Comparison of SLAR images and small-scale, low-sun aerial photographs.

NASA Technical Reports Server (NTRS)

Clark, M. M.

1971-01-01

A comparison of side-looking airborne radar (SLAR) images and black and white aerial photos of similar scale and illumination of an area in the Mojave Desert of California shows that aerial photos yield far more information about geology than do SLAR images because of greater resolution, tonal range, and geometric fidelity, and easier use in stereo. Nevertheless, radar can differentiate some materials or surfaces that aerial photos cannot; thus, they should be considered as complementary, rather than competing tools in geologic investigations. The most significant advantage of SLAR, however, is its freedom from the stringent conditions of weather, date, and time that are required by small-scale aerial photos taken with a specified direction and angle of illumination. Indeed, in low latitudes, SLAR is the only way to obtain small-scale images with low illumination from certain directions; moreover, in areas of nearly continuous cloudiness, radar may be the only practical source of small-scale images.

Building block extraction and classification by means of aerial images fused with super-resolution reconstructed elevation data

NASA Astrophysics Data System (ADS)

Panagiotopoulou, Antigoni; Bratsolis, Emmanuel; Charou, Eleni; Perantonis, Stavros

2017-10-01

The detailed three-dimensional modeling of buildings utilizing elevation data, such as those provided by light detection and ranging (LiDAR) airborne scanners, is increasingly demanded today. There are certain application requirements and available datasets to which any research effort has to be adapted. Our dataset includes aerial orthophotos, with a spatial resolution 20 cm, and a digital surface model generated from LiDAR, with a spatial resolution 1 m and an elevation resolution 20 cm, from an area of Athens, Greece. The aerial images are fused with LiDAR, and we classify these data with a multilayer feedforward neural network for building block extraction. The innovation of our approach lies in the preprocessing step in which the original LiDAR data are super-resolution (SR) reconstructed by means of a stochastic regularized technique before their fusion with the aerial images takes place. The Lorentzian estimator combined with the bilateral total variation regularization performs the SR reconstruction. We evaluate the performance of our approach against that of fusing unprocessed LiDAR data with aerial images. We present the classified images and the statistical measures confusion matrix, kappa coefficient, and overall accuracy. The results demonstrate that our approach predominates over that of fusing unprocessed LiDAR data with aerial images.

CMOS Imaging Sensor Technology for Aerial Mapping Cameras

NASA Astrophysics Data System (ADS)

Neumann, Klaus; Welzenbach, Martin; Timm, Martin

2016-06-01

In June 2015 Leica Geosystems launched the first large format aerial mapping camera using CMOS sensor technology, the Leica DMC III. This paper describes the motivation to change from CCD sensor technology to CMOS for the development of this new aerial mapping camera. In 2002 the DMC first generation was developed by Z/I Imaging. It was the first large format digital frame sensor designed for mapping applications. In 2009 Z/I Imaging designed the DMC II which was the first digital aerial mapping camera using a single ultra large CCD sensor to avoid stitching of smaller CCDs. The DMC III is now the third generation of large format frame sensor developed by Z/I Imaging and Leica Geosystems for the DMC camera family. It is an evolution of the DMC II using the same system design with one large monolithic PAN sensor and four multi spectral camera heads for R,G, B and NIR. For the first time a 391 Megapixel large CMOS sensor had been used as PAN chromatic sensor, which is an industry record. Along with CMOS technology goes a range of technical benefits. The dynamic range of the CMOS sensor is approx. twice the range of a comparable CCD sensor and the signal to noise ratio is significantly better than with CCDs. Finally results from the first DMC III customer installations and test flights will be presented and compared with other CCD based aerial sensors.

First demonstration of aerial gamma-ray imaging using drone for prompt radiation survey in Fukushima

NASA Astrophysics Data System (ADS)

Mochizuki, S.; Kataoka, J.; Tagawa, L.; Iwamoto, Y.; Okochi, H.; Katsumi, N.; Kinno, S.; Arimoto, M.; Maruhashi, T.; Fujieda, K.; Kurihara, T.; Ohsuka, S.

2017-11-01

Considerable amounts of radioactive substances (mainly 137Cs and 134Cs) were released into the environment after the Japanese nuclear disaster in 2011. Some restrictions on residence areas were lifted in April 2017, owing to the successive and effective decontamination operations. However, the distribution of radioactive substances in vast areas of mountain, forest and satoyama close to the city is still unknown; thus, decontamination operations in such areas are being hampered. In this paper, we report on the first aerial gamma-ray imaging of a schoolyard in Fukushima using a drone that carries a high sensitivity Compton camera. We show that the distribution of 137Cs in regions with a diameter of several tens to a hundred meters can be imaged with a typical resolution of 2-5 m within a 10-20 min flights duration. The aerial gamma-ray images taken 10 m and 20 m above the ground are qualitatively consistent with a dose map reconstructed from the ground-based measurements using a survey meter. Although further quantification is needed for the distance and air-absorption corrections to derive in situ dose map, such an aerial drone system can reduce measurement time by a factor of ten and is suitable for place where ground-based measurement are difficult.

A comparison of visual statistics for the image enhancement of FORESITE aerial images with those of major image classes

NASA Astrophysics Data System (ADS)

Jobson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

2006-05-01

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally within the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging-terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on the limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

A Comparison of Visual Statistics for the Image Enhancement of FORESITE Aerial Images with Those of Major Image Classes

NASA Technical Reports Server (NTRS)

Johnson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

2006-01-01

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally with the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging--terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

Aerial Images and Convolutional Neural Network for Cotton Bloom Detection.

PubMed

Xu, Rui; Li, Changying; Paterson, Andrew H; Jiang, Yu; Sun, Shangpeng; Robertson, Jon S

2017-01-01

Monitoring flower development can provide useful information for production management, estimating yield and selecting specific genotypes of crops. The main goal of this study was to develop a methodology to detect and count cotton flowers, or blooms, using color images acquired by an unmanned aerial system. The aerial images were collected from two test fields in 4 days. A convolutional neural network (CNN) was designed and trained to detect cotton blooms in raw images, and their 3D locations were calculated using the dense point cloud constructed from the aerial images with the structure from motion method. The quality of the dense point cloud was analyzed and plots with poor quality were excluded from data analysis. A constrained clustering algorithm was developed to register the same bloom detected from different images based on the 3D location of the bloom. The accuracy and incompleteness of the dense point cloud were analyzed because they affected the accuracy of the 3D location of the blooms and thus the accuracy of the bloom registration result. The constrained clustering algorithm was validated using simulated data, showing good efficiency and accuracy. The bloom count from the proposed method was comparable with the number counted manually with an error of -4 to 3 blooms for the field with a single plant per plot. However, more plots were underestimated in the field with multiple plants per plot due to hidden blooms that were not captured by the aerial images. The proposed methodology provides a high-throughput method to continuously monitor the flowering progress of cotton.

Precision Relative Positioning for Automated Aerial Refueling from a Stereo Imaging System

DTIC Science & Technology

2015-03-01

PRECISION RELATIVE POSITIONING FOR AUTOMATED AERIAL REFUELING FROM A STEREO IMAGING SYSTEM THESIS Kyle P. Werner, 2Lt, USAF AFIT-ENG-MS-15-M-048...REFUELING FROM A STEREO IMAGING SYSTEM THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of...RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENG-MS-15-M-048 PRECISION RELATIVE POSITIONING FOR AUTOMATED AERIAL REFUELING FROM A STEREO IMAGING SYSTEM THESIS

Coma measurement by transmission image sensor with a PSM

NASA Astrophysics Data System (ADS)

Wang, Fan; Wang, Xiangzhao; Ma, Mingying; Zhang, Dongqing; Shi, Weijie; Hu, Jianming

2005-01-01

As feature size decreases, especially with the use of resolution enhancement technique such as off axis illumination and phase shifting mask, fast and accurate in-situ measurement of coma has become very important in improving the performance of modern lithographic tools. The measurement of coma can be achieved by the transmission image sensor, which is an aerial image measurement device. The coma can be determined by measuring the positions of the aerial image at multiple illumination settings. In the present paper, we improve the measurement accuracy of the above technique with an alternating phase shifting mask. Using the scalar diffraction theory, we analyze the effect of coma on the aerial image. To analyze the effect of the alternating phase shifting mask, we compare the pupil filling of the mark used in the above technique with that of the phase-shifted mark used in the new technique. We calculate the coma-induced image displacements of the marks at multiple partial coherence and NA settings, using the PROLITH simulation program. The simulation results show that the accuracy of coma measurement can increase approximately 20 percent using the alternating phase shifting mask.

Study of Automatic Image Rectification and Registration of Scanned Historical Aerial Photographs

NASA Astrophysics Data System (ADS)

Chen, H. R.; Tseng, Y. H.

2016-06-01

Historical aerial photographs directly provide good evidences of past times. The Research Center for Humanities and Social Sciences (RCHSS) of Taiwan Academia Sinica has collected and scanned numerous historical maps and aerial images of Taiwan and China. Some maps or images have been geo-referenced manually, but most of historical aerial images have not been registered since there are no GPS or IMU data for orientation assisting in the past. In our research, we developed an automatic process of matching historical aerial images by SIFT (Scale Invariant Feature Transform) for handling the great quantity of images by computer vision. SIFT is one of the most popular method of image feature extracting and matching. This algorithm extracts extreme values in scale space into invariant image features, which are robust to changing in rotation scale, noise, and illumination. We also use RANSAC (Random sample consensus) to remove outliers, and obtain good conjugated points between photographs. Finally, we manually add control points for registration through least square adjustment based on collinear equation. In the future, we can use image feature points of more photographs to build control image database. Every new image will be treated as query image. If feature points of query image match the features in database, it means that the query image probably is overlapped with control images.With the updating of database, more and more query image can be matched and aligned automatically. Other research about multi-time period environmental changes can be investigated with those geo-referenced temporal spatial data.

Error Estimation Techniques to Refine Overlapping Aerial Image Mosaic Processes via Detected Parameters

ERIC Educational Resources Information Center

Bond, William Glenn

2012-01-01

In this paper, I propose to demonstrate a means of error estimation preprocessing in the assembly of overlapping aerial image mosaics. The mosaic program automatically assembles several hundred aerial images from a data set by aligning them, via image registration using a pattern search method, onto a GIS grid. The method presented first locates…

Aerial image based die-to-model inspections of advanced technology masks

NASA Astrophysics Data System (ADS)

Kim, Jun; Lei, Wei-Guo; McCall, Joan; Zaatri, Suheil; Penn, Michael; Nagpal, Rajesh; Faivishevsky, Lev; Ben-Yishai, Michael; Danino, Udy; Tam, Aviram; Dassa, Oded; Balasubramanian, Vivek; Shah, Tejas H.; Wagner, Mark; Mangan, Shmoolik

2009-10-01

Die-to-Model (D2M) inspection is an innovative approach to running inspection based on a mask design layout data. The D2M concept takes inspection from the traditional domain of mask pattern to the preferred domain of the wafer aerial image. To achieve this, D2M transforms the mask layout database into a resist plane aerial image, which in turn is compared to the aerial image of the mask, captured by the inspection optics. D2M detection algorithms work similarly to an Aerial D2D (die-to-die) inspection, but instead of comparing a die to another die it is compared to the aerial image model. D2M is used whenever D2D inspection is not practical (e.g., single die) or when a validation of mask conformity to design is needed, i.e., for printed pattern fidelity. D2M is of particular importance for inspection of logic single die masks, where no simplifying assumption of pattern periodicity may be done. The application can tailor the sensitivity to meet the needs at different locations, such as device area, scribe lines and periphery. In this paper we present first test results of the D2M mask inspection application at a mask shop. We describe the methodology of using D2M, and review the practical aspects of the D2M mask inspection.

A Mobile System for Measuring Water Surface Velocities Using Unmanned Aerial Vehicle and Large-Scale Particle Image Velocimetry

NASA Astrophysics Data System (ADS)

Chen, Y. L.

