Dissertations / Theses: 'Aerial videography Remote sensing'

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Gastonguay, Jean-Michel. "Mise au point d'un reflectomètre imageur à partir de la vidéographie aérienne multispectrale (VAM) /." Thèse, Chicoutimi : Université du Québec à Chicoutimi, 2002. http://theses.uqac.ca.

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Sayeg, Heitor Siqueira [UNESP]. "Uso de filmagem aérea em perspectiva no apoio à coleta de dados, na pesquisa, no ensino e na divulgação de informações em Geociências." Universidade Estadual Paulista (UNESP), 2008. http://hdl.handle.net/11449/102935.

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Made available in DSpace on 2014-06-11T19:32:19Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-01-17Bitstream added on 2014-06-13T20:03:42Z : No. of bitstreams: 1 sayeg_hs_dr_rcla.pdf: 3535019 bytes, checksum: a38e98172ed9f1310d44aef93596cf8b (MD5)
Fotografia aérea NADIR é um conceito usado rotineiramente por geólogos e pesquisadores de vários campos de atividade. Filmagem aérea de baixa altitude, em perspectiva ou ortogonal, é um recurso muito acessível, pela qualidade e relação custo-benefício dos equipamentos digitais disponíveis, pela capacidade de processamento e facilidade de operação dos softwares e hardwares lançados no mercado e pelo custo da hora de vôo em aviões de pequeno porte. A visualização da organização das paisagens através de filmagens aéreas em perspectiva permite a construção de um banco de dados de fácil manuseio e fornece um ponto de vista complementar às informações derivadas de outras fontes. Os estudos e ações efetuados buscaram explorar essa técnica de registro de dados e testar seu potencial para compor material didático e transmitir informações específicas de interesse geológico.
Vertical aerial videography is a commonly technique used by geologists and researchers from several fields of knowledge. Aerial videography of low altitude, in oblique viewing, is a resource not spread, but very accessible, by the quality of digital equipment available, by capacity and facility of software and hardware operation and by the low cost of flight hour in small planes. The terrain observation (imaging) and oblique visualization of landscape in TV language allow building data base, to promote discrimination of surface landforms and morphologic patterns with tectonic meanings, and supply an approach that supplement the information derived from other media. In this work the goal was to apply this technique of data register in low cost and complexity of data treatment, test its aptitude to compose the didactic material and transmit specific information from geological interest.

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Reames, Steve. "Detecting the Presence of Disease by Unifying Two Methods of Remote Sensing." Thesis, University of North Texas, 2002. https://digital.library.unt.edu/ark:/67531/metadc3120/.

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There is currently no effective tool available to quickly and economically measure a change in landmass in the setting of biomedical professionals and environmental specialists. The purpose of this study is to structure and demonstrate a statistical change-detection method using remotely sensed data that can detect the presence of an infectious land borne disease. Data sources included the Texas Department of Health database, which provided the types of infectious land borne diseases and indicated the geographical area to study. Methods of data collection included the gathering of images produced by digital orthophoto quadrangle and aerial videography and Landsat. Also, a method was developed to identify statistically the severity of changes of the landmass over a three-year period. Data analysis included using a unique statistical detection procedure to measure the severity of change in landmass when a disease was not present and when the disease was present. The statistical detection method was applied to two different remotely sensed platform types and again to two like remotely sensed platform types. The results indicated that when the statistical change detection method was used for two different types of remote sensing mediums (i.e.-digital orthophoto quadrangle and aerial videography), the results were negative due to skewed and unreliable data. However, when two like remote sensing mediums were used (i.e.- videography to videography and Landsat to Landsat) the results were positive and the data were reliable.

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Sayeg, Heitor Siqueira. "Uso de filmagem aérea em perspectiva no apoio à coleta de dados, na pesquisa, no ensino e na divulgação de informações em Geociências /." Rio Claro : [s.n.], 2007. http://hdl.handle.net/11449/102935.

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Orientador: Gilberto José Garcia
Banca: Sergio dos Anjos Ferreira Pinto
Banca: Arquimedes Peres Filho
Banca: Norberto Morales
Banca: Olavo Raymundo Junior
Resumo: Fotografia aérea NADIR é um conceito usado rotineiramente por geólogos e pesquisadores de vários campos de atividade. Filmagem aérea de baixa altitude, em perspectiva ou ortogonal, é um recurso muito acessível, pela qualidade e relação custo-benefício dos equipamentos digitais disponíveis, pela capacidade de processamento e facilidade de operação dos softwares e hardwares lançados no mercado e pelo custo da hora de vôo em aviões de pequeno porte. A visualização da organização das paisagens através de filmagens aéreas em perspectiva permite a construção de um banco de dados de fácil manuseio e fornece um ponto de vista complementar às informações derivadas de outras fontes. Os estudos e ações efetuados buscaram explorar essa técnica de registro de dados e testar seu potencial para compor material didático e transmitir informações específicas de interesse geológico.
Abstract: Vertical aerial videography is a commonly technique used by geologists and researchers from several fields of knowledge. Aerial videography of low altitude, in oblique viewing, is a resource not spread, but very accessible, by the quality of digital equipment available, by capacity and facility of software and hardware operation and by the low cost of flight hour in small planes. The terrain observation (imaging) and oblique visualization of landscape in TV language allow building data base, to promote discrimination of surface landforms and morphologic patterns with tectonic meanings, and supply an approach that supplement the information derived from other media. In this work the goal was to apply this technique of data register in low cost and complexity of data treatment, test its aptitude to compose the didactic material and transmit specific information from geological interest.
Doutor

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McLaughlin, Stephan. "Évaluation de la densité (tiges/ha.) et caractérisation de la défoliation d'un territoire forestier boréal à l'aide de la vidéographie aérienne multispectrale (VAM) /." Thèse, Chicoutimi : Université du Québec à Chicoutimi, 1998. http://theses.uqac.ca.

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Polizel, Jefferson Lordello. "Geotecnologias e clima urbano: aplicação dos recursos de sensoriamento remoto e sistema de informações geográficas na cidade de Piracicaba, SP." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/8/8135/tde-05022010-101157/.

