Relevant bibliographies by topics / Aerial photography in agriculture – Arizona

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

Academic literature on the topic 'Aerial photography in agriculture – Arizona'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 February 2022

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Journal articles on the topic "Aerial photography in agriculture – Arizona"

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Li, Xiaoxiao, Soe W. Myint, Yujia Zhang, Chritopher Galletti, Xiaoxiang Zhang, and Billie L. Turner. "Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography." International Journal of Applied Earth Observation and Geoinformation 33 (December 2014): 321–30. http://dx.doi.org/10.1016/j.jag.2014.04.018.

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Liu, Wei, Xueren Cao, Jieru Fan, Zhenhua Wang, Zhengyuan Yan, Yong Luo, Jonathan S. West, Xiangming Xu, and Yilin Zhou. "Detecting Wheat Powdery Mildew and Predicting Grain Yield Using Unmanned Aerial Photography." Plant Disease 102, no. 10 (October 2018): 1981–88. http://dx.doi.org/10.1094/pdis-12-17-1893-re.

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High-resolution aerial imaging with an unmanned aerial vehicle (UAV) was used to quantify wheat powdery mildew and estimate grain yield. Aerial digital images were acquired at Feekes growth stage (GS) 10.5.4 from flight altitudes of 200, 300, and 400 m during the 2009–10 and 2010–11 seasons; and 50, 100, 200, and 300 m during the 2011–12, 2012–13, and 2013–14 seasons. The image parameter lgR was consistently correlated positively with wheat powdery mildew severity and negatively with wheat grain yield for all combinations of flight altitude and year. Fitting the data with random coefficient regression models showed that the exact relationship of lgR with disease severity and grain yield varied considerably from year to year and to a lesser extent with flight altitude within the same year. The present results raise an important question about the consistency of using remote imaging information to estimate disease severity and grain yield. Further research is needed to understand the nature of interyear variability in the relationship of remote imaging data with disease or grain yield. Only then can we determine how the remote imaging tool can be used in commercial agriculture.
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Pashkov, S. V., and G. Z. Mazhitova. "Application of GIS Technologies and Aerial Photography for Geoinformation Mapping and Modelling of Relief of Agroland Landscapes." Bulletin of Irkutsk State University. Series Earth Sciences 34 (2020): 82–95. http://dx.doi.org/10.26516/2073-3402.2020.34.82.

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The article is devoted to one of the topical applied areas of agrarian landscape research – geoinformation mapping, the development of maps and models of the topography of agricultural areas. The authors demonstrate results of works on large-scale geoinformation mapping and modeling of the topography of the oldest region of bogharic agriculture of Kazakhstan – North Kazakhstan region using methods and materials of remote sensing data and GIS technologies. The main source material in the study was a series of aerial photographs obtained from an unmanned aerial vehicle (UAV). The site of photographing was carried out by GEOSCAN-Kazakhstan LLP with using the Geoscan-201M Agro/Geodesy aerial photography complex. Characteristics of photographing: height – 280 m, visible range – 5 cm/pixel, multispectral – 13 cm/pixel. Geoinformation data on the nature of the relief were obtained during field studies in 2018-2020. Studies were carried out at the local level on the example of agricultural area located in the north of the region within the forest and steppe arable small-circuit agrarian landscape. Based on the results of the study, an electronic vector basis and specialized attribute data of the key area in the GIS environment, a digital relief model were prepared, spatial analysis and modeling of the geomorphological device of the arable surface were performed. The importance of the work is given by a significant agrogenic transformation of the relief of the definite locality during the almost 270-year history of agriculture. A series of maps of the main characteristics and morphometric indicators of the relief, significant from the point of view of crop production intensification and the development of accurate (precision) agriculture of the region, has been worked out. As a result of the study, the methodology of large-scale geoinformation mapping and modeling of the terrain of agrolandscapes in the GIS environment based on aerial photographs from UAVs was developed and tested. The algorithm of work has been compiled, starting from field studies, completing with the development of thematic maps and morphometric analysis of the relief and nature of the surface structure of the studied area.
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Piekielek, Nathan. "A semi-automated workflow for processing historic aerial photography." Abstracts of the ICA 1 (July 15, 2019): 1. http://dx.doi.org/10.5194/ica-abs-1-299-2019.