2015-12-01

Measurement technologies for velocity of river flow are divided into intrusive and nonintrusive methods. Intrusive method requires infield operations. The measuring process of intrusive methods are time consuming, and likely to cause damages of operator and instrument. Nonintrusive methods require fewer operators and can reduce instrument damages from directly attaching to the flow. Nonintrusive measurements may use radar or image velocimetry to measure the velocities at the surface of water flow. The image velocimetry, such as large scale particle image velocimetry (LSPIV) accesses not only the point velocity but the flow velocities in an area simultaneously. Flow properties of an area hold the promise of providing spatially information of flow fields. This study attempts to construct a mobile system UAV-LSPIV by using an unmanned aerial vehicle (UAV) with LSPIV to measure flows in fields. The mobile system consists of a six-rotor UAV helicopter, a Sony nex5T camera, a gimbal, an image transfer device, a ground station and a remote control device. The activate gimbal helps maintain the camera lens orthogonal to the water surface and reduce the extent of images being distorted. The image transfer device can monitor the captured image instantly. The operator controls the UAV by remote control device through ground station and can achieve the flying data such as flying height and GPS coordinate of UAV. The mobile system was then applied to field experiments. The deviation of velocities measured by UAV-LSPIV of field experiments and handhold Acoustic Doppler Velocimeter (ADV) is under 8%. The results of the field experiments suggests that the application of UAV-LSPIV can be effectively applied to surface flow studies.

Automatic forest-fire measuring using ground stations and Unmanned Aerial Systems.

PubMed

Martínez-de Dios, José Ramiro; Merino, Luis; Caballero, Fernando; Ollero, Anibal

2011-01-01

This paper presents a novel system for automatic forest-fire measurement using cameras distributed at ground stations and mounted on Unmanned Aerial Systems (UAS). It can obtain geometrical measurements of forest fires in real-time such as the location and shape of the fire front, flame height and rate of spread, among others. Measurement of forest fires is a challenging problem that is affected by numerous potential sources of error. The proposed system addresses them by exploiting the complementarities between infrared and visual cameras located at different ground locations together with others onboard Unmanned Aerial Systems (UAS). The system applies image processing and geo-location techniques to obtain forest-fire measurements individually from each camera and then integrates the results from all the cameras using statistical data fusion techniques. The proposed system has been extensively tested and validated in close-to-operational conditions in field fire experiments with controlled safety conditions carried out in Portugal and Spain from 2001 to 2006.

Automatic Forest-Fire Measuring Using Ground Stations and Unmanned Aerial Systems

PubMed Central

Martínez-de Dios, José Ramiro; Merino, Luis; Caballero, Fernando; Ollero, Anibal

2011-01-01

This paper presents a novel system for automatic forest-fire measurement using cameras distributed at ground stations and mounted on Unmanned Aerial Systems (UAS). It can obtain geometrical measurements of forest fires in real-time such as the location and shape of the fire front, flame height and rate of spread, among others. Measurement of forest fires is a challenging problem that is affected by numerous potential sources of error. The proposed system addresses them by exploiting the complementarities between infrared and visual cameras located at different ground locations together with others onboard Unmanned Aerial Systems (UAS). The system applies image processing and geo-location techniques to obtain forest-fire measurements individually from each camera and then integrates the results from all the cameras using statistical data fusion techniques. The proposed system has been extensively tested and validated in close-to-operational conditions in field fire experiments with controlled safety conditions carried out in Portugal and Spain from 2001 to 2006. PMID:22163958

An improved dehazing algorithm of aerial high-definition image

NASA Astrophysics Data System (ADS)

Jiang, Wentao; Ji, Ming; Huang, Xiying; Wang, Chao; Yang, Yizhou; Li, Tao; Wang, Jiaoying; Zhang, Ying

2016-01-01

For unmanned aerial vehicle(UAV) images, the sensor can not get high quality images due to fog and haze weather. To solve this problem, An improved dehazing algorithm of aerial high-definition image is proposed. Based on the model of dark channel prior, the new algorithm firstly extracts the edges from crude estimated transmission map and expands the extracted edges. Then according to the expended edges, the algorithm sets a threshold value to divide the crude estimated transmission map into different areas and makes different guided filter on the different areas compute the optimized transmission map. The experimental results demonstrate that the performance of the proposed algorithm is substantially the same as the one based on dark channel prior and guided filter. The average computation time of the new algorithm is around 40% of the one as well as the detection ability of UAV image is improved effectively in fog and haze weather.

Laser Doppler velocimeter aerial spray measurements

NASA Technical Reports Server (NTRS)

Zalay, A. D.; Eberle, W. R.; Howle, R. E.; Shrider, K. R.

1978-01-01

An experimental research program for measuring the location, spatial extent, and relative concentration of airborne spray clouds generated by agricultural aircraft is described. The measurements were conducted with a ground-based laser Doppler velocimeter. The remote sensing instrumentation, experimental tests, and the results of the flight tests are discussed. The cross section of the aerial spray cloud and the observed location, extent, and relative concentration of the airborne particulates are presented. It is feasible to use a mobile laser Doppler velocimeter to track and monitor the transport and dispersion of aerial spray generated by an agricultural aircraft.

International-Aerial Measuring System (I-AMS) Training Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wasiolek, Piotre T.; Malchor, Russell L.; Maurer, Richard J.

2015-10-01

Since the Fukushima reactor accident in 2011, there has been an increased interest worldwide in developing national capabilities to rapidly map and assess ground contamination resulting from nuclear reactor accidents. The capability to rapidly measure the size of the contaminated area, determine the activity level, and identify the radionuclides can aid emergency managers and decision makers in providing timely protective action recommendations to the public and first responders. The development of an aerial detection capability requires interagency coordination to assemble the radiation experts, detection system operators, and aviation aircrews to conduct the aerial measurements, analyze and interpret the data, andmore » provide technical assessments. The Office of International Emergency Management and Cooperation (IEMC) at the U.S. Department of Energy, National Nuclear Security Administration (DOE/NNSA) sponsors an International - Aerial Measuring System (I-AMS) training program for partner nations to develop and enhance their response to radiological emergencies. An initial series of courses can be conducted in the host country to assist in developing an aerial detection capability. As the capability develops and expands, additional experience can be gained through advanced courses with the opportunity to conduct aerial missions over a broad range of radiation environments.« less

Vehicle Detection of Aerial Image Using TV-L1 Texture Decomposition

NASA Astrophysics Data System (ADS)

Wang, Y.; Wang, G.; Li, Y.; Huang, Y.

2016-06-01

Vehicle detection from high-resolution aerial image facilitates the study of the public traveling behavior on a large scale. In the context of road, a simple and effective algorithm is proposed to extract the texture-salient vehicle among the pavement surface. Texturally speaking, the majority of pavement surface changes a little except for the neighborhood of vehicles and edges. Within a certain distance away from the given vector of the road network, the aerial image is decomposed into a smoothly-varying cartoon part and an oscillatory details of textural part. The variational model of Total Variation regularization term and L1 fidelity term (TV-L1) is adopted to obtain the salient texture of vehicles and the cartoon surface of pavement. To eliminate the noise of texture decomposition, regions of pavement surface are refined by seed growing and morphological operation. Based on the shape saliency analysis of the central objects in those regions, vehicles are detected as the objects of rectangular shape saliency. The proposed algorithm is tested with a diverse set of aerial images that are acquired at various resolution and scenarios around China. Experimental results demonstrate that the proposed algorithm can detect vehicles at the rate of 71.5% and the false alarm rate of 21.5%, and that the speed is 39.13 seconds for a 4656 x 3496 aerial image. It is promising for large-scale transportation management and planning.

Evaluation of Deep Learning Based Stereo Matching Methods: from Ground to Aerial Images

NASA Astrophysics Data System (ADS)

Liu, J.; Ji, S.; Zhang, C.; Qin, Z.

2018-05-01

Dense stereo matching has been extensively studied in photogrammetry and computer vision. In this paper we evaluate the application of deep learning based stereo methods, which were raised from 2016 and rapidly spread, on aerial stereos other than ground images that are commonly used in computer vision community. Two popular methods are evaluated. One learns matching cost with a convolutional neural network (known as MC-CNN); the other produces a disparity map in an end-to-end manner by utilizing both geometry and context (known as GC-net). First, we evaluate the performance of the deep learning based methods for aerial stereo images by a direct model reuse. The models pre-trained on KITTI 2012, KITTI 2015 and Driving datasets separately, are directly applied to three aerial datasets. We also give the results of direct training on target aerial datasets. Second, the deep learning based methods are compared to the classic stereo matching method, Semi-Global Matching(SGM), and a photogrammetric software, SURE, on the same aerial datasets. Third, transfer learning strategy is introduced to aerial image matching based on the assumption of a few target samples available for model fine tuning. It experimentally proved that the conventional methods and the deep learning based methods performed similarly, and the latter had greater potential to be explored.

D City Transformations by Time Series of Aerial Images

NASA Astrophysics Data System (ADS)

Adami, A.

2015-02-01

Recent photogrammetric applications, based on dense image matching algorithms, allow to use not only images acquired by digital cameras, amateur or not, but also to recover the vast heritage of analogue photographs. This possibility opens up many possibilities in the use and enhancement of existing photos heritage. The research of the original figuration of old buildings, the virtual reconstruction of disappeared architectures and the study of urban development are some of the application areas that exploit the great cultural heritage of photography. Nevertheless there are some restrictions in the use of historical images for automatic reconstruction of buildings such as image quality, availability of camera parameters and ineffective geometry of image acquisition. These constrains are very hard to solve and it is difficult to discover good dataset in the case of terrestrial close range photogrammetry for the above reasons. Even the photographic archives of museums and superintendence, while retaining a wealth of documentation, have no dataset for a dense image matching approach. Compared to the vast collection of historical photos, the class of aerial photos meets both criteria stated above. In this paper historical aerial photographs are used with dense image matching algorithms to realize 3d models of a city in different years. The models can be used to study the urban development of the city and its changes through time. The application relates to the city centre of Verona, for which some time series of aerial photographs have been retrieved. The models obtained in this way allowed, right away, to observe the urban development of the city, the places of expansion and new urban areas. But a more interesting aspect emerged from the analytical comparison between models. The difference, as the Euclidean distance, between two models gives information about new buildings or demolitions. As considering accuracy it is necessary point out that the quality of final

Aerial Vehicle Surveys of other Planetary Atmospheres and Surfaces: Imaging, Remote-sensing, and Autonomy Technology Requirements

NASA Technical Reports Server (NTRS)

Young, Larry A.; Pisanich, Gregory; Ippolito, Corey; Alena, Rick

2005-01-01

The objective of this paper is to review the anticipated imaging and remote-sensing technology requirements for aerial vehicle survey missions to other planetary bodies in our Solar system that can support in-atmosphere flight. In the not too distant future such planetary aerial vehicle (a.k.a. aerial explorers) exploration missions will become feasible. Imaging and remote-sensing observations will be a key objective for these missions. Accordingly, it is imperative that optimal solutions in terms of imaging acquisition and real-time autonomous analysis of image data sets be developed for such vehicles.

Grab a coffee: your aerial images are already analyzed

NASA Astrophysics Data System (ADS)

Garetto, Anthony; Rademacher, Thomas; Schulz, Kristian

2015-07-01

For over 2 decades the AIMTM platform has been utilized in mask shops as the standard for actinic review of photomask sites in order to perform defect disposition and repair review. Throughout this time the measurement throughput of the systems has been improved in order to keep pace with the requirements demanded by a manufacturing environment, however the analysis of the sites captured has seen little improvement and remained a manual process. This manual analysis of aerial images is time consuming, subject to error and unreliability and contributes to holding up turn-around time (TAT) and slowing process flow in a manufacturing environment. AutoAnalysis, the first application available for the FAVOR® platform, offers a solution to these problems by providing fully automated data transfer and analysis of AIMTM aerial images. The data is automatically output in a customizable format that can be tailored to your internal needs and the requests of your customers. Savings in terms of operator time arise from the automated analysis which no longer needs to be performed. Reliability is improved as human error is eliminated making sure the most defective region is always and consistently captured. Finally the TAT is shortened and process flow for the back end of the line improved as the analysis is fast and runs in parallel to the measurements. In this paper the concept and approach of AutoAnalysis will be presented as well as an update to the status of the project. A look at the benefits arising from the automation and the customizable approach of the solution will be shown.

Underwater binocular imaging of aerial objects versus the position of eyes relative to the flat water surface.

PubMed

Barta, András; Horváth, Gábor

2003-12-01

The apparent position, size, and shape of aerial objects viewed binocularly from water change as a result of the refraction of light at the water surface. Earlier studies of the refraction-distorted structure of the aerial binocular visual field of underwater observers were restricted to either vertically or horizontally oriented eyes. Here we calculate the position of the binocular image point of an aerial object point viewed by two arbitrarily positioned underwater eyes when the water surface is flat. Assuming that binocular image fusion is performed by appropriate vergent eye movements to bring the object's image onto the foveae, the structure of the aerial binocular visual field is computed and visualized as a function of the relative positions of the eyes. We also analyze two erroneous representations of the underwater imaging of aerial objects that have occurred in the literature. It is demonstrated that the structure of the aerial binocular visual field of underwater observers distorted by refraction is more complex than has been thought previously.