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A referida pesquisa tem como finalidade usar ferramentas de geotecnologias para mapear a distribuição espacial do campo térmico da cidade de Piracicaba, SP e comparar os diferentes tipos de superfícies urbanas. Foram feitas coletas de temperatura em 3 áreas distintas, em determinados horários, na estação do verão e inverno. Nesses pontos de coleta de temperatura foram criados polígonos circulares e por meio desses polígonos circulares foram retirados das imagens de alta resolução da videografia aérea multiespectral, utilizando a técnica de classificação supervisionada foram separados as porcentagens dos diferentes tipos das superfícies urbanas. Foram feitas comparações com imagens térmicas, e correlacionadas com pixels retirados do NDVI (Índice de Vegetação por Diferença Normalizada) das imagens multiespectrais da videografia aérea multiespectral, os resultados obtidos do R2=0,68. Outras comparações foram realizadas com as temperaturas coletadas e com cenas da banda 6 do Satélite Landsat 5. Para transformação das cenas, foi utilizado o algoritmo de transformação do software IDRISI 3.2. Foi possível obter mapas temáticos com valores da temperatura radiante da superfície urbana da cidade de Piracicaba. Os resultados obtidos pela comparação entre as classes de cobertura, copa de árvore e a temperatura foram satisfatórios obtendo-se um R2 de 0,56 para polígonos circulares de 50 metros, outros resultados como lago/lagoa o R2 foi 0,72 e para sombra 0,24. Com a evolução dos recursos de geotecnologia, sensoriamento remoto, sistema de informações geográficas, informações mais detalhadas serão obtidas do tecido urbano.
This research aims to use tools to map the geo-spatial distribution of thermal field in Piracicaba, SP, and compare the different types of urban surfaces. Samples were performed in temperature in 3 different areas, at certain times, in the summer season and winter. These collection points were set up temperature circular polygons and polygons through these circulars were derived from images of high resolution multispectral aerial videography, using the technique of supervised classification were separated from the percentages of different types of urban surfaces. Comparisons were made with thermal imaging and correlated with pixels taken from NDVI (Normalized Difference Vegetation Index) the multispectral images of multispectral aerial videography, the results of R2 = 0,68. Other comparisons were made with the temperatures collected and scenes of the band 6 of Landsat 5 (TM). For processing the scenes, we used the algorithm processing software IDRISI 3.2. It was possible to obtain thematic maps with radiant values temperature of the surface of the town of Piracicaba. The results obtained by comparing the classes of coverage, and canopy temperature were adequate to yield an R2 of 0,56 for circular polygons of 50 meters, other results such as lake/pond R2 was 0,72 and for shade 0,24. With the development of resources of geotechnology, remote sensing, geographic information system, more detailed information will be obtained from the urban fabric.

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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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Sivarajan, Saravanan. "Estimating Yield of Irragated Potatoes Using Aerial and Satellite Remote Sensing." DigitalCommons@USU, 2011. http://digitalcommons.usu.edu/etd/1033.

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Multispectral aerial and satellite remote sensing plays a major role in crop yield prediction due to its ability to detect crop growth conditions on spatial and temporal scales in a cost effective manner. Many empirical relationships have been established in the past between spectral vegetation indices and leaf area index, fractional ground cover, and crop growth rates for different crops through ground sampling. Remote sensing-based vegetation index (VI) yield models using airborne and satellite data have been developed only for grain crops like barley, corn, wheat, and sorghum. So it becomes important to validate and extend the VI-based model for tuber crops like potato, taking into account the most significant parameters that affect the final crop yield of these crops.

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Hayes, Austin Craig. "Evaluating the potential of aerial remote sensing in flue-cured tobacco." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/90296.

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Flue-cured tobacco (Nicotiana tabacum L.) is a high value-per-acre crop that is intensively managed to optimize the yield of high quality cured leaf. Aerial remote sensing, specifically unmanned aerial vehicles (UAVs), present flue-cured tobacco producers and researchers with a potential tool for scouting and crop management. A two-year study, conducted in Southside Virginia at the Southern Piedmont Agricultural Research and Extension Center and on commercial farms, assessed the potential of aerial remote sensing in flue-cured tobacco. The effort encompassed two key objectives. First, examine the use of the enhanced normalized difference vegetation index (ENDVI) for separating flue-cured tobacco varieties and nitrogen rates. Secondly, develop hyperspectral indices and/or machine learning classification models capable of detecting Phytophthora nicotianae (black shank) incidence in flue-cured tobacco. In 2017, UAV-acquired ENDVI surveys demonstrated the ability to consistently separate between flue-cured tobacco varieties and nitrogen rates from topping to harvest. In 2018, ENDVI revealed significant differences among N-rates as early as 34 days after transplanting. Two hyperspectral indices were developed to detect black shank incidence based on differences in the spectral profiles of asymptomatic flue-cured tobacco plants compared to those with black shank symptoms. Testing of the indices showed significant differences between the index values of healthy and symptomatic plants (alpha = 0.05). In addition, the indices were able to detect black shank symptoms pre-symptomatically (alpha = 0.09). Subspace linear discriminant analysis, a machine learning classification, was also used for prediction of black shank incidence with up to 85.7% classification accuracy.
Master of Science
Unmanned Aerial Vehicle’s (UAVs) or drones, as they are commonly referred to, may have potential as a tool in flue-cured tobacco research and production. UAVs combined with sensors and cameras provide the opportunity to gather a large amount of data on a particular crop, which may be useful in crop management. Given the intensive management of flue-cured tobacco, producers may benefit from extra insight on how to better assess threats to yield such as under-fertilization and disease pressure. A two-year study was conducted in Southside Virginia at the Southern Piedmont Agricultural Research and Extension Center and on commercial farms. There were two objectives to this effort. First, assess the ability of UAV-acquired multispectral near-infrared imagery to separate flue-cured tobacco varieties and nitrogen rates. Secondly, develop hyperspectral indices and machine learning models that can accurately predict the incidence of black shank in flue-cured tobacco. Flue-cured tobacco nitrogen rates were significantly different in 2017 from 59 days after transplanting to harvest using UAV-acquired near-infrared imagery. In 2018, heavy rainfall may have led to nitrogen leaching from the soil resulting in nitrogen rates being significantly different as early as 34 days after transplanting. The imagery also showed a significant relationship with variety maturation type in the late stages of crop development during ripening. Two hyperspectral indices were developed and one machine learning model was trained. Each had the ability to detect black shank incidence in fluecured tobacco pre-symptomatically, as well as separated black shank infested plants from healthy plants.

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Sivarajan, Saravanan. "Estimating Yield of Irrigated Potatoes Using Aerial and Satellite Remote Sensing." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/1049.

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Multispectral aerial and satellite remote sensing plays a major role in crop yield prediction due to its ability to detect crop growth conditions on spatial and temporal scales in a cost effective manner. Many empirical relationships have been established in the past between spectral vegetation indices and leaf area index, fractional ground cover, and crop growth rates for different crops through ground sampling. Remote sensing-based vegetation index (VI) yield models using airborne and satellite data have been developed only for grain crops like barley, corn, wheat, and sorghum. So it becomes important to validate and extend the VI-based model for tuber crops like potato, taking into account the most significant parameters that affect the final crop yield of these crops.

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Nesbit, Paul R. "Uninhabited Aerial Vehicles and Structure from Motion| A fresh approach to photogrammetry." Thesis, California State University, Long Beach, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1526938.