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<p><strong>Abstract.</strong> Libraries, museums and archives were the original big geospatial information repositories that to this day house thousands to millions of resources containing research-quality geographic information. However, these print resources (and their digital surrogates), are not easily incorporated into the contemporary research process because they are not structured data that is required of web-mapping and geographic information system tools. Fortunately, contemporary big data tools and methods can help with the large-scale conversion of historic resources into structured datasets for mapping and spatial analysis.</p><p>Single frame historic aerial photographs captured originally on film (hereafter “photographs”), are some of the most ubiquitous and information-rich geographic information resources housed in libraries, museums and archives. Photographs authentically encoded information about past places and time-periods without the thematic focus and cartographic generalization of historic print maps. As such, they contain important information in nearly every category of base mapping (i.e. transportation networks, populated places etc.), that is useful to a broad spectrum of research projects and other applications. Photographs are also some of the most frustrating historic resources to use due to their very large map-scale (i.e. small geographic area), lack of reference information and often unknown metadata (i.e. index map, flight altitude, direction etc.).</p><p>The capture of aerial photographs in the contiguous United States (U.S.) became common in the 1920s and was formalized in government programs to systematically photograph the nation at regular time intervals beginning in the 1930s. Many of these photography programs continued until the 1990s meaning that there are approximately 70 years of “data” available for the U.S. that is currently underutilized due to inaccessibility and the challenges of converting photographs to structured data. Large collections of photographs include government (e.g. the U.S. Department of Agriculture Aerial Photography Field Office “The Vault” – over 10 million photographs), educational (e.g. the University of California Santa Barbara Library – approximately 2.5 million photographs), and an unknown number non-governmental organizations (e.g. numerous regional planning commissions and watershed conservation groups). Collectively these photography resources constitute an untapped big geospatial data resource.</p><p>U.S. government photography programs such as the National Agricultural Imagery Program continued and expanded in the digital age (i.e. post early 2000s), so that not only is there opportunity to extend spatial analyses back in time, but also to create seamless datasets that integrate with current and expected future government aerial photography campaigns. What is more, satellite imagery sensors have improved to the point that there is now overlap between satellite imagery and aerial photography in terms of many of their technical specifications (i.e. spatial resolution etc.). The remote capture of land surface imagery is expanding rapidly and with it are new opportunities to explore long-term land-change analyses that require historical datasets.</p><p>Manual methods to process photographs are well-known, but are too labour intensive to apply to entire photography collections. Academic research on methods to increase the discoverability of photographs and convert them to geospatial data at large-scale has to date been limited (although see the work of W. Karel et al.). This presentation details a semi-automated workflow to process historic aerial photographs from U.S. government sources and compares the workflow and results to existing methods and datasets. In a pilot test area of 94 photographs in the U.S. state of Pennsylvania, the workflow was found to be nearly 100-times more efficient than commonly employed alternatives while achieving greater horizontal positional accuracy. Results compared favourably to contemporary digital aerial photography data products, suggesting that they are well-suited for integration with contemporary datasets. Finally, initial results of the workflow were incorporated into several existing online discovery and sharing platforms that will be highlighted in this presentation. Early online usage statistics as well as direct interaction with users demonstrates the broad interest and high-impact of photographs and their derived products (i.e. structured geospatial data).</p>
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Beloev, Ivan H. "A Review on Current and Emerging Application Possibilities for Unmanned Aerial Vehicles." Acta Technologica Agriculturae 19, no. 3 (September 1, 2016): 70–76. http://dx.doi.org/10.1515/ata-2016-0015.