A Low-Cost Imaging System for Aerial Applicators

USDA-ARS?s Scientific Manuscript database

Agricultural aircraft provide a readily available and versatile platform for airborne remote sensing. Although various airborne imaging systems are being used for research and commercial applications, most of these systems are either too expensive or too complex to be of practical use for aerial app...

Measurements from an Aerial Vehicle: A New Tool for Planetary Exploration

NASA Technical Reports Server (NTRS)

Wright, Henry S.; Levine, Joel S.; Croom, Mark A.; Edwards, William C.; Qualls, Garry D.; Gasbarre, Joseph F.

2004-01-01

Aerial vehicles fill a unique planetary science measurement gap, that of regional-scale, near-surface observation, while providing a fresh perspective for potential discovery. Aerial vehicles used in planetary exploration bridge the scale and resolution measurement gaps between orbiters (global perspective with limited spatial resolution) and landers (local perspective with high spatial resolution) thus complementing and extending orbital and landed measurements. Planetary aerial vehicles can also survey scientifically interesting terrain that is inaccessible or hazardous to landed missions. The use of aerial assets for performing observations on Mars, Titan, or Venus will enable direct measurements and direct follow-ons to recent discoveries. Aerial vehicles can be used for remote sensing of the interior, surface and atmosphere of Mars, Venus and Titan. Types of aerial vehicles considered are airplane "heavier than air" and airships and balloons "lighter than air". Interdependencies between the science measurements, science goals and objectives, and platform implementation illustrate how the proper balance of science, engineering, and cost, can be achieved to allow for a successful mission. Classification of measurement types along with how those measurements resolve science questions and how these instruments are accommodated within the mission context are discussed.

Aerial image databases for pipeline rights-of-way management

NASA Astrophysics Data System (ADS)

Jadkowski, Mark A.

1996-03-01

Pipeline companies that own and manage extensive rights-of-way corridors are faced with ever-increasing regulatory pressures, operating issues, and the need to remain competitive in today's marketplace. Automation has long been an answer to the problem of having to do more work with less people, and Automated Mapping/Facilities Management/Geographic Information Systems (AM/FM/GIS) solutions have been implemented at several pipeline companies. Until recently, the ability to cost-effectively acquire and incorporate up-to-date aerial imagery into these computerized systems has been out of the reach of most users. NASA's Earth Observations Commercial Applications Program (EOCAP) is providing a means by which pipeline companies can bridge this gap. The EOCAP project described in this paper includes a unique partnership with NASA and James W. Sewall Company to develop an aircraft-mounted digital camera system and a ground-based computer system to geometrically correct and efficiently store and handle the digital aerial images in an AM/FM/GIS environment. This paper provides a synopsis of the project, including details on (1) the need for aerial imagery, (2) NASA's interest and role in the project, (3) the design of a Digital Aerial Rights-of-Way Monitoring System, (4) image georeferencing strategies for pipeline applications, and (5) commercialization of the EOCAP technology through a prototype project at Algonquin Gas Transmission Company which operates major gas pipelines in New England, New York, and New Jersey.

Floating aerial 3D display based on the freeform-mirror and the improved integral imaging system

NASA Astrophysics Data System (ADS)

Yu, Xunbo; Sang, Xinzhu; Gao, Xin; Yang, Shenwu; Liu, Boyang; Chen, Duo; Yan, Binbin; Yu, Chongxiu

2018-09-01

A floating aerial three-dimensional (3D) display based on the freeform-mirror and the improved integral imaging system is demonstrated. In the traditional integral imaging (II), the distortion originating from lens aberration warps elemental images and degrades the visual effect severely. To correct the distortion of the observed pixels and to improve the image quality, a directional diffuser screen (DDS) is introduced. However, the improved integral imaging system can hardly present realistic images with the large off-screen depth, which limits floating aerial visual experience. To display the 3D image in the free space, the off-axis reflection system with the freeform-mirror is designed. By combining the improved II and the designed freeform optical element, the floating aerial 3D image is presented.

Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis

DTIC Science & Technology

1989-08-01

Automatic Line Network Extraction from Aerial Imangery of Urban Areas Sthrough KnowledghBased Image Analysis N 04 Final Technical ReportI December...Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis Accesion For NTIS CRA&I DTIC TAB 0...paittern re’ognlition. blac’kboardl oriented symbollic processing, knowledge based image analysis , image understanding, aer’ial imsagery, urban area, 17

A low-cost dual-camera imaging system for aerial applicators

USDA-ARS?s Scientific Manuscript database

Agricultural aircraft provide a readily available remote sensing platform as low-cost and easy-to-use consumer-grade cameras are being increasingly used for aerial imaging. In this article, we report on a dual-camera imaging system we recently assembled that can capture RGB and near-infrared (NIR) i...

3D Power Line Extraction from Multiple Aerial Images.

PubMed

Oh, Jaehong; Lee, Changno

2017-09-29

Power lines are cables that carry electrical power from a power plant to an electrical substation. They must be connected between the tower structures in such a way that ensures minimum tension and sufficient clearance from the ground. Power lines can stretch and sag with the changing weather, eventually exceeding the planned tolerances. The excessive sags can then cause serious accidents, while hindering the durability of the power lines. We used photogrammetric techniques with a low-cost drone to achieve efficient 3D mapping of power lines that are often difficult to approach. Unlike the conventional image-to-object space approach, we used the object-to-image space approach using cubic grid points. We processed four strips of aerial images to automatically extract the power line points in the object space. Experimental results showed that the approach could successfully extract the positions of the power line points for power line generation and sag measurement with the elevation accuracy of a few centimeters.

3D Power Line Extraction from Multiple Aerial Images

PubMed Central

Lee, Changno

2017-01-01

Power lines are cables that carry electrical power from a power plant to an electrical substation. They must be connected between the tower structures in such a way that ensures minimum tension and sufficient clearance from the ground. Power lines can stretch and sag with the changing weather, eventually exceeding the planned tolerances. The excessive sags can then cause serious accidents, while hindering the durability of the power lines. We used photogrammetric techniques with a low-cost drone to achieve efficient 3D mapping of power lines that are often difficult to approach. Unlike the conventional image-to-object space approach, we used the object-to-image space approach using cubic grid points. We processed four strips of aerial images to automatically extract the power line points in the object space. Experimental results showed that the approach could successfully extract the positions of the power line points for power line generation and sag measurement with the elevation accuracy of a few centimeters. PMID:28961204

Water Plume Temperature Measurements by an Unmanned Aerial System (UAS).

PubMed

DeMario, Anthony; Lopez, Pete; Plewka, Eli; Wix, Ryan; Xia, Hai; Zamora, Emily; Gessler, Dan; Yalin, Azer P

2017-02-07

We report on the development and testing of a proof of principle water temperature measurement system deployed on an unmanned aerial system (UAS), for field measurements of thermal discharges into water. The primary elements of the system include a quad-copter UAS to which has been integrated, for the first time, both a thermal imaging infrared (IR) camera and an immersible probe that can be dipped below the water surface to obtain vertical water temperature profiles. The IR camera is used to take images of the overall water surface to geo-locate the plume, while the immersible probe provides quantitative temperature depth profiles at specific locations. The full system has been tested including the navigation of the UAS, its ability to safely carry the sensor payload, and the performance of both the IR camera and the temperature probe. Finally, the UAS sensor system was successfully deployed in a pilot field study at a coal burning power plant, and obtained images and temperature profiles of the thermal effluent.

Density estimation in aerial images of large crowds for automatic people counting

NASA Astrophysics Data System (ADS)

Herrmann, Christian; Metzler, Juergen

2013-05-01

Counting people is a common topic in the area of visual surveillance and crowd analysis. While many image-based solutions are designed to count only a few persons at the same time, like pedestrians entering a shop or watching an advertisement, there is hardly any solution for counting large crowds of several hundred persons or more. We addressed this problem previously by designing a semi-automatic system being able to count crowds consisting of hundreds or thousands of people based on aerial images of demonstrations or similar events. This system requires major user interaction to segment the image. Our principle aim is to reduce this manual interaction. To achieve this, we propose a new and automatic system. Besides counting the people in large crowds, the system yields the positions of people allowing a plausibility check by a human operator. In order to automatize the people counting system, we use crowd density estimation. The determination of crowd density is based on several features like edge intensity or spatial frequency. They indicate the density and discriminate between a crowd and other image regions like buildings, bushes or trees. We compare the performance of our automatic system to the previous semi-automatic system and to manual counting in images. By counting a test set of aerial images showing large crowds containing up to 12,000 people, the performance gain of our new system will be measured. By improving our previous system, we will increase the benefit of an image-based solution for counting people in large crowds.

HISTORIC IMAGE: AERIAL VIEW OF THE CEMETERY AND ITS ENVIRONS. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

HISTORIC IMAGE: AERIAL VIEW OF THE CEMETERY AND ITS ENVIRONS. PHOTOGRAPH TAKEN ON 18 MAY 1948. NCA HISTORY COLLECTION. - Knoxville National Cemetery, 939 Tyson Street, Northwest, Knoxville, Knox County, TN

a Fast Approach for Stitching of Aerial Images

NASA Astrophysics Data System (ADS)

Moussa, A.; El-Sheimy, N.

2016-06-01

The last few years have witnessed an increasing volume of aerial image data because of the extensive improvements of the Unmanned Aerial Vehicles (UAVs). These newly developed UAVs have led to a wide variety of applications. A fast assessment of the achieved coverage and overlap of the acquired images of a UAV flight mission is of great help to save the time and cost of the further steps. A fast automatic stitching of the acquired images can help to visually assess the achieved coverage and overlap during the flight mission. This paper proposes an automatic image stitching approach that creates a single overview stitched image using the acquired images during a UAV flight mission along with a coverage image that represents the count of overlaps between the acquired images. The main challenge of such task is the huge number of images that are typically involved in such scenarios. A short flight mission with image acquisition frequency of one second can capture hundreds to thousands of images. The main focus of the proposed approach is to reduce the processing time of the image stitching procedure by exploiting the initial knowledge about the images positions provided by the navigation sensors. The proposed approach also avoids solving for all the transformation parameters of all the photos together to save the expected long computation time if all the parameters were considered simultaneously. After extracting the points of interest of all the involved images using Scale-Invariant Feature Transform (SIFT) algorithm, the proposed approach uses the initial image's coordinates to build an incremental constrained Delaunay triangulation that represents the neighborhood of each image. This triangulation helps to match only the neighbor images and therefore reduces the time-consuming features matching step. The estimated relative orientation between the matched images is used to find a candidate seed image for the stitching process. The pre-estimated transformation

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks.

PubMed

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-11-24

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks

PubMed Central

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-01-01

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed. PMID:29186756

Detection and clustering of features in aerial images by neuron network-based algorithm

NASA Astrophysics Data System (ADS)

Vozenilek, Vit

2015-12-01

The paper presents the algorithm for detection and clustering of feature in aerial photographs based on artificial neural networks. The presented approach is not focused on the detection of specific topographic features, but on the combination of general features analysis and their use for clustering and backward projection of clusters to aerial image. The basis of the algorithm is a calculation of the total error of the network and a change of weights of the network to minimize the error. A classic bipolar sigmoid was used for the activation function of the neurons and the basic method of backpropagation was used for learning. To verify that a set of features is able to represent the image content from the user's perspective, the web application was compiled (ASP.NET on the Microsoft .NET platform). The main achievements include the knowledge that man-made objects in aerial images can be successfully identified by detection of shapes and anomalies. It was also found that the appropriate combination of comprehensive features that describe the colors and selected shapes of individual areas can be useful for image analysis.

Looking into the water with oblique head tilting: revision of the aerial binocular imaging of underwater objects.

PubMed

Horváth, Gábor; Buchta, Krisztián; Varjú, Dezsö

2003-06-01

It is a well-known phenomenon that when we look into the water with two aerial eyes, both the apparent position and the apparent shape of underwater objects are different from the real ones because of refraction at the water surface. Earlier studies of the refraction-distorted structure of the underwater binocular visual field of aerial observers were restricted to either vertically or horizontally oriented eyes. We investigate a generalized version of this problem: We calculate the position of the binocular image point of an underwater object point viewed by two arbitrarily positioned aerial eyes, including oblique orientations of the eyes relative to the flat water surface. Assuming that binocular image fusion is performed by appropriate vergent eye movements to bring the object's image onto the foveas, the structure of the underwater binocular visual field is computed and visualized in different ways as a function of the relative positions of the eyes. We show that a revision of certain earlier treatments of the aerial imaging of underwater objects is necessary. We analyze and correct some widespread erroneous or incomplete representations of this classical geometric optical problem that occur in different textbooks. Improving the theory of aerial binocular imaging of underwater objects, we demonstrate that the structure of the underwater binocular visual field of aerial observers distorted by refraction is more complex than has been thought previously.

