Integration Of Multispectral Camera Systems For Enhanced Visualization Biological Studies Using UAS

The purpose of this research is to enhance visualization of warm-blooded animals and analyze the vegetation in which they are located using a camera system mounted on Unmanned Aircraft System (UAS). The results are coherently displayed in a single image at the same spatial location so that biologists will have accurate animal counts along with vegetation conditions. Application of aerial imagery has been used to analyze the vegetation health and determining the number of the animals by the wildlife service. However, a major obstacle of the research is to combine the two imaging systems to obtain the same spatial image with enhanced visualization. The two camera systems used in this research are the Tetracam ADC lite multispectral and the FLIR Photon 320 infrared camera. These two camera systems each have a different lens, field of view and sensor array size. The project involves the alignment of the two cameras to pixel level for the spectral image analysis. The spectral image analysis provides both vegetation information, such as Normalized Difference Vegetation Index (NDVI), along with enhanced visualization of warm-blooded targets. The system was miniaturized for the standalone payload for aerospace applications including UAS. The FLIR Photon 320 was used to capture the infrared image and a Tetracam ADC lite multispectral camera was used to capture the near infrared, red and green spectral band images. A laboratory experimental setup was designed to mechanically align the two camera systems to get close identical spatial imagery. Spatial registration of the two images was performed using reverse image warping method by finding affine transformation matrix using point correspondences. Both camera systems were calibrated using Camera Calibration Toolbox for Matlab to reduce any distortion due to the lenses. A single board computer is used to capture and store the image data from FLIR Photon 320 infrared camera while the Tetracam image data is stored internally on board. The image capture time was set by continuous timed delay triggering within the Tetracam camera. The single board computer follows the Tetracam signals and matches the FLIR Photon 320 still image acquisition time with the Tetracam ADC lite. Once the images are captured and stored by the camera systems, the files are downloaded and image processing is conducted. The data was analyzed to calculate the NDVI to observe the plant health. The infrared spectral band was used to identify the warm-blooded animals. In addition, various false color combinations of spectral bands and normalized difference ratios are processed to observe the visual enhancement capabilities on the vegetation and warm-blooded animal. It was determined that detected warm-blooded animal in the infrared band registered on top of NDVI image to show the vegetation health in a single image produced effective results. The combined image data from the FLIR Photon 320 and Tetracam ADC lite produced meaningful vegetation and animal information in the single image. This enhanced the capacity to identify and count animals while simultaneously characterize the vegetation environment, which is highly desired in ecosystem studie

Measurement and Evaluation of Roadway Geometry for Safety Analyses and Pavement Material Volume Estimation for Resurfacing and Rehabilitation Using Mobile LiDAR and Imagery-based Point Clouds

Roadway safety is a multifaceted issue affected by several variables including geometric design features of the roadway, weather conditions, sight distance issues, user behavior, and pavement surface condition. In recent years, transportation agencies have demonstrated a growing interest in utilizing Light Detecting and Ranging (LiDAR) and other remote sensing technologies to enhance data collection productivity, safety, and facilitate the development of strategies to maintain and improve existing roadway infrastructure. Studies have shown that three-dimensional (3D) point clouds acquired using mobile LiDAR systems are highly accurate, dense, and have numerous applications in transportation. Point cloud data applications include extraction of roadway geometry features, asset management, as-built documentation, and maintenance operations. Another source of highly accurate 3D data in the form of point clouds is close-range aerial photogrammetry using unmanned aerial vehicle (UAV) systems. One of the main advantages of these systems over conventional surveying methods is the ability to obtain accurate continuous data in a timely manner. Traditional surveying techniques allow for the collection of road surface data only at specified intervals. Point clouds from LiDAR and imagery-based data can be imported into modeling and design software to create a virtual representation of constructed roadways using 3D models. From a roadway safety assessment standpoint, mobile LiDAR scanning (MLS) systems and UAV close-range photogrammetry (UAV-CRP) can be used as effective methods to produce accurate digital representations of existing roadways for various safety evaluations. This research used LiDAR data collected by five vendors and UAV imagery data collected by the research team to achieve the following objectives: a) evaluate the accuracy of point clouds from MLS and UAV imagery data for collection roadway cross slopes for system-wide cross slope verification; b) evaluate the accuracy of as-built geometry features extracted from MLS and UAV imagery-based point clouds for estimating design speeds on horizontal and vertical curves of existing roadways; c) Determine whether MLS and UAV imagery-based point clouds can be used to produce accurate road surface models for material volume estimation purposes. Ground truth data collected using manual field survey measurements were used to validate the results of this research. Cross slope measurements were extracted from ten randomly selected stations along a 4-lane roadway. This resulted in a total of 42 cross slope measurements per data set including measurements from left turn lanes. The roadway is an urban parkway classified as an urban principal arterial located in Anderson, South Carolina. A comparison of measurements from point clouds and measurements from field survey data using t-test statical analysis showed that deviations between field survey data and MLS and UAV imagery-based point clouds were within the acceptable range of ±0.2% specified by SHRP2 and the South Carolina Department of Transportation (SCDOT). A surface-to-surface method was used to compute and compare material volumes between terrain models from MLS and UAV imagery-based point clouds and a terrain model from field survey data. The field survey data consisted of 424 points collected manually at sixty-nine 100-ft stations over the 1.3-mile study area. The average difference in height for all MLS data was less than 1 inch except for one of the vendors which appeared to be due to a systematic error. The average height difference for the UAV imagery-based data was approximately 1.02 inches. The relatively small errors indicated that these data sets can be used to obtain reliable material volume estimates. Lastly, MLS and UAV imagery-based point clouds were used to obtain horizontal curve radii and superelevation data to estimate design speeds on horizontal curves. Results from paired t-test statistical analyses using a 95% confidence level showed that geometry data extracted from point clouds can be used to obtain realistic estimates of design speeds on horizontal curves. Similarly, road grade and sight distance were obtained from point clouds for design speed estimation on crest and sag vertical curves. A similar approach using a paired t-test statistical analysis at a 95% confidence level showed that point clouds can be used to obtain reliable design speed information on crest and sag vertical curves. The proposed approach offers advantages over extracting information from design drawings which may provide an inaccurate representation of the as-built roadway