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Abstract This paper presents a review on current and emerging application possibilities for unmanned aerial vehicles (UAVs). The introduction section of the paper briefly describes some of the application areas in which drones are currently being used. The next chapters of the paper describe more detailly the use of UAVs for aerial photography, filming, security and logistics, GIS, land and water surveys. The main focus of the last chapters is on the advantages and the disadvantages of the drones usage in precision agriculture, wildlife and nature observations and archaeology. The last chapters also provide information on how the advanced information technology solutions can be implemented in order to provide means for fighting invasive species, to increase the yield of certain crops, to monitor and predict flooding, wildfires and other disasters, etc. This paper provides only overview of the most interesting and widely available applications of the UAVs, but there are also many other more specific and dedicated solutions for implementation of the drones for different purposes.
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Nguyen, Khang, Nhut T. Huynh, Phat C. Nguyen, Khanh-Duy Nguyen, Nguyen D. Vo, and Tam V. Nguyen. "Detecting Objects from Space: An Evaluation of Deep-Learning Modern Approaches." Electronics 9, no. 4 (March 30, 2020): 583. http://dx.doi.org/10.3390/electronics9040583.

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Unmanned aircraft systems or drones enable us to record or capture many scenes from the bird’s-eye view and they have been fast deployed to a wide range of practical domains, i.e., agriculture, aerial photography, fast delivery and surveillance. Object detection task is one of the core steps in understanding videos collected from the drones. However, this task is very challenging due to the unconstrained viewpoints and low resolution of captured videos. While deep-learning modern object detectors have recently achieved great success in general benchmarks, i.e., PASCAL-VOC and MS-COCO, the robustness of these detectors on aerial images captured by drones is not well studied. In this paper, we present an evaluation of state-of-the-art deep-learning detectors including Faster R-CNN (Faster Regional CNN), RFCN (Region-based Fully Convolutional Networks), SNIPER (Scale Normalization for Image Pyramids with Efficient Resampling), Single-Shot Detector (SSD), YOLO (You Only Look Once), RetinaNet, and CenterNet for the object detection in videos captured by drones. We conduct experiments on VisDrone2019 dataset which contains 96 videos with 39,988 annotated frames and provide insights into efficient object detectors for aerial images.
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Shin, Patrick, Temuulen Sankey, Margaret Moore, and Andrea Thode. "Evaluating Unmanned Aerial Vehicle Images for Estimating Forest Canopy Fuels in a Ponderosa Pine Stand." Remote Sensing 10, no. 8 (August 11, 2018): 1266. http://dx.doi.org/10.3390/rs10081266.

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Forests in the Southwestern United States are becoming increasingly susceptible to large wildfires. As a result, forest managers are conducting forest fuel reduction treatments for which spatial fuels and structure information are necessary. However, this information currently has coarse spatial resolution and variable accuracy. This study tested the feasibility of using unmanned aerial vehicle (UAV) imagery to estimate forest canopy fuels and structure in a southwestern ponderosa pine stand. UAV-based multispectral images and Structure-from-Motion point clouds were used to estimate canopy cover, canopy height, tree density, canopy base height, and canopy bulk density. Estimates were validated with field data from 57 plots and aerial photography from the U.S. Department of Agriculture National Agriculture Imaging Program. Results indicate that UAV imagery can be used to accurately estimate forest canopy cover (correlation coefficient (R2) = 0.82, root mean square error (RMSE) = 8.9%). Tree density estimates correctly detected 74% of field-mapped trees with a 16% commission error rate. Individual tree height estimates were strongly correlated with field measurements (R2 = 0.71, RMSE = 1.83 m), whereas canopy base height estimates had a weaker correlation (R2 = 0.34, RMSE = 2.52 m). Estimates of canopy bulk density were not correlated to field measurements. UAV-derived inputs resulted in drastically different estimates of potential crown fire behavior when compared with coarse resolution LANDFIRE data. Methods from this study provide additional data to supplement, or potentially substitute, traditional estimates of canopy fuel.
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Flórez, Jimmy, José Ortega, Andrés Betancourt, Andrés García, Marlon Bedoya, and Juan S. Botero. "A review of algorithms, methods, and techniques for detecting UAVs and UAS using audio, radiofrequency, and video applications." TecnoLógicas 23, no. 48 (May 15, 2020): 269–85. http://dx.doi.org/10.22430/22565337.1408.