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Three-dimensional mapping and modeling can contribute to knowledge about the real world. Techniques are largely driven by available technology and typically involve expensive equipment and expert skill. Recent advances have led to low-cost remotely sensed data collection and generation of 3D terrain models using Uninhabited Aerial Vehicles (UAV) and Structure from Motion (SfM) processing software. This research presents a low-cost alternative to 3D mapping by pairing UAV collection methods with three SfM processing techniques. Surface models are generated from the same image set captured from a low-cost UAV coupled with a digital camera. Accuracy of resulting models identifies strengths and weaknesses of each technique. Analysis of different slope ranges investigates the divide at which surfaces generated become less reliable. This research provides a deeper understanding of the strengths and limitations of emerging technologies used together in a fresh approach to photogrammetry.

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Howard, Donald Benton. "Remote sensing, processing and transmission of data for an unmanned aerial vehicle." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA283104.

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Perry, John Hendrix. "A synthesized directly georeferenced remote sensing technique for small unmanned aerial vehicles." [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0025070.

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Demiraslan, Tugay. "Estimation of DBH Using Tree Variables Derived from Aerial LiDAR for Ford Forest, Baraga, Michigan." Thesis, Michigan Technological University, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13422276.

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This study implemented LiDAR (Light Detection and Ranging) remote sensing technology and applied ITD (Individual Tree Detection) methods as an approach to estimate some essential tree variables, such as DBH (Diameter at Breast Height), height, volume, and biomass for Ford Forest Research Center in Upper Peninsula, Michigan. There were 34 deciduous (1 bigtooth aspen, 9 red oaks, 20 sugar maples, 2 white birches, and 2 yellow birches) and 17 coniferous (2 eastern hemlocks, 11 red pines, and 4 white pines) subject tree species. There were two different available LiDAR datasets from the same area that were collected in 2011 and 2017. Height measurements were done at 96% and 97% accuracy for hardwood and softwood tree species, respectively.

Several other tree variables derived from LiDAR point cloud were used to estimate DBH by using regression analysis for both 2017 and 2011 datasets. Estimation equations were tested on the other dataset. The best-fitted formula was 2017’s, with 0.55 adjusted R² and less than 0.0001 p-values on 2017 LiDAR data while 0.42 adjusted R² and less than 0.0001 p-values on 2011’s dataset. Some additional analysis that includes calculating PRMSE (Predicted Root Mean Square Error), BIAS (Mean Error), and MAD (Mean Absolute Difference) have been applied. The equation that was generated by using data from 2017 has –0.57 BIAS for Hardwood and 1.13 BIAS for softwood. That result indicates that the equation has –0.57 centimeters (cm) estimation error for hardwood and 1.13 cm for softwood on DBH estimations.

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Teterukovskiy, Alexei. "Computational statistics with environmental and remote sensing applications /." Umeå : Dept. of Forest Economics, Swedish Univ. of Agricultural Sciences, 2003. http://epsilon.slu.se/s277.pdf.

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Valero, Pérez Mario Miguel. "Infrared image processing tools for automated aerial remote sensing of active wildland fires." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/671010.

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Forest fires are natural phenomena essential for ecosystem balance. However, their impact on society is increasing. Emergency managers are facing unprecedented crises producing massive evacuations, numerous casualties and economic losses in the order of billions of dollars. At the same time, fire scientists around the world are struggling to improve our understanding of wildfire dynamics, which is incomplete at present. Extensive large-scale experimental campaigns have been designed, funded and implemented in recent years to study fire behaviour. Furthermore, operational fire spread simulators have been revisited to improve their accuracy when working .in real time. A very promising approach to do so is data assimilation, which relies on fire monitoring. In this context, there is a strong need for accurate detailed information about wildfire behaviour, with a triple goal: firstly, to improve the understanding of fire dynamics; secondly, to assist evacuation and firefighting tasks if such data can be acquired and provided in real time during a fire emergency; thirdly, to support modelling efforts including the specific case of data-driven fire spread simulators Remote sensing techniques have shown a great potential to monitor wildland fires. Thermal infrared (TIR) cameras allow a clear view of the fire, in most conditions even in the presence of heavy smoke. Furthermore, modern TIR cameras are light, compact and affordable and they can be installed aboard Unmanned and Remotely Piloted Aircraft (UAS and RPAS, respectively), which facilitates sensor deployment while drastically reducing cost and risk. These conditions have spurred an interest in the use of airborne thermal infrared imaging to measure fire behaviour metrics with high temporal and spatial resolution. However, the analysis of TIR imagery has so far been mostly manual and often only qualitative. When quantitative results have been obtained, they have usually been computed analysing individually a subset of video frames. This methodology entails two important limitations. Firstly, image analysis is slow and it cannot be performed in real time. Secondly, measured values of fire behaviour metrics are averaged both in time and space, with a significant portion of the acquired information never being used. This Thesis contributes to the automation of active wildfire monitoring. It presents a number of image processing algorithms that assist in the analysis of aerial thermal infrared imagery. After a thorough review of the current state of the art, highest priority needs were identified (chapter 1). Detected needs include video stabilization, fire perimeter tracking and the estimation of spatially explicit fire rates of spread (ROS). Image registration and video stabilization are essential to georeference aerial imagery, which must be performed before any further analysis. Automated fire perimeter tracking has a great applicability for tactical emergency management and it allows ROS estimation Finally, ROS can be used to derive additional fire behaviour metrics such as fire fine intensity and it can be fed into data-driven simulators to improve operational fire spread forecast. Algorithms for IR tire image segmentation, fire line detection and fire perimeter tracking are presented in chapters 2 and 3, whereas image registration and video stabilization are dealt with in chapters 4 and 5. Additionally, chapter 6 describes a number of tools developed to overcome practical limitations of modern compact IR cameras. Afterwards, chapter 7 provides a demonstration of the use of developed algorithms in two independent datasets. Finally, chapter 8 describes the integration of the software developed in this Thesis with third-party tools. External software necessary for the study of wildfire behaviour includes Geographic Information Systems (GIS), fire models based on Computational Fluid Dynamics (CFD) and data-driven fire spread simulators that incorporate data assimilation.
Los incendios forestales son un fenómeno natural, esencial para la conservación de una gran cantidad de ecosistemas. Sin embargo, su impacto social ha aumentado considerablemente en los últimos años. La ocurrencia de incendios cerca de asentamientos humanos ha dado lugar recientemente a importantes desastres con evacuaciones masivas, numerosas víctimas mortales y pérdidas económicas multimillonarias. Mientras los equipos de gestión de emergencias buscan nuevas herramientas para hacer frente a estas situaciones, la comunidad científica trata de mejorar el conocimiento disponible sobre el comportamiento del fuego. En este contexto, crece la necesidad de obtener información fiable y detallada sobre el comportamiento de los incendios forestales a escala real. Dicha información tiene tres aplicaciones principales: en primer lugar, permite el estudio científico de la dinámica del fuego; en segundo lugar, refuerza la percepción de la situación durante una emergencia y ayuda en la toma de decisiones; en tercer lugar, puede ser utilizada por simuladores basados en la asimilación de datos para mejorar la predicción de la propagación del fuego. La primera aplicación requiere información con gran resolución espacial y temporal, así como una metodología de análisis sistemática que permita relacionar las variables de dinámica del fuego con las propiedades del combustible, el terreno y las condiciones meteorológicas. Además, las aplicaciones durante un escenario de emergencia requieren información en tiempo real. Las técnicas de teledetección han demostrado tener un gran potencial para monitorizar incendios forestales. En concreto, las cámaras de termografía infrarroja instaladas en plataformas aéreas permiten obtener una visión clara del fuego incluso en presencia de humo. Además, estas cámaras han sufrido un desarrollo considerable con diseños cada vez más compactos, ligeros y económicos que permiten su instalación en vehículos aéreos no tripulados (UAVs), reduciendo costes y riesgo para el personal que las opera. Estas circunstancias han favorecido el uso de cámaras termográficas aerotransportadas en campañas experimentales a mediana y gran escala, y sugieren una importante aplicabilidad en incendios forestales no controlados. No obstante, el análisis de las imágenes adquiridas se realiza de forma manual, a menudo únicamente cualitativa. Cuando se obtienen resultados cuantitativos sobre el comportamiento del fuego, su resolución tanto espacial como temporal queda limitada por la imposibilidad de procesar toda la información disponible. Además, la metodología manual imposibilita el procesamiento de datos en tiempo real. Con el fin de facilitar el estudio del comportamiento de incendios forestales mediante técnicas de teledetección, esta tesis propone una serie de algoritmos de procesamiento de imagen infrarroja. Un análisis bibliográfico inicial (capítulo 1) permitió identificar las principales necesidades existentes, que incluyen el registro de imágenes, la estabilización de vídeo, la detección de las líneas de fuego activas y la medición de la velocidad de propagación del incendio. Todos estos aspectos son tratados en los capítulos 2, 3, 4 y 5 de esta tesis. A continuación, el capítulo 6 añade una serie de soluciones prácticas diseñadas para solventar limitaciones existentes en el uso de cámaras termográficas compactas. El capítulo 7 incluye una demostración del uso combinado de los algoritmos propuestos. Por último. el capítulo 8 describe la integración del software desarrollado con otros programas existentes que resultan de utilidad en el estudio de incendios forestales. Entre los programas externos de interés se encuentran los Sistemas de Información Geográfica (SIG), los simuladores basados en dinámica de fluidos computacional (CFD) y los simuladores de propagación de incendios que incorporan asimilación de datos.