Technical viability of high-resolution cartographic products with unmanned aerial vehicles and lightweight sensors applied to engineering

Los avances tecnológicos en sectores como el agronómico, forestal, arqueológico, civil, etc. están suponiendo una revolución debido a la utilización de nuevas tecnologías con la finalidad de optimizar recursos y minimizar los costes. Concretamente, el uso de las plataformas aéreas no tripuladas y los avances experimentados en los sensores a bordo de éstas, permiten obtener información actualizada, así como generar productos que ayuden a la toma de decisiones. En este sentido, cada vez más estas plataformas se están convirtiendo en herramientas con las cuales es posible obtener información en el momento que se desee y a menor coste, comparado con los satélites remotos o las plataformas tripuladas. La elección de usar uno u otro dependerá del análisis de todos los factores que influyen para alcanzar el objetivo. Esta Tesis Doctoral tiene como objetivo principal analizar la viabilidad de los productos cartográficos de alta resolución obtenidos mediante plataformas aéreas no tripuladas con sensores ligeros a bordo. En primer lugar, se ha realizado un recorrido de la evolución experimentada por estas plataformas y de la tipología de sensores que pueden ser integrados, así como algunas de las aplicaciones en las que se están empleando y el procedimiento fotogramétrico a seguir para obtener el producto final. A continuación, se ha evaluado la calidad a través de diferentes test o estándares cartográficos con el fin de analizar la viabilidad del producto generado. Del mismo modo, se han llevado a cabo varios estudios con diferentes configuraciones de vuelo y distintas combinaciones de parámetros que influyen en la planificación del mismo. El objetivo ha sido determinar cuál de ellas es la más adecuada en función de los requerimientos a satisfacer y de la calidad posicional. Los productos cartográficos generados con plataformas aéreas no tripuladas han demostrado que pueden ser aplicados en diferentes ramas de la ingeniería (agronómica y civil, en este caso) para la toma de decisiones que faciliten la gestión y ayuden a definir las actuaciones pertinentes a llevar a cabo.Technological advances in sectors such as agronomy, forestry, archaeology, civil engineering, etc. are assuming a revolution due to the use of new technologies in order to optimize resources and minimize costs. Specifically, the use of unmanned aerial platforms and the advances made in the sensors on board, allow us to obtain updated information, as well as to generate products that help decision making. In this sense, more and more these platforms are becoming tools with which it is possible to obtain information at the time you want and at a lower cost, compared to remote satellites or manned platforms. The choice of using one or the other will depend on the analysis of all the factors that influence the achievement of the objective. The aim of this PhD thesis is to analyze the viability of high-resolution cartographic products obtained from unmanned aerial platforms with light on-board sensors. Firstly, a tour of the evolution experienced by these platforms and the type of sensors that can be integrated, as well as some of the applications in which they are being used and the photogrammetric procedure to be followed to obtain the final product. Next, the quality was evaluated using different tests or cartographic standards in order to analyze the viability of the product generated. In the same way, several studies have been carried out with different flight configurations and different combinations of parameters that influence the planning of the flight. The objective has been to determine which of them is the most suitable according to the requirements to be satisfied and the positional quality. Cartographic products generated with unmanned aerial platforms have shown that they can be applied in different branches of engineering (agronomic and civil, in this case) for decision-making that facilitate management and help define the relevant actions to be carried out

Geomatics support to the metric documentation of the archaeological heritage. Tests and validations on the use of low-cost, rapid, image-based sensors and systems.

L'abstract è presente nell'allegato / the abstract is in the attachmen

VGC 2023 - Unveiling the dynamic Earth with digital methods: 5th Virtual Geoscience Conference: Book of Abstracts

Conference proceedings of the 5th Virtual Geoscience Conference, 21-22 September 2023, held in Dresden. The VGC is a multidisciplinary forum for researchers in geoscience, geomatics and related disciplines to share their latest developments and applications.:Short Courses 9 Workshops Stream 1 10 Workshop Stream 2 11 Workshop Stream 3 12 Session 1 – Point Cloud Processing: Workflows, Geometry & Semantics 14 Session 2 – Visualisation, communication & Teaching 27 Session 3 – Applying Machine Learning in Geosciences 36 Session 4 – Digital Outcrop Characterisation & Analysis 49 Session 5 – Airborne & Remote Mapping 58 Session 6 – Recent Developments in Geomorphic Process and Hazard Monitoring 69 Session 7 – Applications in Hydrology & Ecology 82 Poster Contributions 9

Visual and Camera Sensors

This book includes 13 papers published in Special Issue ("Visual and Camera Sensors") of the journal Sensors. The goal of this Special Issue was to invite high-quality, state-of-the-art research papers dealing with challenging issues in visual and camera sensors

A Status of NASA Rotorcraft Research

In 2006, NASA rotorcraft research was refocused to emphasize high-fidelity first-principles predictive tool development and validation. As part of this new emphasis, documenting the status of NASA rotorcraft research and defining the state-of-the-art in rotorcraft predictive capability were undertaken. This report is the result of this two-year effort. Contributors to this work encompass a wide range of expertise covering the technical disciplines of aeromechanics, acoustics, computational fluid dynamics (CFD), flight dynamics and control, experimental capabilities, propulsion, structures and materials, and multi-disciplinary analysis