Design of an integrated aerial image sensor

NASA Astrophysics Data System (ADS)

Xue, Jing; Spanos, Costas J.

2005-05-01

The subject of this paper is a novel integrated aerial image sensor (IAIS) system suitable for integration within the surface of an autonomous test wafer. The IAIS could be used as a lithography processing monitor, affording a "wafer's eye view" of the process, and therefore facilitating advanced process control and diagnostics without integrating (and dedicating) the sensor to the processing equipment. The IAIS is composed of an aperture mask and an array of photo-detectors. In order to retrieve nanometer scale resolution of the aerial image with a practical photo-detector pixel size, we propose a design of an aperture mask involving a series of spatial phase "moving" aperture groups. We demonstrate a design example aimed at the 65nm technology node through TEMPEST simulation. The optimized, key design parameters include an aperture width in the range of 30nm, aperture thickness in the range of 70nm, and offer a spatial resolution of about 5nm, all with comfortable fabrication tolerances. Our preliminary simulation work indicates the possibility of the IAIS being applied to the immersion lithography. A bench-top far-field experiment verifies that our approach of the spatial frequency down-shift through forming large Moire patterns is feasible.

Water Plume Temperature Measurements by an Unmanned Aerial System (UAS)

PubMed Central

DeMario, Anthony; Lopez, Pete; Plewka, Eli; Wix, Ryan; Xia, Hai; Zamora, Emily; Gessler, Dan; Yalin, Azer P.

2017-01-01

We report on the development and testing of a proof of principle water temperature measurement system deployed on an unmanned aerial system (UAS), for field measurements of thermal discharges into water. The primary elements of the system include a quad-copter UAS to which has been integrated, for the first time, both a thermal imaging infrared (IR) camera and an immersible probe that can be dipped below the water surface to obtain vertical water temperature profiles. The IR camera is used to take images of the overall water surface to geo-locate the plume, while the immersible probe provides quantitative temperature depth profiles at specific locations. The full system has been tested including the navigation of the UAS, its ability to safely carry the sensor payload, and the performance of both the IR camera and the temperature probe. Finally, the UAS sensor system was successfully deployed in a pilot field study at a coal burning power plant, and obtained images and temperature profiles of the thermal effluent. PMID:28178215

Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data

PubMed Central

Huang, Huabing; Gong, Peng; Cheng, Xiao; Clinton, Nick; Li, Zengyuan

2009-01-01

Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data. PMID:22573971

Overview of meteorological measurements for aerial spray modeling.

PubMed

Rafferty, J E; Biltoft, C A; Bowers, J F

1996-06-01

The routine meteorological observations made by the National Weather Service have a spatial resolution on the order of 1,000 km, whereas the resolution needed to conduct or model aerial spray applications is on the order of 1-10 km. Routinely available observations also do not include the detailed information on the turbulence and thermal structure of the boundary layer that is needed to predict the transport, dispersion, and deposition of aerial spray releases. This paper provides an overview of the information needed to develop the meteorological inputs for an aerial spray model such as the FSCBG and discusses the different types of instruments that are available to make the necessary measurements.

Using aerial images for establishing a workflow for the quantification of water management measures

NASA Astrophysics Data System (ADS)

Leuschner, Annette; Merz, Christoph; van Gasselt, Stephan; Steidl, Jörg

2017-04-01

Quantified landscape characteristics, such as morphology, land use or hydrological conditions, play an important role for hydrological investigations as landscape parameters directly control the overall water balance. A powerful assimilation and geospatial analysis of remote sensing datasets in combination with hydrological modeling allows to quantify landscape parameters and water balances efficiently. This study focuses on the development of a workflow to extract hydrologically relevant data from aerial image datasets and derived products in order to allow an effective parametrization of a hydrological model. Consistent and self-contained data source are indispensable for achieving reasonable modeling results. In order to minimize uncertainties and inconsistencies, input parameters for modeling should be extracted from one remote-sensing dataset mainly if possbile. Here, aerial images have been chosen because of their high spatial and spectral resolution that permits the extraction of various model relevant parameters, like morphology, land-use or artificial drainage-systems. The methodological repertoire to extract environmental parameters range from analyses of digital terrain models, multispectral classification and segmentation of land use distribution maps and mapping of artificial drainage-systems based on spectral and visual inspection. The workflow has been tested for a mesoscale catchment area which forms a characteristic hydrological system of a young moraine landscape located in the state of Brandenburg, Germany. These dataset were used as input-dataset for multi-temporal hydrological modelling of water balances to detect and quantify anthropogenic and meteorological impacts. ArcSWAT, as a GIS-implemented extension and graphical user input interface for the Soil Water Assessment Tool (SWAT) was chosen. The results of this modeling approach provide the basis for anticipating future development of the hydrological system, and regarding system changes for

Detection of Aspens Using High Resolution Aerial Laser Scanning Data and Digital Aerial Images

PubMed Central

Säynäjoki, Raita; Packalén, Petteri; Maltamo, Matti; Vehmas, Mikko; Eerikäinen, Kalle

2008-01-01

The aim was to use high resolution Aerial Laser Scanning (ALS) data and aerial images to detect European aspen (Populus tremula L.) from among other deciduous trees. The field data consisted of 14 sample plots of 30 m × 30 m size located in the Koli National Park in the North Karelia, Eastern Finland. A Canopy Height Model (CHM) was interpolated from the ALS data with a pulse density of 3.86/m2, low-pass filtered using Height-Based Filtering (HBF) and binarized to create the mask needed to separate the ground pixels from the canopy pixels within individual areas. Watershed segmentation was applied to the low-pass filtered CHM in order to create preliminary canopy segments, from which the non-canopy elements were extracted to obtain the final canopy segmentation, i.e. the ground mask was analysed against the canopy mask. A manual classification of aerial images was employed to separate the canopy segments of deciduous trees from those of coniferous trees. Finally, linear discriminant analysis was applied to the correctly classified canopy segments of deciduous trees to classify them into segments belonging to aspen and those belonging to other deciduous trees. The independent variables used in the classification were obtained from the first pulse ALS point data. The accuracy of discrimination between aspen and other deciduous trees was 78.6%. The independent variables in the classification function were the proportion of vegetation hits, the standard deviation of in pulse heights, accumulated intensity at the 90th percentile and the proportion of laser points reflected at the 60th height percentile. The accuracy of classification corresponded to the validation results of earlier ALS-based studies on the classification of individual deciduous trees to tree species. PMID:27873799

HISTORIC IMAGE: AERIAL VIEW OF THE CEMETERY AND ITS ENVIRONS. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

HISTORIC IMAGE: AERIAL VIEW OF THE CEMETERY AND ITS ENVIRONS. PHOTOGRAPH TAKEN ON 6 APRIL 1968. NCA HISTORY COLLECTION. - Rock Island National Cemetery, Rock Island Arsenal, 0.25 mile north of southern tip of Rock Island, Rock Island, Rock Island County, IL

A low-cost single-camera imaging system for aerial applicators

USDA-ARS?s Scientific Manuscript database

Agricultural aircraft provide a readily available and versatile platform for airborne remote sensing. Although various airborne imaging systems are available, most of these systems are either too expensive or too complex to be of practical use for aerial applicators. The objective of this study was ...

Integration of aerial remote sensing imaging data in a 3D-GIS environment

NASA Astrophysics Data System (ADS)

Moeller, Matthias S.

2003-03-01

For some years sensor systems have been available providing digital images of a new quality. Especially aerial stereo scanners acquire digital multispectral images with an extremely high ground resolution of about 0.10 - 0.15m and provide in addition a Digital Surface Models (DSM). These imaging products both can be used for a detailed monitoring at scales up to 1:500. The processed georeferenced multispectral orthoimages can be readily integrated into GIS making them useful for a number of applications. The DSM, derived from forward and backward facing sensors of an aerial imaging system provides a ground resolution of 0.5 m and can be used for 3D visualization purposes. In some cases it is essential, to store the ground elevation as a Digital Terrain Model (DTM) and also the height of 3-dimensional objects in a separated database. Existing automated algorithms do not work precise for the extraction of DTM from aerial scanner DSM. This paper presents a new approach which combines the visible image data and the DSM data for the generation of DTM with a reliable geometric accuracy. Already existing cadastral data can be used as a knowledge base for the extraction of building heights in cities. These elevation data is the essential source for a GIS based urban information system with a 3D visualization component.

Aerial imaging technology for photomask qualification: from a microscope to a metrology tool

NASA Astrophysics Data System (ADS)

Garetto, Anthony; Scherübl, Thomas; Peters, Jan Hendrik

2012-09-01

Photomasks carry the structured information of the chip designs printed with lithography scanners onto wafers. These structures, for the most modern technologies, are enlarged by a factor of 4 with respect to the final circuit design, and 20-60 of these photomasks are needed for the production of a single completed chip used, for example, in computers or cell phones. Lately, designs have been reported to be on the drawing board with close to 100 of these layers. Each of these photomasks will be reproduced onto the wafer several hundred times and typically 5000-50 000 wafers will be produced with each of them. Hence, the photomasks need to be absolutely defect-free to avoid any fatal electrical shortcut in the design or drastic performance degradation. One well-known method in the semiconductor industry is to analyze the aerial image of the photomask in a dedicated tool referred to as Aerial Imaging Measurement System, which emulates the behavior of the respective lithography scanner used for the imaging of the mask. High-end lithography scanners use light with a wavelength of 193 nm and high numerical apertures (NAs) of 1.35 utilizing a water film between the last lens and the resist to be illuminated (immersion scanners). Complex illumination shapes enable the imaging of structures well below the wavelength used. Future lithography scanners will work at a wavelength of 13.5 nm [extreme ultraviolet (EUV)] and require the optical system to work with mirrors in vacuum instead of the classical lenses used in current systems. The exact behavior of these systems is emulated by the Aerial Image Measurement System (AIMS™; a Trademark of Carl Zeiss). With these systems, any position of the photomask can be imaged under the same illumination condition used by the scanners, and hence, a prediction of the printing behavior of any structure can be derived. This system is used by mask manufacturers in their process flow to review critical defects or verify defect repair

Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge-Based Image Analysis.

DTIC Science & Technology

1988-01-19

approach for the analysis of aerial images. In this approach image analysis is performed ast three levels of abstraction, namely iconic or low-level... image analysis , symbolic or medium-level image analysis , and semantic or high-level image analysis . Domain dependent knowledge about prototypical urban

Three scales of aerial photography compared for making stand measurements

Treesearch

Earl J. Rogers; Gene Avery; Roy A. Chapman

1959-01-01

Three scales of aerial photography were tested in an attempt to determine the best scale to use in forest surveying. This was done by comparing photo measurements of average tree height, average crown diameter, and crown-closure percent. These stand variables were selected for testing because of their applicability in making aerial estimates of timber volume.

Unmanned aerial vehicle acquisition of three-dimensional digital image correlation measurements for structural health monitoring of bridges

NASA Astrophysics Data System (ADS)

Reagan, Daniel; Sabato, Alessandro; Niezrecki, Christopher

2017-04-01

Civil engineering structures such as bridges, buildings, and tunnels continue to be used despite aging and deterioration well past their design life. In 2013, the American Society of Civil Engineers (ASCE) rated the state of the U.S. bridges as mediocre, despite the $12.8 billion USD annually invested. Traditional inspection and monitoring techniques may produce inconsistent results, are labor intensive and too time-consuming to be considered effective for large-scale monitoring. Therefore, new structural health monitoring systems must be developed that are automated, highly accurate, minimally invasive, and cost effective. Three-dimensional (3D) digital image correlation (DIC) systems possess the capability of extracting full-field strain, displacement, and geometry profiles. Furthermore, as this measurement technique is implemented within an Unmanned Aerial Vehicle (UAV) the capability to expedite the optical-based measurement process is increased as well as the infrastructure downtime being reduced. These resulting integrity maps of the structure of interest can be easily interpreted by trained personal. Within this paper, the feasibility of performing DIC measurements using a pair of cameras installed on a UAV is shown. Performance is validated with in-flight measurements. Also, full-field displacement monitoring, 3D measurement stitching, and 3D point-tracking techniques are employed in conjunction with 3D mapping and data management software. The results of these experiments show that the combination of autonomous flight with 3D DIC and other non-contact measurement systems provides a highly valuable and effective civil inspection platform.