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Di, Long. "Cognitive Formation Flight in Multi-Unmanned Aerial Vehicle-Based Personal Remote Sensing Systems." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/985.

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This work introduces a design and implementation of using multiple unmanned aerial vehicles (UAVs) to achieve cooperative formation flight based on the personal remote sensing platforms developed by the author and the colleagues in the Center for Self-Organizing and Intelligent Systems (CSOIS). The main research objective is to simulate the multiple UAV system, design a multi-agent controller to achieve simulated formation flight with formation reconfiguration and real-time controller tuning functions, implement the control system on actual UAV platforms and demonstrate the control strategy and various formation scenarios in practical flight tests. Research combines analysis on flight control stabilities, develop- ment of a low-cost UAV testbed, mission planning and trajectory tracking, multiple sensor fusion research for UAV attitude estimations, low-cost inertial measurement unit (IMU) evaluation studies, AggieAir remote sensing platform and fail-safe feature development, al- titude controller design for vertical take-off and landing (VTOL) aircraft, and calibration and implementation of an air pressure sensor for wind profiling purposes on the developed multi-UAV platform. Definitions of the research topics and the plans are also addressed.

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Jensen, Austin M. "Innovative Payloads for Small Unmanned Aerial System-Based Personal Remote Sensing and Applications." DigitalCommons@USU, 2014. https://digitalcommons.usu.edu/etd/2192.

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Remote sensing enables the acquisition of large amounts of data, over a small period of time, in support of many ecological applications (i.e. precision agriculture, vegetation mapping, etc.) commonly from satellite or manned aircraft platforms. This dissertation focuses on using small unmanned aerial systems (UAS) as a remote sensing platform to collect aerial imagery from commercial-grade cameras and as a radio localization platform to track radio-tagged sh. The small, low-cost nature of small UAS enables remotely sensed data to be captured at a lower cost, higher spatial and temporal resolution, and in a more timely manner than conventional platforms. However, these same attributes limit the types of cameras and sensors that can be used on small UAS and introduce challenges in calibrating the imagery and converting it into actionable information for end users. A major contribution of this dissertation addresses this issue and includes a complete description on how to calibrate imagery from commercial-grade visual, near-infrared, and thermal cameras. This includes the presentation of novel surface temperature sampling methods, which can be used during the ight, to help calibrate thermal imagery. Landsat imagery is used to help evaluate these methods for accuracy; one of the methods performs very well and is logistically feasible for regular use. Another major contribution of this dissertation includes novel, simple methods to estimate the location of radio-tagged sh using multiple unmanned aircraft (UA). A simulation is created to test these methods, and Monte Carlo analysis is used to predict their performance in real-world scenarios. This analysis shows that the methods are able to locate the radio-tagged sh with good accuracy. When multiple UAs are used, the accuracy does not improve; however the sh is located much quicker than when one UA is used.

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ioannidis, ioannis. "Unmanned Aerial Vehicles and remote sensing in search and rescue missions in Sweden." Thesis, KTH, Fastigheter och byggande, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-266775.

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This paper gives a thοrοugh lοοk in the use οf Unmanned Aerial Vehicles (UAV) in search and rescue missiοns. The οbjective is tο identify, thrοugh a literature review, all types οf UAV, the available remοte sensοrs that can be mοunted in a UAV and what type οf data each sensοr prοvides, the methοdοlοgy οn flight planning and what is the regulatοry framewοrk, guidelines and limitatiοns, οf UAV flight in sοme οf the biggest cοuntries wοrldwide and in specific fοr the Eurοpean Uniοn and Sweden. Alsο, a brief research in the field οf machine learning was dοne in οrder tο identify the pοssibilities given in use οf οbject recοgnitiοn and avοidance techniques. In the case οf Sweden, we have alsο identified the framewοrk fοr the Search and Rescue οperatiοns accοrding tο the “Civil Prοtectiοn Act. Gοvernment Bill 2002/03:119. Refοrmed rescue services legislatiοn”, in whοse hands falls the respοnsibility tο use and implement UAVs in such type οf missiοns. The main οbjectives fοr future develοpment are the full autοnοmy οf a UAV, the energy limitatiοns in the οperatiοnal phase, the fast prοcessing οf data οnbοard and the acquisitiοn οf the data thrοugh cοmmunicatiοn links withοut the need οf a physical cοnnectiοn between the UAV and the grοund cοntrοl statiοn (GCS). Accοrding tο οur research the οptimal cοnfiguratiοn οf UAVs in a search and rescue scenariο is a fleet οf fully autοnοmοus heterοgeneοus UAVs (fixed-wing UAVs and quadcοpters) with sοlar panels attached tο the fixed-wing UAVs, a high-resοlutiοn camera, a thermal camera and a Synthetic Aperture Radar (SAR). As the field οf UAVs is vastly grοwing the research οn the subject was cοnducted until April 1st, 2018 due tο new papers and research cοnducted in the subject regularly.