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Unmanned Aerial Vehicles (UAVs), also known as drones, have had an exponential evolution in recent times due in large part to the development of technologies that enhance the development of these devices. This has resulted in increasingly affordable and better-equipped artifacts, which implies their application in new fields such as agriculture, transport, monitoring, and aerial photography. However, drones have also been used in terrorist acts, privacy violations, and espionage, in addition to involuntary accidents in high-risk zones such as airports. In response to these events, multiple technologies have been introduced to control and monitor the airspace in order to ensure protection in risk areas. This paper is a review of the state of the art of the techniques, methods, and algorithms used in video, radiofrequency, and audio-based applications to detect UAVs and Unmanned Aircraft Systems (UAS). This study can serve as a starting point to develop future drone detection systems with the most convenient technologies that meet certain requirements of optimal scalability, portability, reliability, and availability.
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Korobov, Dmitry S., and Alexander V. Borisov. "The origins of terraced field agriculture in the Caucasus: new discoveries in the Kislovodsk basin." Antiquity 87, no. 338 (November 22, 2013): 1086–103. http://dx.doi.org/10.1017/s0003598x00049887.

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Terraced field systems are a feature of many regions of the world and have been dated as early as 6000 cal BC in the Levant (Kuijt et al. in Antiquity 81 (2007: 106–18)). The discovery of agricultural terraces in the northern Caucasus, reported here, extends their distribution into a new area. Relatively low population levels in the late medieval and early modern periods have preserved several blocks of terraced fields, some of them created at the beginning of the first millennium BC, others in the mid first millennium AD. The earlier terraced fields, associated with material and settlements of the Koban culture, culminated in over-exploitation of the land and exacerbated erosion during environmental change in the mid first millennium BC. The later series of terraced fields are of different form and are associated with the settlement in the area of communities of Alans in the first millennium AD. They largely avoided the areas rendered infertile by Koban period overexploitation. The morphology and chronology of the terraced field systems are explored using a combination of aerial photography, GIS analysis and field investigations.
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Davoli, Luca, Emanuele Pagliari, and Gianluigi Ferrari. "Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming." Drones 5, no. 2 (April 15, 2021): 26. http://dx.doi.org/10.3390/drones5020026.

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Unmanned Aerial Vehicles (UAVs) and small drones are nowadays being widely used in heterogeneous use cases: aerial photography, precise agriculture, inspections, environmental data collection, search-and-rescue operations, surveillance applications, and more. When designing UAV swarm-based applications, a key “ingredient” to make them effective is the communication system (possible involving multiple protocols) shared by flying drones and terrestrial base stations. When compared to ground communication systems for swarms of terrestrial vehicles, one of the main advantages of UAV-based communications is the presence of direct Line-of-Sight (LOS) links between flying UAVs operating at an altitude of tens of meters, often ensuring direct visibility among themselves and even with some ground Base Transceiver Stations (BTSs). Therefore, the adoption of proper networking strategies for UAV swarms allows users to exchange data at distances (significantly) longer than in ground applications. In this paper, we propose a hybrid communication architecture for UAV swarms, leveraging heterogeneous radio mesh networking based on long-range communication protocols—such as LoRa and LoRaWAN—and IEEE 802.11s protocols. We then discuss its strengths, constraints, viable implementation, and relevant reference use cases.
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Dissertations / Theses on the topic "Aerial photography in agriculture – Arizona"

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Knapp, Paul Aaron. "THE USE OF LARGE-SCALE AERIAL PHOTOGRAPHY FOR DETECTING CHANGES OF AN ARID RANGELAND IN SOUTHWESTERN ARIZONA." Thesis, The University of Arizona, 1985. http://hdl.handle.net/10150/292059.