Applicability of New Approaches of Sensor Orientation to Micro Aerial Vehicles

NASA Astrophysics Data System (ADS)

Rehak, M.; Skaloud, J.

2016-06-01

This study highlights the benefits of precise aerial position and attitude control in the context of mapping with Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline inspections or mapping of large areas with homogeneous surface structure, e.g. forests or agricultural fields. There, accurate aerial control plays a major role in successful terrain reconstruction and artifact-free ortophoto generation. The presented experiments focus on new approaches of aerial control. We confirm practically that the relative aerial position and attitude control can improve accuracy in difficult mapping scenarios. Indeed, the relative orientation method represents an attractive alternative in the context of MAVs for two reasons. First, the procedure is somewhat simplified, e.g. the angular misalignment, so called boresight, between the camera and the inertial measurement unit (IMU) does not have to be determined and, second, the effect of possible systematic errors in satellite positioning (e.g. due to multipath and/or incorrect recovery of differential carrier-phase ambiguities) is mitigated. First, we present a typical mapping project over an agricultural field and second, we perform a corridor road mapping. We evaluate the proposed methods in scenarios with and without automated image observations. We investigate a recently proposed concept where adjustment is performed using image observations limited to ground control and check points, so called fast aerial triangulation (Fast AT). In this context we show that accurate aerial control (absolute or relative) together with a few image observations can deliver accurate results comparable to classical aerial triangulation with thousands of image measurements. This procedure in turns reduces the demands on processing time and the requirements on the existence of surface texture. Finally, we compare the above mentioned procedures with direct sensor

Neural-network classifiers for automatic real-world aerial image recognition

NASA Astrophysics Data System (ADS)

Greenberg, Shlomo; Guterman, Hugo

1996-08-01

We describe the application of the multilayer perceptron (MLP) network and a version of the adaptive resonance theory version 2-A (ART 2-A) network to the problem of automatic aerial image recognition (AAIR). The classification of aerial images, independent of their positions and orientations, is required for automatic tracking and target recognition. Invariance is achieved by the use of different invariant feature spaces in combination with supervised and unsupervised neural networks. The performance of neural-network-based classifiers in conjunction with several types of invariant AAIR global features, such as the Fourier-transform space, Zernike moments, central moments, and polar transforms, are examined. The advantages of this approach are discussed. The performance of the MLP network is compared with that of a classical correlator. The MLP neural-network correlator outperformed the binary phase-only filter (BPOF) correlator. It was found that the ART 2-A distinguished itself with its speed and its low number of required training vectors. However, only the MLP classifier was able to deal with a combination of shift and rotation geometric distortions.

Neural-network classifiers for automatic real-world aerial image recognition.

PubMed

Greenberg, S; Guterman, H

1996-08-10

We describe the application of the multilayer perceptron (MLP) network and a version of the adaptive resonance theory version 2-A (ART 2-A) network to the problem of automatic aerial image recognition (AAIR). The classification of aerial images, independent of their positions and orientations, is required for automatic tracking and target recognition. Invariance is achieved by the use of different invariant feature spaces in combination with supervised and unsupervised neural networks. The performance of neural-network-based classifiers in conjunction with several types of invariant AAIR global features, such as the Fourier-transform space, Zernike moments, central moments, and polar transforms, are examined. The advantages of this approach are discussed. The performance of the MLP network is compared with that of a classical correlator. The MLP neural-network correlator outperformed the binary phase-only filter (BPOF) correlator. It was found that the ART 2-A distinguished itself with its speed and its low number of required training vectors. However, only the MLP classifier was able to deal with a combination of shift and rotation geometric distortions.

Region Three Aerial Measurement System Flight Planning Tool - 12006

DOE Office of Scientific and Technical Information (OSTI.GOV)

Messick, Chuck; Pham, Minh; Smith, Ron

The Region 3 Aerial Measurement System Flight Planning Tool is used by the National Nuclear Security Agency (NNSA), United States Department of Energy, Radiological Assistance Program, Region 3, to respond to emergency radiological situations. The tool automates the flight planning package process while decreasing Aerial Measuring System response times and decreases the potential for human error. Deployment of the Region Three Aerial Measurement System Flight Planning Tool has resulted in an immediate improvement to the flight planning process in that time required for mission planning has been reduced from 1.5 hours to 15 minutes. Anecdotally, the RAP team reports thatmore » the rate of usable data acquired during surveys has improved from 40-60 percent to over 90 percent since they began using the tool. Though the primary product of the flight planning tool is a pdf format document for use by the aircraft flight crew, the RAP team has begun carrying their laptop computer on the aircraft during missions. By connecting a Global Positioning System (GPS) device to the laptop and using ESRI ArcMap's GPS tool bar to overlay the aircraft position directly on the flight plan in real time, the RAP team can evaluate and correct the aircraft position as the mission is executed. (authors)« less

Retrieve polarization aberration from image degradation: a new measurement method in DUV lithography

NASA Astrophysics Data System (ADS)

Xiang, Zhongbo; Li, Yanqiu

2017-10-01

Detailed knowledge of polarization aberration (PA) of projection lens in higher-NA DUV lithographic imaging is necessary due to its impact to imaging degradations, and precise measurement of PA is conductive to computational lithography techniques such as RET and OPC. Current in situ measurement method of PA thorough the detection of degradations of aerial images need to do linear approximation and apply the assumption of 3-beam/2-beam interference condition. The former approximation neglects the coupling effect of the PA coefficients, which would significantly influence the accuracy of PA retrieving. The latter assumption restricts the feasible pitch of test masks in higher-NA system, conflicts with the Kirhhoff diffraction model of test mask used in retrieving model, and introduces 3D mask effect as a source of retrieving error. In this paper, a new in situ measurement method of PA is proposed. It establishes the analytical quadratic relation between the PA coefficients and the degradations of aerial images of one-dimensional dense lines in coherent illumination through vector aerial imaging, which does not rely on the assumption of 3-beam/2- beam interference and linear approximation. In this case, the retrieval of PA from image degradation can be convert from the nonlinear system of m-quadratic equations to a multi-objective quadratic optimization problem, and finally be solved by nonlinear least square method. Some preliminary simulation results are given to demonstrate the correctness and accuracy of the new PA retrieving model.

Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

PubMed

Huang, Rongyong; Zheng, Shunyi; Hu, Kun

2018-06-01

Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4⁻1/2 (0.17⁻0.27 m) and 1/8⁻1/4 (0.10⁻0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.

Film cameras or digital sensors? The challenge ahead for aerial imaging

USGS Publications Warehouse

Light, D.L.

1996-01-01

Cartographic aerial cameras continue to play the key role in producing quality products for the aerial photography business, and specifically for the National Aerial Photography Program (NAPP). One NAPP photograph taken with cameras capable of 39 lp/mm system resolution can contain the equivalent of 432 million pixels at 11 ??m spot size, and the cost is less than $75 per photograph to scan and output the pixels on a magnetic storage medium. On the digital side, solid state charge coupled device linear and area arrays can yield quality resolution (7 to 12 ??m detector size) and a broader dynamic range. If linear arrays are to compete with film cameras, they will require precise attitude and positioning of the aircraft so that the lines of pixels can be unscrambled and put into a suitable homogeneous scene that is acceptable to an interpreter. Area arrays need to be much larger than currently available to image scenes competitive in size with film cameras. Analysis of the relative advantages and disadvantages of the two systems show that the analog approach is more economical at present. However, as arrays become larger, attitude sensors become more refined, global positioning system coordinate readouts become commonplace, and storage capacity becomes more affordable, the digital camera may emerge as the imaging system for the future. Several technical challenges must be overcome if digital sensors are to advance to where they can support mapping, charting, and geographic information system applications.

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

Comparison of binary mask defect printability analysis using virtual stepper system and aerial image microscope system

NASA Astrophysics Data System (ADS)

Phan, Khoi A.; Spence, Chris A.; Dakshina-Murthy, S.; Bala, Vidya; Williams, Alvina M.; Strener, Steve; Eandi, Richard D.; Li, Junling; Karklin, Linard

1999-12-01

As advanced process technologies in the wafer fabs push the patterning processes toward lower k1 factor for sub-wavelength resolution printing, reticles are required to use optical proximity correction (OPC) and phase-shifted mask (PSM) for resolution enhancement. For OPC/PSM mask technology, defect printability is one of the major concerns. Current reticle inspection tools available on the market sometimes are not capable of consistently differentiating between an OPC feature and a true random defect. Due to the process complexity and high cost associated with the making of OPC/PSM reticles, it is important for both mask shops and lithography engineers to understand the impact of different defect types and sizes to the printability. Aerial Image Measurement System (AIMS) has been used in the mask shops for a number of years for reticle applications such as aerial image simulation and transmission measurement of repaired defects. The Virtual Stepper System (VSS) provides an alternative method to do defect printability simulation and analysis using reticle images captured by an optical inspection or review system. In this paper, pre- programmed defects and repairs from a Defect Sensitivity Monitor (DSM) reticle with 200 nm minimum features (at 1x) will be studied for printability. The simulated resist lines by AIMS and VSS are both compared to SEM images of resist wafers qualitatively and quantitatively using CD verification.Process window comparison between unrepaired and repaired defects for both good and bad repair cases will be shown. The effect of mask repairs to resist pattern images for the binary mask case will be discussed. AIMS simulation was done at the International Sematech, Virtual stepper simulation at Zygo and resist wafers were processed at AMD-Submicron Development Center using a DUV lithographic process for 0.18 micrometer Logic process technology.

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 5 : aerial bridge deck imaging data collection and software revision.

DOT National Transportation Integrated Search

2012-02-01

For rapid deployment of bridge scan missions, sub-inch aerial imaging using small format aerial photography : is suggested. Under-belly photography is used to generate high resolution aerial images that can be geo-referenced and : used for quantifyin...

Aerial sampling using drones for measuring trace gases

NASA Astrophysics Data System (ADS)

Chang, Chih-Chung; Wang, Jia-Lin; Chang, Chih-Yuan; Lin, Ming-Ren; Ou-Yang, Chang-Feng; Pan, Xiang-Xu; Lin, Neng-Huei

2017-04-01

Aerial and ground-level samples were simultaneously collected at the northern tip of Taiwan, Cape Fuguei, which is commonly served as a receptor site to receive air parcels from East Asia, Asian continent, the northwest Pacific Ocean and the island of Taiwan itself. Both aerial and surface samples were analyzed for 106 volatile organic compounds (VOCs) and divided into three categories as follows: 1. the total concentrations of 106 VOC (T-VOC) at 300-m height that are lower than the T-VOC level at the surface (Category A), 2. T-VOC concentrations at 300-m that are higher than those at the surface (Category B), and 3. comparable concentrations (Category C). Ten VOCs were exploited as tracers for a variety of emission sources linking to possible sources and transport routes of airborne pollutants. The first two categories A and B showed significant differences in the observed composition and concentrations of tracers between aerial and ground-level samples, implying that the pollutants at different heights may have resulted from different sources and poor air mixing, despite only a 300-m difference in vertical height. In contrast, Category C showed good vertical mixing, as indicated by the comparable concentrations between the aerial and surface measurements. Since the three categories occurred in specific meteorological conditions (between, prior to, and after cold fronts), respectively, it suggests that varied prevailing meteorology controlled the distribution and transport of airborne pollutants. Unlike sampling commonly performed at the surface, this study uses aerial sampling to demonstrate that layered structures under different meteorological conditions. Sampling aloft in lower boundary layer avoids samples being over-influenced by the close-by surface sources such as traffic to reveal signatures of a broader region.

Draper Laboratory small autonomous aerial vehicle

NASA Astrophysics Data System (ADS)

DeBitetto, Paul A.; Johnson, Eric N.; Bosse, Michael C.; Trott, Christian A.

1997-06-01

The Charles Stark Draper Laboratory, Inc. and students from Massachusetts Institute of Technology and Boston University have cooperated to develop an autonomous aerial vehicle that won the 1996 International Aerial Robotics Competition. This paper describes the approach, system architecture and subsystem designs for the entry. This entry represents a combination of many technology areas: navigation, guidance, control, vision processing, human factors, packaging, power, real-time software, and others. The aerial vehicle, an autonomous helicopter, performs navigation and control functions using multiple sensors: differential GPS, inertial measurement unit, sonar altimeter, and a flux compass. The aerial transmits video imagery to the ground. A ground based vision processor converts the image data into target position and classification estimates. The system was designed, built, and flown in less than one year and has provided many lessons about autonomous vehicle systems, several of which are discussed. In an appendix, our current research in augmenting the navigation system with vision- based estimates is presented.