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Noonan, Andrea L. "Flight plan generation for unmanned aerial vehicles." Thesis, Manhattan, Kan. : Kansas State University, 2007. http://hdl.handle.net/2097/385.

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Koc, Ayten. "Remote Sensing Study Of Surgu Fault Zone." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606611/index.pdf.

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The geometry, deformation mechanism and kinematics of the Sü
rgü
Fault Zone is investigated by using remotely sensed data including Landsat TM and ASTER imagery combined with SRTM, and stereo-aerial photographs. They are used to extract information related to regional lineaments and tectono-morphological characteristics of the SFZ. Various image processing and enhancement techniques including contrast enhancement, PCA, DS and color composites are applied on the imagery and three different approaches including manual, semi automatic and automatic lineament extraction methods are followed. Then the lineaments obtained from ASTER and Landsat imagery using manual and automatic methods are overlaid to produce a final lineaments map. The results have indicated that, the total number and length of the lineaments obtained from automatic is more than other methods while the percentages of overlapping lineaments for the manual method is more than the automatic method which indicate that the lineaments from automatic method does not discriminate man made features which result more lineaments and less overlapping ratio with respect to final map. It is revealed from the detail analysis that, the SFZ displays characteristic deformation patterns of strike-slip faults, such as pressure ridges, linear fault controlled valleys, deflected stream courses, rotated blocks and juxtaposition of stratigraphical horizons in macroscopic scale. In addition to these, kinematic analyses carried out using fault slip data indicated that the Sü
rgü
Fault Zone is dextral strike-slip fault zone with a reverse component of slip and cumulative displacement along the fault is more than 2 km.

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Aqdus, Syed Ali. "Airborne multispectral and hyperspectral remote sensing techniques in archaeology a comparative study /." Thesis, Thesis restricted. Connect to e-thesis to view abstract, 2009. http://theses.gla.ac.uk/812/.

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Thesis (Ph.D.) - University of Glasgow, 2009.
Ph.D. thesis submitted to the Faculty of Physical Sciences, Department of Geographical and Earth Sciences and the Faculty of Arts, Department of Archaeology, University of Glasgow, 2009. Includes bibliographical references. Print version also available.

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Guerra, Hernández Juan. "Applicability of advanced remote sensing technologies to support forest management." Doctoral thesis, ISA/UL, 2018. http://hdl.handle.net/10400.5/17507.

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Tese de Doutoramento - Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia
Forest ecosystems provide multiple wood and non-wood forest products and services that are crucial for the socio-economic development of rural areas. In this context, current methods of estimating variables of interest in forest ecosystems should be improved due to new demands for information related to sustainable forest management. Advanced remote sensing (RS) technologies provide data that will address the increasing demands for information and support the subsequent development of prediction models. Airborne laser scanning (ALS) has emerged as one of the most promising RS technologies for characterizing tree canopies and other biophysical characteristics essential for forest inventories. The use of 3D data acquired from Digital Aerial photography (DAP) is a useful alternative to ALS-based forest variable estimation. The rapid development of Unmanned Aerial Vehicles (UAVs) (drones) fitted with digital aerial cameras and the use of SfM (Structure from Motion) techniques together provide new possibilities for efficient mapping of forest variables. Combining ALS and DAP technologies with UAV platforms will probably have a strong impact on forest inventory practices in the next decade, leading to more accurate characterization of forest stands, as well as for monitoring forest growth. The overall aim of all of the five studies included in this doctoral thesis is to evaluate the capacity of two advanced RS technologies (ALS and DAP) to provide methods and tools that support forest management at different scales ranging from stand level to individual tree level
N/A

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Swetnam, Tyson L. "Cordilleran forest scaling dynamics and disturbance regimes quantified by aerial lidar." Thesis, The University of Arizona, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3605921.

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Semi-arid forests are in a period of rapid transition as a result of unprecedented landscape scale fires, insect outbreaks, drought, and anthropogenic land use practices. Understanding how historically episodic disturbances led to coherent forest structural and spatial patterns that promoted resilience and resistance is a critical part of addressing change. Here my coauthors and I apply metabolic scaling theory (MST) to examine scaling behavior and structural patterns of semi-arid conifer forests in Arizona and New Mexico. We conceptualize a linkage to mechanistic drivers of forest assembly that incorporates the effects of low-intensity disturbance, and physiologic and resource limitations as an extension of MST. We use both aerial LiDAR data and field observations to quantify changes in forest structure from the sub-meter to landscape scales. We found: (1) semi-arid forest structure exhibits MST-predicted behaviors regardless of disturbance and that MST can help to quantitatively measure the level of disturbance intensity in a forest, (2) the application of a power law to a forest overstory frequency distribution can help predict understory presence/absence, (3) local indicators of spatial association can help to define first order effects (e.g. topographic changes) and map where recent disturbances (e.g. logging and fire) have altered forest structure. Lastly, we produced a comprehensive set of above-ground biomass and carbon models for five distinct forest types and ten common species of the southwestern US that are meant for use in aerial LiDAR forest inventory projects. This dissertation presents both a conceptual framework and applications for investigating local scales (stands of trees) up to entire ecosystems for diagnosis of current carbon balances, levels of departure from historical norms, and ecological stability. These tools and models will become more important as we prepare our ecosystems for a future characterized by increased climatic variability with an associated increase in frequency and severity of ecological disturbances.

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Jensen, Austin M. "gRAID: A Geospatial Real-Time Aerial Image Display for a Low-Cost Autonomous Multispectral Remote Sensing." DigitalCommons@USU, 2009. https://digitalcommons.usu.edu/etd/497.

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Remote sensing helps many applications like precision irrigation, habitat mapping, and traffic monitoring. However, due to shortcomings of current remote sensing platforms - like high cost, low spatial, and temporal resolution - many applications do not have access to useful remote sensing data. A team at the Center for Self-Organizing and Intelligent Systems (CSOIS) together with the Utah Water Research Laboratory (UWRL) at Utah State University has been developing a new remote sensing platform to deal with these shortcomings in order to give more applications access to remote sensing data. This platform (AggieAir) is low cost, fully autonomous, easy to use, independent of a runway, has a fast turnover time, and a high spatial resolution. A program called the Geospatial Real-Time Aerial Image Display (gRAID) has also been developed to process the images taken from AggieAir. gRAID is able to correct the camera lens distortion, georeference, and display the images on a 3D globe, and export them in a conventional Geographic Information System (GIS) format for further processing. AggieAir and gRAID prove to be innovative and useful tools for remote sensing.