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Interpretation of large-scale color infrared and color aerial photography can be a labor and cost-effective means for inventorying and monitoring rangelands while maintaining accuracy. Ground measurements of vegetation cover at Organ Pipe Cactus National Monument were taken in 1975 and 1984. Large-scale (1:1200) color and color infrared aerial photo estimates were compared to these ground measurements through regression and correlation to check photo accuracy. Relationships between photo estimates and ground measurements of total vegetation and shrub cover were strong when using either film type. Color infrared photo estimates corresponded better with ground measurements for both tree cover and cactus cover than color photo estimates. Large-scale aerial photography is also useful for determining some of the causes of vegetation change. Evidence gathered from both sets of photos suggested that vegetation change at OPCNM was largely the result of domestic livestock removal and short-term climatic fluctuations.
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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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Hui, Lin Ning. "THE USE OF LARGE SCALE COLOR AERIAL PHOTOGRAPHY TO MONITOR CATTLE GRAZING IN MESQUITE GRASSLANDS, SOUTHERN ARIZONA." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/275514.

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Tickes, Barry. "The Comparison of Aerial and Sprinkler Applied Delayed Applications of Kerb® to Lettuce." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2004. http://hdl.handle.net/10150/215253.

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Five tests were conducted to compare delayed applications of Kerb applied by air with applications made through sprinklers. Applications were made commercially to plots ranging in size from 11 to 18 acres. Broadleaf weed control was better in all tests from the sprinkler applied Kerb than from aerial application. The control of volunteer sudangrass was poor in one test from both types of applications and worse from the sprinkler than the aerial application. It was concluded that applying Kerb though sprinklers to lettuce is effective and often superior to aerial applications.
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Pryor, Logan S. "Land-cover mapping in an agriculture zone using simulated Sentinel-2 data." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Geography, c2012, 2012. http://hdl.handle.net/10133/3367.

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Remote sensing technologies are used to assist in the mapping and monitoring of land cover in space and time. The European Space Agency’s (ESA) upcoming Sentinel-2 MultiSpectral Instrument (MSI) to be launched in 2013 has improved spatial and spectral properties compared to the current large-swath medium-resolution satellite sensors. Prior to the deployment of future sensors it is important to simulate and test the sensor data to evaluate the sensor's potential performance in producing the existing data products and develop new algorithms. This study simulated Sentinel-2 MSI data from airborne hyperspectral data over an agriculture area in northern Alberta, Canada. The standard Sentinel-2 MSI land-cover product was evaluated by comparing it to one created from the standard Landsat 5 TM and SPOT 5 HRV data products. Furthermore the standard Sentinel-2 MSI water column content band configuration and algorithm was evaluated for atmospheric correction purposes.
xi, 90 leaves : col. ill. ; 29 cm
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Wolters, Dustin Joseph. "Assessment of Corn Plant Population at Emergence from Processed Color Aerial Imagery." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437666741.

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Chesser, Zack B. "Integrated management techniques used for cogongrass control." Master's thesis, Mississippi State : Mississippi State University, 2007. http://library.msstate.edu/etd/show.asp?etd=etd-11052007-162512.

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Pelcat, Yann S. "Soil landscape characterization of crop stubble covered fields using Ikonos high resolution panchromatic images." Thesis, Winnipeg : University of Manitoba, 2006. http://www.collectionscanada.ca/obj/s4/f2/dsk3/MWU/TC-MWU-224.pdf.

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Thesis (M.Sc.)--University of Manitoba, 2006.
A thesis submitted to the Faculty of Graduate Studies in partial fulfillment of the requirements for the degree of Master of Science, Department of Soil Science. Includes bibliographical references.
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Román, Glenda M. "Spectral merging and object-oriented classification of National Agriculture Imagery Program (NAIP) digital aerial photography and landsat TM data." 2006. http://catalog.hathitrust.org/api/volumes/oclc/71514930.html.