Detection of rice sheath blight using an unmanned aerial system with high-resolution color and multispectral imaging.

PubMed

Zhang, Dongyan; Zhou, Xingen; Zhang, Jian; Lan, Yubin; Xu, Chao; Liang, Dong

2018-01-01

Detection and monitoring are the first essential step for effective management of sheath blight (ShB), a major disease in rice worldwide. Unmanned aerial systems have a high potential of being utilized to improve this detection process since they can reduce the time needed for scouting for the disease at a field scale, and are affordable and user-friendly in operation. In this study, a commercialized quadrotor unmanned aerial vehicle (UAV), equipped with digital and multispectral cameras, was used to capture imagery data of research plots with 67 rice cultivars and elite lines. Collected imagery data were then processed and analyzed to characterize the development of ShB and quantify different levels of the disease in the field. Through color features extraction and color space transformation of images, it was found that the color transformation could qualitatively detect the infected areas of ShB in the field plots. However, it was less effective to detect different levels of the disease. Five vegetation indices were then calculated from the multispectral images, and ground truths of disease severity and GreenSeeker measured NDVI (Normalized Difference Vegetation Index) were collected. The results of relationship analyses indicate that there was a strong correlation between ground-measured NDVIs and image-extracted NDVIs with the R2 of 0.907 and the root mean square error (RMSE) of 0.0854, and a good correlation between image-extracted NDVIs and disease severity with the R2 of 0.627 and the RMSE of 0.0852. Use of image-based NDVIs extracted from multispectral images could quantify different levels of ShB in the field plots with an accuracy of 63%. These results demonstrate that a customer-grade UAV integrated with digital and multispectral cameras can be an effective tool to detect the ShB disease at a field scale.

a New Paradigm for Matching - and Aerial Images

NASA Astrophysics Data System (ADS)

Koch, T.; Zhuo, X.; Reinartz, P.; Fraundorfer, F.

2016-06-01

This paper investigates the performance of SIFT-based image matching regarding large differences in image scaling and rotation, as this is usually the case when trying to match images captured from UAVs and airplanes. This task represents an essential step for image registration and 3d-reconstruction applications. Various real world examples presented in this paper show that SIFT, as well as A-SIFT perform poorly or even fail in this matching scenario. Even if the scale difference in the images is known and eliminated beforehand, the matching performance suffers from too few feature point detections, ambiguous feature point orientations and rejection of many correct matches when applying the ratio-test afterwards. Therefore, a new feature matching method is provided that overcomes these problems and offers thousands of matches by a novel feature point detection strategy, applying a one-to-many matching scheme and substitute the ratio-test by adding geometric constraints to achieve geometric correct matches at repetitive image regions. This method is designed for matching almost nadir-directed images with low scene depth, as this is typical in UAV and aerial image matching scenarios. We tested the proposed method on different real world image pairs. While standard SIFT failed for most of the datasets, plenty of geometrical correct matches could be found using our approach. Comparing the estimated fundamental matrices and homographies with ground-truth solutions, mean errors of few pixels can be achieved.

aerial and ground measurements of emissions from agricultural and forest burns

EPA Science Inventory

This poster describes our measurement capabilities, particularly as they relate to interests within Region 7. Aerial instrumentation systems are discussed and field measurement campaigns are described in text and photos.

D Surface Generation from Aerial Thermal Imagery

NASA Astrophysics Data System (ADS)

Khodaei, B.; Samadzadegan, F.; Dadras Javan, F.; Hasani, H.

2015-12-01

Aerial thermal imagery has been recently applied to quantitative analysis of several scenes. For the mapping purpose based on aerial thermal imagery, high accuracy photogrammetric process is necessary. However, due to low geometric resolution and low contrast of thermal imaging sensors, there are some challenges in precise 3D measurement of objects. In this paper the potential of thermal video in 3D surface generation is evaluated. In the pre-processing step, thermal camera is geometrically calibrated using a calibration grid based on emissivity differences between the background and the targets. Then, Digital Surface Model (DSM) generation from thermal video imagery is performed in four steps. Initially, frames are extracted from video, then tie points are generated by Scale-Invariant Feature Transform (SIFT) algorithm. Bundle adjustment is then applied and the camera position and orientation parameters are determined. Finally, multi-resolution dense image matching algorithm is used to create 3D point cloud of the scene. Potential of the proposed method is evaluated based on thermal imaging cover an industrial area. The thermal camera has 640×480 Uncooled Focal Plane Array (UFPA) sensor, equipped with a 25 mm lens which mounted in the Unmanned Aerial Vehicle (UAV). The obtained results show the comparable accuracy of 3D model generated based on thermal images with respect to DSM generated from visible images, however thermal based DSM is somehow smoother with lower level of texture. Comparing the generated DSM with the 9 measured GCPs in the area shows the Root Mean Square Error (RMSE) value is smaller than 5 decimetres in both X and Y directions and 1.6 meters for the Z direction.

Looking for an old aerial photograph

USGS Publications Warehouse

,

1997-01-01

Attempts to photograph the surface of the Earth date from the 1800's, when photographers attached cameras to balloons, kites, and even pigeons. Today, aerial photographs and satellite images are commonplace. The rate of acquiring aerial photographs and satellite images has increased rapidly in recent years. Views of the Earth obtained from aircraft or satellites have become valuable tools to Government resource planners and managers, land-use experts, environmentalists, engineers, scientists, and a wide variety of other users. Many people want historical aerial photographs for business or personal reasons. They may want to locate the boundaries of an old farm or a piece of family property. Or they may want a photograph as a record of changes in their neighborhood, or as a gift. The U.S. Geological Survey (USGS) maintains the Earth Science Information Centers (ESIC?s) to sell aerial photographs, remotely sensed images from satellites, a wide array of digital geographic and cartographic data, as well as the Bureau?s wellknown maps. Declassified photographs from early spy satellites were recently added to the ESIC offerings of historical images. Using the Aerial Photography Summary Record System database, ESIC researchers can help customers find imagery in the collections of other Federal agencies and, in some cases, those of private companies that specialize in esoteric products.

Integration of aerial imaging and variable-rate technology for site-specific aerial herbicide application

USDA-ARS?s Scientific Manuscript database

As remote sensing and variable rate technology are becoming more available for aerial applicators, practical methodologies on effective integration of these technologies are needed for site-specific aerial applications of crop production and protection materials. The objectives of this study were to...

Oblique Aerial Photography Tool for Building Inspection and Damage Assessment

NASA Astrophysics Data System (ADS)

Murtiyoso, A.; Remondino, F.; Rupnik, E.; Nex, F.; Grussenmeyer, P.

2014-11-01

Aerial photography has a long history of being employed for mapping purposes due to some of its main advantages, including large area imaging from above and minimization of field work. Since few years multi-camera aerial systems are becoming a practical sensor technology across a growing geospatial market, as complementary to the traditional vertical views. Multi-camera aerial systems capture not only the conventional nadir views, but also tilted images at the same time. In this paper, a particular use of such imagery in the field of building inspection as well as disaster assessment is addressed. The main idea is to inspect a building from four cardinal directions by using monoplotting functionalities. The developed application allows to measure building height and distances and to digitize man-made structures, creating 3D surfaces and building models. The realized GUI is capable of identifying a building from several oblique points of views, as well as calculates the approximate height of buildings, ground distances and basic vectorization. The geometric accuracy of the results remains a function of several parameters, namely image resolution, quality of available parameters (DEM, calibration and orientation values), user expertise and measuring capability.

Direct Penguin Counting Using Unmanned Aerial Vehicle Image

NASA Astrophysics Data System (ADS)

Hyun, C. U.; Kim, H. C.; Kim, J. H.; Hong, S. G.

2015-12-01

This study presents an application of unmanned aerial vehicle (UAV) images to monitor penguin colony in Baton Peninsula, King George Island, Antarctica. The area around Narębski Point located on the southeast coast of Barton Peninsula was designated as Antarctic Specially Protected Area No. 171 (ASPA 171), and Chinstrap and Gentoo penguins inhabit in this area. The UAV images were acquired in a part of ASPA 171 from four flights in a single day, Jan 18, 2014. About 360 images were mosaicked as an image of about 3 cm spatial resolution and then a subset including representative penguin rookeries was selected. The subset image was segmented based on gradient map of pixel values, and spectral and spatial attributes were assigned to each segment. The object based image analysis (OBIA) was conducted with consideration of spectral attributes including mean and minimum values of each segment and various shape attributes such as area, length, compactness and roundness to detect individual penguin. The segments indicating individual penguin were effectively detected on rookeries with high contrasts in the spectral and shape attributes. The importance of periodic and precise monitoring of penguins has been recognized because variations of their populations reflect environmental changes and disturbance from human activities. Utilization of very high resolution imaging method shown in this study can be applied to other penguin habitats in Antarctica, and the results will be able to support establishing effective environmental management plans.

Advanced Image Processing of Aerial Imagery

NASA Technical Reports Server (NTRS)

Woodell, Glenn; Jobson, Daniel J.; Rahman, Zia-ur; Hines, Glenn

2006-01-01

Aerial imagery of the Earth is an invaluable tool for the assessment of ground features, especially during times of disaster. Researchers at the NASA Langley Research Center have developed techniques which have proven to be useful for such imagery. Aerial imagery from various sources, including Langley's Boeing 757 Aries aircraft, has been studied extensively. This paper discusses these studies and demonstrates that better-than-observer imagery can be obtained even when visibility is severely compromised. A real-time, multi-spectral experimental system will be described and numerous examples will be shown.

Observation of coral reefs on Ishigaki Island, Japan, using Landsat TM images and aerial photographs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matsunaga, Tsuneo; Kayanne, Hajime

1997-06-01

Ishigaki Island is located at the southwestern end of Japanese Islands and famous for its fringing coral reefs. More than twenty LANDSAT TM images in twelve years and aerial photographs taken on 1977 and 1994 were used to survey two shallow reefs on this island, Shiraho and Kabira. Intensive field surveys were also conducted in 1995. All satellite images of Shiraho were geometrically corrected and overlaid to construct a multi-date satellite data set. The effects of solar elevation and tide on satellite imagery were studied with this data set. The comparison of aerial and satellite images indicated that significant changesmore » occurred between 1977 and 1984 in Kabira: rapid formation in the western part and decrease in the eastern part of dark patches. The field surveys revealed that newly formed dark patches in the west contain young corals. These results suggest that remote sensing is useful for not only mapping but also monitoring of shallow coral reefs.« less

Feature-based registration of historical aerial images by Area Minimization

NASA Astrophysics Data System (ADS)

Nagarajan, Sudhagar; Schenk, Toni

2016-06-01

The registration of historical images plays a significant role in assessing changes in land topography over time. By comparing historical aerial images with recent data, geometric changes that have taken place over the years can be quantified. However, the lack of ground control information and precise camera parameters has limited scientists' ability to reliably incorporate historical images into change detection studies. Other limitations include the methods of determining identical points between recent and historical images, which has proven to be a cumbersome task due to continuous land cover changes. Our research demonstrates a method of registering historical images using Time Invariant Line (TIL) features. TIL features are different representations of the same line features in multi-temporal data without explicit point-to-point or straight line-to-straight line correspondence. We successfully determined the exterior orientation of historical images by minimizing the area formed between corresponding TIL features in recent and historical images. We then tested the feasibility of the approach with synthetic and real data and analyzed the results. Based on our analysis, this method shows promise for long-term 3D change detection studies.

Application of high resolution images from unmanned aerial vehicles for hydrology and range science

USDA-ARS?s Scientific Manuscript database

A common problem in many natural resource disciplines is the lack of high-enough spatial resolution images that can be used for monitoring and modeling purposes. Advances have been made in the utilization of Unmanned Aerial Vehicles (UAVs) in hydrology and rangeland science. By utilizing low fligh...

Aerial Images from AN Uav System: 3d Modeling and Tree Species Classification in a Park Area

NASA Astrophysics Data System (ADS)

Gini, R.; Passoni, D.; Pinto, L.; Sona, G.