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Sahar, Liora. "Using remote-sensing and gis technology for automated building extraction." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/37231.

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Extraction of buildings from remote sensing sources is an important GIS application and has been the subject of extensive research over the last three decades. An accurate building inventory is required for applications such as GIS database maintenance and revision; impervious surfaces mapping; storm water management; hazard mitigation and risk assessment. Despite all the progress within the fields of photogrammetry and image processing, the problem of automated feature extraction is still unresolved. A methodology for automatic building extraction that integrates remote sensing sources and GIS data was proposed. The methodology consists of a series of image processing and spatial analysis techniques. It incorporates initial simplification procedure and multiple feature analysis components. The extraction process was implemented and tested on three distinct types of buildings including commercial, residential and high-rise. Aerial imagery and GIS data from Shelby County, Tennessee were identified for the testing and validation of the results. The contribution of each component to the overall methodology was quantitatively evaluated as relates to each type of building. The automatic process was compared to manual building extraction and provided means to alleviate the manual procedure effort. A separate module was implemented to identify the 2D shape of a building. Indices for two specific shapes were developed based on the moment theory. The indices were tested and evaluated on multiple feature segments and proved to be successful. The research identifies the successful building extraction scenarios as well as the challenges, difficulties and drawbacks of the process. Recommendations are provided based on the testing and evaluation for future extraction projects.

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Scott, Kevon K. "Occlusion-Aware Sensing and Coverage in Unmanned Aerial Vehicle (UAV) Networks." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1479816954496473.

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Jaafar, Jasmee. "An evaluation of the generation and potential applications of digital surface models." Thesis, University of Nottingham, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326567.

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Wijesingha, Jayan Sri Jeewantha [Verfasser]. "Fine-scale grassland monitoring using unmanned aerial vehicle borne remote sensing / Jayan Sri Jeewantha Wijesingha." Kassel : Universitätsbibliothek Kassel, 2020. http://d-nb.info/1209713527/34.

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Wijesingha, Jayan [Verfasser]. "Fine-scale grassland monitoring using unmanned aerial vehicle borne remote sensing / Jayan Sri Jeewantha Wijesingha." Kassel : Universitätsbibliothek Kassel, 2020. http://d-nb.info/1209713527/34.

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Holmström, Hampus. "Data acquisition for forestry planning by remote sensing based sample plot imputation /." Umeå : Swedish Univ. of Agricultural Sciences (Sveriges lantbruksuniv.), 2001. http://epsilon.slu.se/avh/2001/91-576-6086-7.pdf.

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Thompson, James. "Identifying Subsurface Tile Drainage Systems Utilizing Remote Sensing Techniques." University of Toledo / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1290141705.

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Teasdale, Gregg N. "Satellite and aerial imaging in characterization, hydrologic analysis and modeling of inland watersheds and streams." Online access for everyone, 2005. http://www.dissertations.wsu.edu/Dissertations/Fall2005/G%5FTeasdale%5F090205.pdf.

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Park, Keith Marron. "The global-to-local search method: A systematic search procedure that uses the context of the textured layout to locate and detect low-contrast targets in aerial images." CSUSB ScholarWorks, 1993. https://scholarworks.lib.csusb.edu/etd-project/700.

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35

Coopmans, Calvin. "Architecture, Inertial Navigation, and Payload Designs for Low-Cost Unmanned Aerial Vehicle-Based Personal Remote Sensing." DigitalCommons@USU, 2010. https://digitalcommons.usu.edu/etd/692.

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This thesis presents work done towards a Personal Remote Sensing (PRS) system: small Unmanned Aerial Vehicles (UAVs) with electronic, control, and sensing subsystems. Based on papers presented to conferences (AutoTestCon2008 and MESA2009), as well as other work on PRS, multiple levels of engineering are detailed: complex multi-UAV data flow; attitude estimation filters; real-time microprocessor functionality; and small, mobile power systems. Wherever possible, Open-Source tools and designs have been used, modified, or studied, providing excellent cost to performance ratios in most cases. First, the overall PRS UAV architecture, AggieAir, is presented with a motivating examples (GhostEye and EagleEye camera payloads). Then, AggieNav, an inertial navigation system for small UAVs, is detailed, along with information about a Kalman filter for estimation of UAV navigation, position, and attitude. Finally the Spatial Environment Autonomous Logger (SEAL), a general-purpose wireless datalogger for small UAV applications, is presented, with application examples with and without small UAVs. This work represents designs based on two years of organic small UAV system growth, and provides integrated solutions to many problems of small UAV communication, sensing, and control.

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Anishchenko, Ilya. "Design, Development, and Validation of a High-Performance Tilt-Frame Unmanned Aerial System for Landing in Tree Orchards." Thesis, University of California, Davis, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10749568.

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Huanglongbing (HLB) is an incurable bacterial disease that kills citrus trees and threatens to decimate California's $2.2 billion citrus industry. A solution for limiting the spread of HLB is to rapidly detect infected trees with a chemical sensor equipped Unmanned Aerial System (UAS), which lands within tree proximity and deploys an extendable boom for air-sample collection. The Agricultural UAS project is a multidisciplinary engineering effort to conduct chemical sample collection and analysis in remote locations, to study a tilt-frame UAS concept performance, and to test a novel Propeller Thrust Governing System (PTGS). Simulated flight metrics show that a tilt-frame UAS concept significantly increases endurance, range, cruising performance, and service envelope over a conventional multi-rotor UAS design. A UAS prototype has been built by integrating the following subsystems: tilt-frame aircraft design, PTGS, and an attitude control system. The PTGS is a novel subsystem designed for regulating thrust of a constant velocity, non-variable pitch propeller through the use of actuated aerodynamic surfaces (flaps) for vehicle attitude control. Experiments conducted on a custom-built force measuring platform show that a standard/inverted flap combination produces a high force-to-flap deflection angle ratio, preserves a linear response, and minimizes coupling between downwards/sideways forces. An attitude controller was designed using a cascade PID scheme with a Mahony filter for rapid attitude estimation. By modeling system dynamics and using airfoil theory, predicted dynamic response and simulated flight metrics are generated and then experimentally validated with a functional prototype vehicle. Collected flight data deviates from predicted performance by less than 5%.

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Kendler, Johnathan M. "Evaluating methods for implementing photogrammetric sensor platforms with various Lidar components for use with close and mid-range particle detection systems." abstract and full text PDF (UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1460763.

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Potter, Thomas Noel 1959. "The use of multispectral aerial video to determine land cover for hydrological simulations in small urban watersheds." Thesis, The University of Arizona, 1993. http://hdl.handle.net/10150/291381.

