hangay, George, Severiano F. Gayubo, Marjorie A. Hoy, Marta Goula, Allen Sanborn, Wendell L. Morrill, Gerd GÄde, et al. "Aerial Photography." In Encyclopedia of Entomology, 53. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_84.

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Mancini, Keith, and John Sidoriak. "Aerial Photography." In Fundamentals of Forensic Photography, 129–51. New York : Routledge, 2017. | Series: Applications in scientific photography: Routledge, 2017. http://dx.doi.org/10.4324/9781315693125-7.

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Aldred, Oscar. "The Aerial Imagination." In Archaeology and Photography, 193–208. London; New York: Bloomsbury Visual Arts, 2019. |: Routledge, 2020. http://dx.doi.org/10.4324/9781003103325-11.

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Ceraudo, Giuseppe. "Aerial Photography in Archaeology." In Natural Science in Archaeology, 11–30. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01784-6_2.

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Hopley, David. "Aerial Photography of Coral Reefs." In Encyclopedia of Modern Coral Reefs, 13–15. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-2639-2_282.

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Gilbertson, D. D., M. Kent, and F. B. Pyatt. "Aerial photography and satellite imagery." In Practical Ecology for Geography and Biology, 176–93. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4684-1415-8_10.

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Conference papers on the topic "Aerial photography in oceanography"

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Ferreira, Michel, Hugo Conceição, Ricardo Fernandes, and Ozan K. Tonguz. "Stereoscopic aerial photography." In the sixth ACM international workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1614269.1614279.

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Sattar, Naw Safrin, Muhammad Abdullah Adnan, and Maimuna Begum Kali. "Secured aerial photography using Homomorphic Encryption." In 2017 International Conference on Networking, Systems and Security (NSysS). IEEE, 2017. http://dx.doi.org/10.1109/nsyss.2017.7885810.

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Yu, Xinle, Zhanxin Yang, and Chao Chen. "An OFDM Transmission System for Aerial photography." In 2009 International Conference on Management and Service Science (MASS). IEEE, 2009. http://dx.doi.org/10.1109/icmss.2009.5305836.

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Yurchuk, Iryna, Vladyslav Kovdrya, and Lolita Bilyanska. "Segmentation of Digital Images of Aerial Photography." In 2019 IEEE 5th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD). IEEE, 2019. http://dx.doi.org/10.1109/apuavd47061.2019.8943841.

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Murray, John C., Nark J. Neal, and Frederic Labrosse. "Intelligent Kite Aerial Platform for Site Photography." In 2007 IEEE International Conference on Automation Science and Engineering. IEEE, 2007. http://dx.doi.org/10.1109/coase.2007.4341813.

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Tiziani, Hans J. "Measurement of image disturbance in aerial photography." In 8th Meeting in Israel on Optical Engineering, edited by Moshe Oron, Itzhak Shladov, and Yitzhak Weissman. SPIE, 1993. http://dx.doi.org/10.1117/12.150990.

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Knowles, James, James J. Pearson, Brian Ringer, and Joan B. Lurie. "Model-based object recognition in aerial photography." In Interdisciplinary Computer Vision: Applications and Changing Needs--22nd AIPR Workshop, edited by J. Michael Selander. SPIE, 1994. http://dx.doi.org/10.1117/12.169474.

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Shi, Lijuan, Yuanyuan Sun, Jian Zhao, Shuai Han, Jingxiao Bi, and Wenhua Dong. "3D Modeling Based on UAV Aerial Photography." In 2020 International Conference on Virtual Reality and Visualization (ICVRV). IEEE, 2020. http://dx.doi.org/10.1109/icvrv51359.2020.00065.

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Dilich, Michael A., and John M. Goebelbecker. "Accident Investigation and Reconstruction Mapping with Aerial Photography." In International Congress & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1996. http://dx.doi.org/10.4271/960894.

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Li, Ying-cheng, Dong-mei Ye, Xiao-bo Ding, Chang-sheng Teng, Guang-hui Wang, and Tuan-hao Li. "UAV Aerial Photography Technology in Island Topographic Mapping." In 2011 International Symposium on Image and Data Fusion (ISIDF). IEEE, 2011. http://dx.doi.org/10.1109/isidf.2011.6024228.

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Reports on the topic "Aerial photography in oceanography"

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DeRaps, M. R., and N. E. M. Kinsman. Spatially referenced oblique aerial photography of the Golovin shoreline, July 2012. Alaska Division of Geological & Geophysical Surveys, October 2012. http://dx.doi.org/10.14509/24465.

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DeRaps, M. R., and N. E. M. Kinsman. Spatially referenced oblique aerial photography of the Eastern Norton Sound shoreline, July 2011. Alaska Division of Geological & Geophysical Surveys, February 2012. http://dx.doi.org/10.14509/23143.

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Lannom, Keith B., David L. Evans, and Zhiliang Zhu. Comparison of AVHRR classification and aerial photography interpretation for estimation of forest area. New Orleans, LA: U.S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, 1995. http://dx.doi.org/10.2737/so-rp-292.

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Christel, L. M. Using historical aerial photography and softcopy photogrammetry for waste unit mapping in L Lake. Office of Scientific and Technical Information (OSTI), October 1997. http://dx.doi.org/10.2172/658133.

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Provencher, L., and J. M. Dubois. Interpretation guide of natural geographic features from ETM+ Landsat imagery and aerial photography: dune. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2005. http://dx.doi.org/10.4095/314945.

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Provencher, L., and J. M. Dubois. Interpretation guide of natural geographic features from ETM+ Landsat imagery and aerial photography: esker. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2005. http://dx.doi.org/10.4095/314947.

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Provencher, L., and J. M. Dubois. Interpretation guide of natural geographic features from ETM+ Landsat imagery and aerial photography: moraine. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2005. http://dx.doi.org/10.4095/314951.

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Provencher, L., and J. M. Dubois. Interpretation guide of natural geographic features from ETM+ Landsat imagery and aerial photography: reef. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2005. http://dx.doi.org/10.4095/314963.

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Provencher, L., and J. M. Dubois. Interpretation guide of natural geographic features from ETM+ Landsat imagery and aerial photography: pingo. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2005. http://dx.doi.org/10.4095/314961.

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Provencher, L., and J. M. Dubois. Interpretation guide of natural geographic features from ETM+ Landsat imagery and aerial photography: intermittent water. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2005. http://dx.doi.org/10.4095/314953.

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