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Thesis (M.S.)--University of Wisconsin--Madison, 2006.
Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 48-50).
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Books on the topic "Aerial photography in agriculture – Arizona"

1

Rundquist, Donald C. A guide to the practical use of aerial color-infrared photography in agriculture. [Lincoln]: Conservation and Survey Division, Institute of Agriculture and Natural Resources, University of Nebraska--Lincoln, 1988.

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Workshop on Color Aerial Photography in the Plant Sciences (11th 1987 Weslaco, Tex.). Color aerial photography and videography in the plant sciences and related fields: Proceedings of the eleventh biennial Workshop on Color Aerial Photography in the Plant Sciences, held at Hoblitzelle Auditorium, Agricultural Experiment Station, Weslaco, Texas, April 27-May 1, 1987. Edited by Everitt J. H, Nixon Paul R, United States. Agricultural Research Service. Laboratory., and American Society for Photogrammetry and Remote Sensing. Falls Church, Va: The Society, 1987.

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Workshop on Color Aerial Photography in the Plant Sciences. Color aerial photography in the plant sciences and related fields: A compendium, 1967-1983 : selected papers from the first nine Biennial Workshops on Color Aerial Photography in the Plant Sciences. Falls Church, VA: American Society for Photogrammetry and Remote Sensing, 1988.

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Fukuhara, Michikazu. Uchū kara mita Nihon no nōgyō. Ibaraki-ken Tsukuba-shi: Nōrin Suisanshō Nōgyō Kankyō Gijutsu Kenkyūjo, 1993.

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Nesby, R. N. Interpretation of native range vegetation from 1:500 70-mm large-scale color and color infrared photography. Edmonton: Alberta Energy and Natural Resources, 1986.

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Fasolo, Michele. Antichi paesaggi agrari d'Italia nelle banche dati dell'AGEA. Roma: Agenzia per le Erogazioni in Agricoltura, 2006.

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Čulíková, Lucie. Nedestruktivní výzkum polních systémů: Non-destructive research of field systems. Plzeň: Katedra archeologie Fakulty filozofické Západočeské univerzity v Plzni, 2013.

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Turner, Raymond M. The changing mile revisited: An ecological study of vegetation change with time in the lower mile of an arid and semiarid region. Tucson, AZ: University of Arizona Press, 2003.

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Color aerial photography in the plant sciences and related fields: A compendium, 1967-1983 : Selected papers from the first nine Biennial Workshops on Color Aerial Photography in the Plant Sciences. American Society for Photogrammetry and Remote Sensing, 1988.

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Friedkin, William C. Digital analysis of remotely sensed images for evaluating color in turfgrass. 1996.

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Book chapters on the topic "Aerial photography in agriculture – Arizona"

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Burger, B. "ADAR Digital Aerial Photography Applications In Precision Farming." In Proceedings of the Third International Conference on Precision Agriculture, 905. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1996.precisionagproc3.c108.

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Jiang, Wencong, Yanling Li, Yong Liang, and Yanwei Zeng. "Research on Quality Index System of Digital Aerial Photography Results." In Computer and Computing Technologies in Agriculture IV, 381–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18336-2_47.

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Wang, Xiaojun, Yanling Li, Yong Liang, and Yanwei Zeng. "Research on Quality Inspection Method of Digital Aerial Photography Results." In Computer and Computing Technologies in Agriculture IV, 392–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18336-2_48.

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Zeng, Yanwei, Yong Liang, Wencong Jiang, and Xiaojun Wang. "Research on Automatic Inspection Methods of Flight Quality of Digital Aerial Photography Results." In Computer and Computing Technologies in Agriculture V, 176–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27275-2_19.

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Liang, Yong, Yanwei Zeng, Wencong Jiang, and Xiaojun Wang. "Research on Automatic Inspection Methods of Image Quality of Digital Aerial Photography Results." In Computer and Computing Technologies in Agriculture V, 320–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27275-2_37.

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Bausch, Walter, and Kenan Diker. "Image Analysis of 35-mm Aerial Photography for Estimating Various Plant Parameters." In Proceedings of the Fourth International Conference on Precision Agriculture, 1617. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1999.precisionagproc4.c66b.