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Airborne multispectral video was evaluated as a tool for obtaining urban land cover information for hydrological simulations. Land cover data was obtained for a small urban watershed in Tucson, Arizona using four methods: multispectral aerial video (2 meter and 4 meter pixel resolution), National High Altitude Photography (NHAP), multispectral satellite imagery from Systeme Pour l'Observation de la Terre (SPOT), and by conventional survey. A semi-automated land cover classification produced four classes: vegetation, buildings, pavement, and bare soil. The land cover data from each classification was used as input to a runoff simulation model. Runoff values generate by each simulation were compared to observed runoff. A chi-square goodness-of-fit test indicated that SPOT produced landcover data most similar to the conventional classification. In the curve number model, the SPOT data produced simulated runoff values most similar to observed runoff.

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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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40

Henderson, Caleb Aleksandr. "Identification of Disease Stress in Turfgrass Canopies Using Thermal Imagery and Automated Aerial Image Analysis." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/103621.

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Remote sensing techniques are important for detecting disease within the turfgrass canopy. Herein, we look at two such techniques to assess their viability in detecting and isolating turfgrass diseases. First, thermal imagery is used to detect differences in canopy temperature associated with the onset of brown patch infection in tall fescue. Sixty-four newly seeded stands of tall fescue were arranged in a randomized block design with two runs with eight blocks each containing four inoculum concentrations within a greenhouse. Daily measurements were taken of the canopy and ambient temperature with a thermal camera. After five consecutive days differences were detected in canopy – ambient temperature in both runs (p=0.0015), which continued for the remainder of the experiment. Moreover, analysis of true colour imagery during this time yielded no significant differences between groups. A field study comparing canopy temperature of adjacent symptomatic and asymptomatic tall fescue and creeping bentgrass canopies showed differences as well (p<0.0492). The second project attempted to isolate spring dead spot from aerial imagery of bermudagrass golf course fairways using a Python script. Aerial images from unmanned aerial vehicle flights were collected from four fairways at Nicklaus Course of Bay Creek Resort in Cape Charles, VA. Accuracy of the code was measured by creating buffer zones around code generated points and measuring how many disease centers measured by hand were eclipsed. Accuracies measured as high as 97% while reducing coverage of the fairway by over 30% compared to broadcast applications. Point density maps of the hand and code points also appeared similar. These data provide evidence for new opportunities in remote turfgrass disease detection.
Master of Science in Life Sciences
Turfgrasses are ubiquitous, from home lawns to sports fields, where they are used for their durability and aesthetics. Disease within the turfgrass canopy can ruin these aspects of the turfgrass reducing its overall quality. This makes detection and management of disease within the canopy an important part of maintaining turfgrass. Here we look at the effectiveness of imaging techniques in detecting and isolating disease within cool-season and warm-season turfgrasses. We test the capacity for thermal imagery to detect the infection of tall fescue (Festuca arundenacea) with Rhizoctonia solani, the causal agent of brown patch. In greenhouse experiments, differences were detected in normalized canopy temperature between differing inoculation levels at five days post inoculation, and in field conditions we were able to observe differences in canopy temperature between adjacent symptomatic and non-symptomatic stands. We also developed a Python script to automatically identify and record the location of spring dead spot damage within mosaicked images of bermudagrass golf fairways captured via unmanned aerial vehicle. The developed script primarily used Hough transform to mark the circular patches within the fairway and recorded the GPS coordinates of each disease center. When compared to disease incidence maps created manually the script was able to achieve accuracies as high as 97% while reducing coverage of the fairway by over 30% compared to broadcast applications. Point density maps created from points in the code appeared to match those created manually. Both findings have the potential to be used as tools to help turfgrass managers.

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Johnson, Ryan L., and University of Lethbridge Faculty of Arts and Science. "Airborne remote sensing of forest leaf area index in mountainous terrain." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2000, 2000. http://hdl.handle.net/10133/90.

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Leaf area index (LAI) provides forestry information that is important for regional scale ecological models and in studies of global change. This research examines the effects of mountainous terrain on the radiometric properties of multispectral CASI imagery in estimating ground-based optical measurements of LAI, obtained using the TRAC and LAI- 2000 systems. Field and image data were acquired summer 1998 in Kananaskis, Alberta, Canada. To account for the influence of terrain a new modified approach using the Li and Strahler Geometric Optical Mutual Shadowing (GOMS) model in 'multiple forward mode' (MFM) was developed. This new methodology was evaluated against four traditional radiometric corrections used in comination with spectral mixture analysis (SMA) and NDVI. The MFM approach provided the best overall predictions of LAI measured with ground-based optical instruments, followed by terrain normalized SMA, SMA without terrain normalization and NDVI.
xiv, 151 leaves : ill. (some col.), map ; 29 cm.

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Suiter, Ashley E. "REMOTE SENSING BASED DETECTION OF FORESTED WETLANDS: AN EVALUATION OF LIDAR, AERIAL IMAGERY, AND THEIR DATA FUSION." OpenSIUC, 2015. https://opensiuc.lib.siu.edu/theses/1636.

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Multi-spectral imagery provides a robust and low-cost dataset for assessing wetland extent and quality over broad regions and is frequently used for wetland inventories. However in forested wetlands, hydrology is obscured by tree canopy making it difficult to detect with multi-spectral imagery alone. Because of this, classification of forested wetlands often includes greater errors than that of other wetlands types. Elevation and terrain derivatives have been shown to be useful for modelling wetland hydrology. But, few studies have addressed the use of LiDAR intensity data detecting hydrology in forested wetlands. Due the tendency of LiDAR signal to be attenuated by water, this research proposed the fusion of LiDAR intensity data with LiDAR elevation, terrain data, and aerial imagery, for the detection of forested wetland hydrology. We examined the utility of LiDAR intensity data and determined whether the fusion of Lidar derived data with multispectral imagery increased the accuracy of forested wetland classification compared with a classification performed with only multi-spectral image. Four classifications were performed: Classification A - All Imagery, Classification B - All LiDAR, Classification C - LiDAR without Intensity, and Classification D - Fusion of All Data. These classifications were performed using random forest and each resulted in a 3-foot resolution thematic raster of forested upland and forested wetland locations in Vermilion County, Illinois. The accuracies of these classifications were compared using Kappa Coefficient of Agreement. Importance statistics produced within the random forest classifier were evaluated in order to understand the contribution of individual datasets. Classification D, which used the fusion of LiDAR and multi-spectral imagery as input variables, had moderate to strong agreement between reference data and classification results. It was found that Classification A performed using all the LiDAR data and its derivatives (intensity, elevation, slope, aspect, curvatures, and Topographic Wetness Index) was the most accurate classification with Kappa: 78.04%, indicating moderate to strong agreement. However, Classification C, performed with LiDAR derivative without intensity data had less agreement than would be expected by chance, indicating that LiDAR contributed significantly to the accuracy of Classification B.