2012-07-01

The use of aerial imagery acquired by Unmanned Aerial Vehicles (UAVs) is scheduled within the FoGLIE project (Fruition of Goods Landscape in Interactive Environment): it starts from the need to enhance the natural, artistic and cultural heritage, to produce a better usability of it by employing audiovisual movable systems of 3D reconstruction and to improve monitoring procedures, by using new media for integrating the fruition phase with the preservation ones. The pilot project focus on a test area, Parco Adda Nord, which encloses various goods' types (small buildings, agricultural fields and different tree species and bushes). Multispectral high resolution images were taken by two digital compact cameras: a Pentax Optio A40 for RGB photos and a Sigma DP1 modified to acquire the NIR band. Then, some tests were performed in order to analyze the UAV images' quality with both photogrammetric and photo-interpretation purposes, to validate the vector-sensor system, the image block geometry and to study the feasibility of tree species classification. Many pre-signalized Control Points were surveyed through GPS to allow accuracy analysis. Aerial Triangulations (ATs) were carried out with photogrammetric commercial software, Leica Photogrammetry Suite (LPS) and PhotoModeler, with manual or automatic selection of Tie Points, to pick out pros and cons of each package in managing non conventional aerial imagery as well as the differences in the modeling approach. Further analysis were done on the differences between the EO parameters and the corresponding data coming from the on board UAV navigation system.

Aerial Video Imaging

NASA Technical Reports Server (NTRS)

1991-01-01

When Michael Henry wanted to start an aerial video service, he turned to Johnson Space Center for assistance. Two NASA engineers - one had designed and developed TV systems in Apollo, Skylab, Apollo- Soyuz and Space Shuttle programs - designed a wing-mounted fiberglass camera pod. Camera head and angles are adjustable, and the pod is shaped to reduce vibration. The controls are located so a solo pilot can operate the system. A microprocessor displays latitude, longitude, and bearing, and a GPS receiver provides position data for possible legal references. The service has been successfully utilized by railroads, oil companies, real estate companies, etc.

Detection of Laurel Wilt Disease in Avocado Using Low Altitude Aerial Imaging

PubMed Central

de Castro, Ana I.; Ehsani, Reza; Ploetz, Randy C.; Crane, Jonathan H.; Buchanon, Sherrie

2015-01-01

Laurel wilt is a lethal disease of plants in the Lauraceae plant family, including avocado (Persea americana). This devastating disease has spread rapidly along the southeastern seaboard of the United States and has begun to affect commercial avocado production in Florida. The main objective of this study was to evaluate the potential to discriminate laurel wilt-affected avocado trees using aerial images taken with a modified camera during helicopter surveys at low-altitude in the commercial avocado production area. The ability to distinguish laurel wilt-affected trees from other factors that produce similar external symptoms was also studied. RmodGB digital values of healthy trees and laurel wilt-affected trees, as well as fruit stress and vines covering trees were used to calculate several vegetation indices (VIs), band ratios, and VI combinations. These indices were subjected to analysis of variance (ANOVA) and an M-statistic was performed in order to quantify the separability of those classes. Significant differences in spectral values among laurel wilt affected and healthy trees were observed in all vegetation indices calculated, although the best results were achieved with Excess Red (ExR), (Red–Green) and Combination 1 (COMB1) in all locations. B/G showed a very good potential for separate the other factors with symptoms similar to laurel wilt-affected trees, such as fruit stress and vines covering trees, from laurel wilt-affected trees. These consistent results prove the usefulness of using a modified camera (RmodGB) to discriminate laurel wilt-affected avocado trees from healthy trees, as well as from other factors that cause the same symptoms and suggest performing the classification in further research. According to our results, ExR and B/G should be utilized to develop an algorithm or decision rules to classify aerial images, since they showed the highest capacity to discriminate laurel wilt-affected trees. This methodology may allow the rapid

Detection of laurel wilt disease in avocado using low altitude aerial imaging.

PubMed

de Castro, Ana I; Ehsani, Reza; Ploetz, Randy C; Crane, Jonathan H; Buchanon, Sherrie

2015-01-01

Laurel wilt is a lethal disease of plants in the Lauraceae plant family, including avocado (Persea americana). This devastating disease has spread rapidly along the southeastern seaboard of the United States and has begun to affect commercial avocado production in Florida. The main objective of this study was to evaluate the potential to discriminate laurel wilt-affected avocado trees using aerial images taken with a modified camera during helicopter surveys at low-altitude in the commercial avocado production area. The ability to distinguish laurel wilt-affected trees from other factors that produce similar external symptoms was also studied. RmodGB digital values of healthy trees and laurel wilt-affected trees, as well as fruit stress and vines covering trees were used to calculate several vegetation indices (VIs), band ratios, and VI combinations. These indices were subjected to analysis of variance (ANOVA) and an M-statistic was performed in order to quantify the separability of those classes. Significant differences in spectral values among laurel wilt affected and healthy trees were observed in all vegetation indices calculated, although the best results were achieved with Excess Red (ExR), (Red-Green) and Combination 1 (COMB1) in all locations. B/G showed a very good potential for separate the other factors with symptoms similar to laurel wilt-affected trees, such as fruit stress and vines covering trees, from laurel wilt-affected trees. These consistent results prove the usefulness of using a modified camera (RmodGB) to discriminate laurel wilt-affected avocado trees from healthy trees, as well as from other factors that cause the same symptoms and suggest performing the classification in further research. According to our results, ExR and B/G should be utilized to develop an algorithm or decision rules to classify aerial images, since they showed the highest capacity to discriminate laurel wilt-affected trees. This methodology may allow the rapid detection

Suitability of low cost commercial off-the-shelf aerial platforms and consumer grade digital cameras for small format aerial photography

NASA Astrophysics Data System (ADS)

Turley, Anthony Allen

Many research projects require the use of aerial images. Wetlands evaluation, crop monitoring, wildfire management, environmental change detection, and forest inventory are but a few of the applications of aerial imagery. Low altitude Small Format Aerial Photography (SFAP) is a bridge between satellite and man-carrying aircraft image acquisition and ground-based photography. The author's project evaluates digital images acquired using low cost commercial digital cameras and standard model airplanes to determine their suitability for remote sensing applications. Images from two different sites were obtained. Several photo missions were flown over each site, acquiring images in the visible and near infrared electromagnetic bands. Images were sorted and analyzed to select those with the least distortion, and blended together with Microsoft Image Composite Editor. By selecting images taken within minutes apart, radiometric qualities of the images were virtually identical, yielding no blend lines in the composites. A commercial image stitching program, Autopano Pro, was purchased during the later stages of this study. Autopano Pro was often able to mosaic photos that the free Image Composite Editor was unable to combine. Using telemetry data from an onboard data logger, images were evaluated to calculate scale and spatial resolution. ERDAS ER Mapper and ESRI ArcGIS were used to rectify composite images. Despite the limitations inherent in consumer grade equipment, images of high spatial resolution were obtained. Mosaics of as many as 38 images were created, and the author was able to record detailed aerial images of forest and wetland areas where foot travel was impractical or impossible.

Measurement of the Energy-Dependent Angular Response of the ARES Detector System and Application to Aerial Imaging

NASA Astrophysics Data System (ADS)

Joshi, Tenzing H. Y.; Quiter, Brian J.; Maltz, Jonathan S.; Bandstra, Mark S.; Haefner, Andrew; Eikmeier, Nicole; Wagner, Eric; Luke, Tanushree; Malchow, Russell; McCall, Karen

2017-07-01

The Airborne Radiological Enhanced-sensor System (ARES) includes a prototype helicopter-borne CsI(Na) detector array that has been developed as part of the DHS Domestic Nuclear Detection Office Advanced Technology Demonstration. The detector system geometry comprises two pairs of 23-detector arrays designed to function as active masks, providing additional angular resolution of measured gamma rays in the roll dimension. Experimental measurements, using five radioisotopes (137Cs, 60Co, 241Am, 131I, and 99mTc), were performed to map the detector response in both roll and pitch dimensions. This paper describes the acquisition and analysis of these characterization measurements, calculation of the angular response of the ARES system, and how this response function is used to improve aerial detection and localization of radiological and nuclear threat sources.

Image degradation in aerial imagery duplicates. [photographic processing of photographic film and reproduction (copying)

NASA Technical Reports Server (NTRS)

Lockwood, H. E.

1975-01-01

A series of Earth Resources Aircraft Program data flights were made over an aerial test range in Arizona for the evaluation of large cameras. Specifically, both medium altitude and high altitude flights were made to test and evaluate a series of color as well as black-and-white films. Image degradation, inherent in duplication processing, was studied. Resolution losses resulting from resolution characteristics of the film types are given. Color duplicates, in general, are shown to be degraded more than black-and-white films because of the limitations imposed by available aerial color duplicating stock. Results indicate that a greater resolution loss may be expected when the original has higher resolution. Photographs of the duplications are shown.

Algorithm for automatic image dodging of unmanned aerial vehicle images using two-dimensional radiometric spatial attributes

NASA Astrophysics Data System (ADS)

Li, Wenzhuo; Sun, Kaimin; Li, Deren; Bai, Ting

2016-07-01

Unmanned aerial vehicle (UAV) remote sensing technology has come into wide use in recent years. The poor stability of the UAV platform, however, produces more inconsistencies in hue and illumination among UAV images than other more stable platforms. Image dodging is a process used to reduce these inconsistencies caused by different imaging conditions. We propose an algorithm for automatic image dodging of UAV images using two-dimensional radiometric spatial attributes. We use object-level image smoothing to smooth foreground objects in images and acquire an overall reference background image by relative radiometric correction. We apply the Contourlet transform to separate high- and low-frequency sections for every single image, and replace the low-frequency section with the low-frequency section extracted from the corresponding region in the overall reference background image. We apply the inverse Contourlet transform to reconstruct the final dodged images. In this process, a single image must be split into reasonable block sizes with overlaps due to large pixel size. Experimental mosaic results show that our proposed method reduces the uneven distribution of hue and illumination. Moreover, it effectively eliminates dark-bright interstrip effects caused by shadows and vignetting in UAV images while maximally protecting image texture information.

Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging

NASA Astrophysics Data System (ADS)

Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.

2017-12-01

In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four

Small unmanned aerial vehicles (micro-UAVs, drones) in plant ecology.

PubMed

Cruzan, Mitchell B; Weinstein, Ben G; Grasty, Monica R; Kohrn, Brendan F; Hendrickson, Elizabeth C; Arredondo, Tina M; Thompson, Pamela G

2016-09-01

Low-elevation surveys with small aerial drones (micro-unmanned aerial vehicles [UAVs]) may be used for a wide variety of applications in plant ecology, including mapping vegetation over small- to medium-sized regions. We provide an overview of methods and procedures for conducting surveys and illustrate some of these applications. Aerial images were obtained by flying a small drone along transects over the area of interest. Images were used to create a composite image (orthomosaic) and a digital surface model (DSM). Vegetation classification was conducted manually and using an automated routine. Coverage of an individual species was estimated from aerial images. We created a vegetation map for the entire region from the orthomosaic and DSM, and mapped the density of one species. Comparison of our manual and automated habitat classification confirmed that our mapping methods were accurate. A species with high contrast to the background matrix allowed adequate estimate of its coverage. The example surveys demonstrate that small aerial drones are capable of gathering large amounts of information on the distribution of vegetation and individual species with minimal impact to sensitive habitats. Low-elevation aerial surveys have potential for a wide range of applications in plant ecology.

Building Change Detection from Bi-Temporal Dense-Matching Point Clouds and Aerial Images.

PubMed

Pang, Shiyan; Hu, Xiangyun; Cai, Zhongliang; Gong, Jinqi; Zhang, Mi

2018-03-24

In this work, a novel building change detection method from bi-temporal dense-matching point clouds and aerial images is proposed to address two major problems, namely, the robust acquisition of the changed objects above ground and the automatic classification of changed objects into buildings or non-buildings. For the acquisition of changed objects above ground, the change detection problem is converted into a binary classification, in which the changed area above ground is regarded as the foreground and the other area as the background. For the gridded points of each period, the graph cuts algorithm is adopted to classify the points into foreground and background, followed by the region-growing algorithm to form candidate changed building objects. A novel structural feature that was extracted from aerial images is constructed to classify the candidate changed building objects into buildings and non-buildings. The changed building objects are further classified as "newly built", "taller", "demolished", and "lower" by combining the classification and the digital surface models of two periods. Finally, three typical areas from a large dataset are used to validate the proposed method. Numerous experiments demonstrate the effectiveness of the proposed algorithm.

Three dimensional monitoring of urban development by means of ortho-rectified aerial photographs and high-resolution satellite images.