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Franzen, David W., Lance Reitmeier, Joseph F. Giles, and Allan C. Cattanach. "Aerial Photography and Satellite Imagery to Detect Deep Soil Nitrogen Levels in Potato and Sugarbeet." In Proceedings of the Fourth International Conference on Precision Agriculture, 281–90. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/1999.precisionagproc4.c24.

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BLAKEMAN, R. H. "THE IDENTIFICATION OF CROP DISEASE AND STRESS BY AERIAL PHOTOGRAPHY." In Applications of Remote Sensing in Agriculture, 229–54. Elsevier, 1990. http://dx.doi.org/10.1016/b978-0-408-04767-8.50020-7.

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Jain, Lokesh Kumar. "Remote Sensing Techniques and Its Application in Arid Zones of India." In Environmental Information Systems, 1065–79. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7033-2.ch047.

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Remote sensing technologies offer the potential for contributing the security to human existence on arid zones in the country in variety of ways. Remote Sensing in agriculture particularly for natural resource management. It provides important coverage, mapping and classification of land cover features. The remote view of the sensor and the ability to store, analyze, and display the sensed data on field maps are make remote sensing a potentially important tool for agriculture. The aerial photography gives two main advantages viz., speedy survey in very large area or remote area and precise description and recording of resources status. Remotely sensed images provide a means to assess field conditions and gave valuable insights into agronomic management. It led to understanding of leaf reflectance and leaf emittance changes in response to leaf thickness, species, canopy shape, leaf age, nutrient status, and water status. Understanding of leaf reflectance has led to quantify various agronomic parameters, e.g., leaf area, crop cover, biomass, crop type, nutrient status, and yield.
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Jain, Lokesh Kumar. "Remote Sensing Techniques and Its Application in Arid Zones of India." In Advances in Geospatial Technologies, 193–211. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1814-3.ch009.

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Abstract:
Remote sensing technologies offer the potential for contributing the security to human existence on arid zones in the country in variety of ways. Remote Sensing in agriculture particularly for natural resource management. It provides important coverage, mapping and classification of land cover features. The remote view of the sensor and the ability to store, analyze, and display the sensed data on field maps are make remote sensing a potentially important tool for agriculture. The aerial photography gives two main advantages viz., speedy survey in very large area or remote area and precise description and recording of resources status. Remotely sensed images provide a means to assess field conditions and gave valuable insights into agronomic management. It led to understanding of leaf reflectance and leaf emittance changes in response to leaf thickness, species, canopy shape, leaf age, nutrient status, and water status. Understanding of leaf reflectance has led to quantify various agronomic parameters, e.g., leaf area, crop cover, biomass, crop type, nutrient status, and yield.
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Conference papers on the topic "Aerial photography in agriculture – Arizona"

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Heinlein, Sarah N., Terry L. Pavlis, and Ronald Bruhn. "GEOMORPHOLOGY, HIGH-RESOLUTION LIDAR, AND AERIAL PHOTOGRAPHY DATA - EXTRACTING GEOLOGIC INSIGHTS FROM 3D MODELING - RAGGED MOUNTAIN FAULT SOUTHERN ALASKA, USA." In GSA Annual Meeting in Phoenix, Arizona, USA - 2019. Geological Society of America, 2019. http://dx.doi.org/10.1130/abs/2019am-340249.

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Molnia, Bruce F., Kim M. Angeli, Shawn J. Dilles, Gary B. Fisher, and E. Terrence Slonecker. "THE FLUVIAL-MARINE TRANSITION IN SPACE AND TIME - USING GLOBAL FIDUCIALS HIGH RESOLUTION IMAGERY, LANDSAT, AND AERIAL PHOTOGRAPHY TO MONITOR SIX DECADES OF CHANGE AT EAST TIMBALIER ISLAND, LOUISIANA: 1953 - 2019." In GSA Annual Meeting in Phoenix, Arizona, USA - 2019. Geological Society of America, 2019. http://dx.doi.org/10.1130/abs/2019am-339109.

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