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Han, Yiding. "An Autonomous Unmanned Aerial Vehicle-Based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications." DigitalCommons@USU, 2009. https://digitalcommons.usu.edu/etd/513.

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This work concentrates on the topic of remote sensing using a multispectral imag-ing system for water management and agriculture applications. The platform, which is alight-weight inexpensive runway-free unmanned aerial vehicle (UAV), namely, AggieAir, ispresented initially. A major portion of this work focuses on the development of a light-weight multispectral imager payload for the AggieAir platform, called GhostFoto. Theimager is band-recongurable, covering both visual red, green, and blue (RGB) and nearinfrared (NIR) spectrum, and interfaced with UAV on-board computer. The developmentof the image processing techniques, which are based on the collected multispectral aerialimages, is also presented in this work. One application is to perform fully autonomous rivertracking for applications such as river water management. Simulation based on aerial mul-tispectral images is done to demonstrate the feasibility of the developed algorithm. Othereort is made to create a systematic method to generate normalized difference vegetationindex (NDVI) using the airborne imagery. The GhostFoto multispectral imaging systembased on AggieAir architecture is proven to be an innovative and useful tool.

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Haghighattalab, Atena. "High-throughput phenotyping of large wheat breeding nurseries using unmanned aerial system, remote sensing and GIS techniques." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/34486.

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Doctor of Philosophy
Department of Geography
Douglas G. Goodin
Jesse A. Poland
Kevin Price
Wheat breeders are in a race for genetic gain to secure the future nutritional needs of a growing population. Multiple barriers exist in the acceleration of crop improvement. Emerging technologies are reducing these obstacles. Advances in genotyping technologies have significantly decreased the cost of characterizing the genetic make-up of candidate breeding lines. However, this is just part of the equation. Field-based phenotyping informs a breeder’s decision as to which lines move forward in the breeding cycle. This has long been the most expensive and time-consuming, though most critical, aspect of breeding. The grand challenge remains in connecting genetic variants to observed phenotypes followed by predicting phenotypes based on the genetic composition of lines or cultivars. In this context, the current study was undertaken to investigate the utility of UAS in assessment field trials in wheat breeding programs. The major objective was to integrate remotely sensed data with geospatial analysis for high throughput phenotyping of large wheat breeding nurseries. The initial step was to develop and validate a semi-automated high-throughput phenotyping pipeline using a low-cost UAS and NIR camera, image processing, and radiometric calibration to build orthomosaic imagery and 3D models. The relationship between plot-level data (vegetation indices and height) extracted from UAS imagery and manual measurements were examined and found to have a high correlation. Data derived from UAS imagery performed as well as manual measurements while exponentially increasing the amount of data available. The high-resolution, high-temporal HTP data extracted from this pipeline offered the opportunity to develop a within season grain yield prediction model. Due to the variety in genotypes and environmental conditions, breeding trials are inherently spatial in nature and vary non-randomly across the field. This makes geographically weighted regression models a good choice as a geospatial prediction model. Finally, with the addition of georeferenced and spatial data integral in HTP and imagery, we were able to reduce the environmental effect from the data and increase the accuracy of UAS plot-level data. The models developed through this research, when combined with genotyping technologies, increase the volume, accuracy, and reliability of phenotypic data to better inform breeder selections. This increased accuracy with evaluating and predicting grain yield will help breeders to rapidly identify and advance the most promising candidate wheat varieties.

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Browning, Dawn M. "Woody Plant Dynamics in a Sonoran Desert Ecosystem across Scales: Remote Sensing and Field Perspectives." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/195333.

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Historic land uses impose discernable legacy effects that may influence ecosystem function, a concern of particular importance in actively managed landscapes. In recent history (ca. 150 years) tree and shrub abundance has increased at the expense of native grasses in savannas and grasslands. The magnitude and patterns of change are spatially heterogeneous, highlighting the need for analytical approaches spanning multiple spatial scales, from individual plants to patches to landscapes. The overarching goal of this dissertation was to explore long-term dynamics associated with woody plant encroachment with aerial photography and field studies to examine cover, density, soils and land use history at the Santa Rita Experimental Range.The first study characterized patterns in woody cover change on contrasting soils over 60 years using aerial photography. Woody patch dynamics revealed encroachment and stabilization phases in woody plant proliferation. Soil properties reflected the rate at which uplands reached a dynamic equilibrium, but not the endpoint (ca. 35% cover). Fluctuations around dynamic equilibrium reflected net change in patch growth and acquiescence combined with colonization and mortality. Efforts to characterize changes in land cover will require patch-based assessments beyond coarse estimates of percent cover.The second study capitalized on historic field measurements of shrub canopies to validate estimates of shrub cover derived from the earliest aerial photography, quantified detection limitations of 1936 aerial photographs for mapping shrub cover, assessed species-specific contributions to percent cover, and translated detection limitations to proportions of velvet mesquite (Prosopis velutina var Woot.) biomass missed with 1930s aerial photography.The third study was a field-based approach investigating how livestock grazing influenced mesquite cover, density, biomass, and stand structure over 74 years. The study supplemented traditional statistical analysis of grazing effects with methods quantifying spatial autocorrelation structure of mesquite density by grazing treatment. The outcome re-affirmed the supposition that mesquite cover may be dynamically stable at ca 30%, and revealed that livestock grazing slowed the shrub encroachment process from 1932 to 2006, counter to expectation. Results indicate that shrub growth trajectories persist long-term. Overall, this work affirms the importance of land use legacies and long-term perspectives in rangeland shrub dynamics.

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Liu, Yang. "Remote Sensing of Forest Structural Changes due to Shale Gas Extraction in Muskingum Watershed." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535703702856946.

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Erikson, Mats. "Segmentation and classification of individual tree crowns : in high spatial resolution aerial images /." Uppsala : Centre for Image Analysis, Swedish Univ. of Agricultural Sciences, 2004. http://epsilon.slu.se/s320.pdf.

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Niu, Xutong. "Highway extraction from high resolution aerial photography using a geometric active contour model." The Ohio State University, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=osu1101833084.

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Metzler, Jacob W. "Use of Multi-temporal IKONOS and LANDSAT ETM+ Satellite Imagery to Determine Forest Stand Conditions in Northern Maine." Fogler Library, University of Maine, 2004. http://www.library.umaine.edu/theses/pdf/MetzlerJW2004.pdf.

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Magnusson, Mattias. "Evaluation of remote sensing techniques for estimation of forest variables at stand level /." Umeå : Dept. of Forest Resource Management and Geomatics, Swedish University of Agricultural Sciences, 2006. http://epsilon.slu.se/200685.pdf.

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Dissertations / Theses on the topic 'Aerial videography Remote sensing'

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