PubMed

Ayhan, E; Erden, O; Gormus, E T

2008-12-01

Nowadays, cities are developing and changing rapidly due to the increases in the population and immigration. Rapid changing brings obligation to control the cities by planning. The satellite images and the aerial photographs enable us to track the urban development and provide the opportunity to get the current data about urban. With the help of these images, cities may have interrogated dynamic structures. This study is composed of three steps. In the first step, orthophoto images have been generated in order to track urban developments by using the aerial photographs and the satellite images. In this step, the panchromatic (PAN), the multi spectral (MS) and the pan-sharpened image of IKONOS satellite have been used as input satellite data and the accuracy of orthophoto images has been investigated in detail, in terms of digital elevation model (DEM), control points, input images and their properties. In the second step, a 3D city model with database has been generated with the help of orthophoto images and the vector layouts. And in the last step, up to date urban information obtained from 3D city model. This study shows that it is possible to detect the unlicensed buildings and the areas which are going to be nationalized and it also shows that it is easy to document the existing alterations in the cities with the help of current development plans and orthophoto images. And since accessing updated data is very essential to control development and monitor the temporal alterations in urban areas, in this study it is proven that the orthophoto images generated by using aerial photos and satellite images are very reliable to use in obtaining topographical information, in change detection and in city planning. When digital orthophoto images used with GIS, they provide quick decision control mechanisms and quick data collection. Besides, they help to find efficient solutions in a short time in the planning applications.

A case study of comparing radiometrically calibrated reflectance of an image mosaic from unmanned aerial system with that of a single image from manned aircraft over a same area

NASA Astrophysics Data System (ADS)

Shi, Yeyin; Thomasson, J. Alex; Yang, Chenghai; Cope, Dale; Sima, Chao

2017-05-01

Though sharing with many commonalities, one of the major differences between conventional high-altitude airborne remote sensing and low-altitude unmanned aerial system (UAS) based remote sensing is that the latter one has much smaller ground footprint for each image shot. To cover the same area on the ground, it requires the low-altitude UASbased platform to take many highly-overlapped images to produce a good mosaic, instead of just one or a few image shots by the high-altitude aerial platform. Such an UAS flight usually takes 10 to 30 minutes or even longer to complete; environmental lighting change during this time span cannot be ignored especially when spectral variations of various parts of a field are of interests. In this case study, we compared the visible reflectance of two aerial imagery - one generated from mosaicked UAS images, the other generated from a single image taken by a manned aircraft - over the same agricultural field to quantitatively evaluate their spectral variations caused by the different data acquisition strategies. Specifically, we (1) developed our customized ground calibration points (GCPs) and an associated radiometric calibration method for UAS data processing based on camera's sensitivity characteristics; (2) developed a basic comparison method for radiometrically calibrated data from the two aerial platforms based on regions of interests. We see this study as a starting point for a series of following studies to understand the environmental influence on UAS data and investigate the solutions to minimize such influence to ensure data quality.

Identification and measurement of shrub type vegetation on large scale aerial photography

NASA Technical Reports Server (NTRS)

Driscoll, R. S.

1970-01-01

Important range-shrub species were identified at acceptable levels of accuracy on large-scale 70 mm color and color infrared aerial photographs. Identification of individual shrubs was significantly higher, however, on color infrared. Photoscales smaller than 1:2400 had limited value except for mature individuals of relatively tall species, and then only if crown margins did not overlap and sharp contrast was evident between the species and background. Larger scale photos were required for low-growing species in dense stands. The crown cover for individual species was estimated from the aerial photos either with a measuring magnifier or a projected-scale micrometer. These crown cover measurements provide techniques for earth-resource analyses when used in conjunction with space and high-altitude remotely procured photos.

Image quality of the cat eye measured during retinal ganglion cell experiments.

PubMed

Bonds, A B; Enroth-Cugell, C; Pinto, L H

1972-01-01

1. The modulation transfer function (MTF) of the dioptrics of fifteen cat eyes was determined. The aerial image, formed by the eye of a standard object (a 0.5-1.0 degrees annulus), was photographed. The transmission of the film negative was measured with a scanning microdensitometer to yield the light distribution within the aerial image. Correcting for the double passage, this experimentally determined light distribution and the known object light distribution were used to obtain the MTF, applying Fourier methods. Each MTF was used to calculate the light distribution within the retinal image of stimuli of various geometry used in experiments on retinal ganglion cells in the same eye.2. When the eye was equipped with an artificial pupil of the same size as that used in the neurophysiological experiments (4.0-4.8 mm diam.) the MTF had fallen to 0.5 at 2.43 c/deg. When the pupil was removed the MTF had fallen to 0.5 at a much lower spatial frequency (1.0 c/deg). This shows that even when one uses an artificial pupil too large to provide optimal image quality there is a vast improvement over using no pupil.3. These image quality measurements were prompted by the need to know the actual stimulus image in experiments on the functional organization of the receptive field, a need exemplified in this paper by a few specific physiological results. The full neurophysiological results appear in the next two papers.

Fuzzy C-Means Algorithm for Segmentation of Aerial Photography Data Obtained Using Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Akinin, M. V.; Akinina, N. V.; Klochkov, A. Y.; Nikiforov, M. B.; Sokolova, A. V.

2015-05-01

The report reviewed the algorithm fuzzy c-means, performs image segmentation, give an estimate of the quality of his work on the criterion of Xie-Beni, contain the results of experimental studies of the algorithm in the context of solving the problem of drawing up detailed two-dimensional maps with the use of unmanned aerial vehicles. According to the results of the experiment concluded that the possibility of applying the algorithm in problems of decoding images obtained as a result of aerial photography. The considered algorithm can significantly break the original image into a plurality of segments (clusters) in a relatively short period of time, which is achieved by modification of the original k-means algorithm to work in a fuzzy task.

A Novel Approach to Measuring Glacier Motion Remotely using Aerial LiDAR

NASA Astrophysics Data System (ADS)

Telling, J. W.; Fountain, A. G.; Glennie, C. L.; Obryk, M.

2016-12-01

Glaciers play an important role in the Earth's climate system, affecting climate and ocean circulation at the largest scales, and contributing to runoff and sea level rise at local scales. A key variable is glacier motion and tracking motion is critical to understanding how flow responds to changes in boundary conditions and to testing predictive models of glacier behavior. Although field measurements of glacier motion have been collected since the 19th Century, field operations remain a slow, laborious, sometimes dangerous, task yielding only a few data points per glacier. In recent decades satellite imaging of glacier motion has proved very fruitful, but the spatial resolution of the imagery restricts applications to regional scale analyses. Here we assess the utility of using aerial LiDAR surveys and particle image velocimetry (PIV) as a method for tracking glacier motion over relatively small regions (<50km2). Five glaciers in Taylor Valley, Antarctica, were surveyed twice; the first LiDAR survey was conducted in 2001 and the second was conducted in 2014. The cold-dry climate conditions of Taylor Valley and the relatively slow motion of its polar glaciers (≤ 8m yr-1) preserve the surface roughness and limit the advected distance of the features making the 13-year interval between surveys sufficient for monitoring glacier motion. Initial results yield reasonable flow fields and show great promise. The range of flow speeds, surface roughness, and transient snow patches found on these glaciers provide a robust test of PIV methods. Results will be compared to field measurements of glacier velocity and to results from feature tracking, a common technique based on paired optical images. The merits of using this technique to measure glacier motion will be discussed in the context of these results. Applying PIV to LiDAR point clouds may offer a higher resolution data set of glacier velocity than satellite images or field measurements.

EROS main image file - A picture perfect database for Landsat imagery and aerial photography

NASA Technical Reports Server (NTRS)

Jack, R. F.

1984-01-01

The Earth Resources Observation System (EROS) Program was established by the U.S. Department of the Interior in 1966 under the administration of the Geological Survey. It is primarily concerned with the application of remote sensing techniques for the management of natural resources. The retrieval system employed to search the EROS database is called INORAC (Inquiry, Ordering, and Accounting). A description is given of the types of images identified in EROS, taking into account Landsat imagery, Skylab images, Gemini/Apollo photography, and NASA aerial photography. Attention is given to retrieval commands, geographic coordinate searching, refinement techniques, various online functions, and questions regarding the access to the EROS Main Image File.

Comparison of DSMs acquired by terrestrial laser scanning, UAV-based aerial images and ground-based optical images at the Super-Sauze landslide

NASA Astrophysics Data System (ADS)

Rothmund, Sabrina; Niethammer, Uwe; Walter, Marco; Joswig, Manfred

2013-04-01

In recent years, the high-resolution and multi-temporal 3D mapping of the Earth's surface using terrestrial laser scanning (TLS), ground-based optical images and especially low-cost UAV-based aerial images (Unmanned Aerial Vehicle) has grown in importance. This development resulted from the progressive technical improvement of the imaging systems and the freely available multi-view stereo (MVS) software packages. These different methods of data acquisition for the generation of accurate, high-resolution digital surface models (DSMs) were applied as part of an eight-week field campaign at the Super-Sauze landslide (South French Alps). An area of approximately 10,000 m² with long-term average displacement rates greater than 0.01 m/day has been investigated. The TLS-based point clouds were acquired at different viewpoints with an average point spacing between 10 to 40 mm and at different dates. On these days, more than 50 optical images were taken on points along a predefined line on the side part of the landslide by a low-cost digital compact camera. Additionally, aerial images were taken by a radio-controlled mini quad-rotor UAV equipped with another low-cost digital compact camera. The flight altitude ranged between 20 m and 250 m and produced a corresponding ground resolution between 0.6 cm and 7 cm. DGPS measurements were carried out as well in order to geo-reference and validate the point cloud data. To generate unscaled photogrammetric 3D point clouds from a disordered and tilted image set, we use the widespread open-source software package Bundler and PMVS2 (University of Washington). These multi-temporal DSMs are required on the one hand to determine the three-dimensional surface deformations and on the other hand it will be required for differential correction for orthophoto production. Drawing on the example of the acquired data at the Super-Sauze landslide, we demonstrate the potential but also the limitations of the photogrammetric point clouds. To

Image quality of the cat eye measured during retinal ganglion cell experiments

PubMed Central

Bonds, A. B.; Enroth-Cugell, Christina; Pinto, L. H.

1972-01-01

1. The modulation transfer function (MTF) of the dioptrics of fifteen cat eyes was determined. The aerial image, formed by the eye of a standard object (a 0·5-1·0° annulus), was photographed. The transmission of the film negative was measured with a scanning microdensitometer to yield the light distribution within the aerial image. Correcting for the double passage, this experimentally determined light distribution and the known object light distribution were used to obtain the MTF, applying Fourier methods. Each MTF was used to calculate the light distribution within the retinal image of stimuli of various geometry used in experiments on retinal ganglion cells in the same eye. 2. When the eye was equipped with an artificial pupil of the same size as that used in the neurophysiological experiments (4·0-4·8 mm diam.) the MTF had fallen to 0·5 at 2·43 c/deg. When the pupil was removed the MTF had fallen to 0·5 at a much lower spatial frequency (1·0 c/deg). This shows that even when one uses an artificial pupil too large to provide optimal image quality there is a vast improvement over using no pupil. 3. These image quality measurements were prompted by the need to know the actual stimulus image in experiments on the functional organization of the receptive field, a need exemplified in this paper by a few specific physiological results. The full neurophysiological results appear in the next two papers. ImagesFig. 3Fig. 4 PMID:5014105

Very high resolution aerial films

NASA Astrophysics Data System (ADS)

Becker, Rolf

1986-11-01

The use of very high resolution aerial films in aerial photography is evaluated. Commonly used panchromatic, color, and CIR films and their high resolution equivalents are compared. Based on practical experience and systematic investigations, the very high image quality and improved height accuracy that can be achieved using these films are demonstrated. Advantages to be gained from this improvement and operational restrictions encountered when using high resolution film are discussed.

Melon yield prediction using small unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Zhao, Tiebiao; Wang, Zhongdao; Yang, Qi; Chen, YangQuan

2017-05-01

Thanks to the development of camera technologies, small unmanned aerial systems (sUAS), it is possible to collect aerial images of field with more flexible visit, higher resolution and much lower cost. Furthermore, the performance of objection detection based on deeply trained convolutional neural networks (CNNs) has been improved significantly. In this study, we applied these technologies in the melon production, where high-resolution aerial images were used to count melons in the field and predict the yield. CNN-based object detection framework-Faster R-CNN is applied in the melon classification. Our results showed that sUAS plus CNNs were able to detect melons accurately in the late harvest season.

Moving object detection in top-view aerial videos improved by image stacking

NASA Astrophysics Data System (ADS)

Teutsch, Michael; Krüger, Wolfgang; Beyerer, Jürgen

2017-08-01

Image stacking is a well-known method that is used to improve the quality of images in video data. A set of consecutive images is aligned by applying image registration and warping. In the resulting image stack, each pixel has redundant information about its intensity value. This redundant information can be used to suppress image noise, resharpen blurry images, or even enhance the spatial image resolution as done in super-resolution. Small moving objects in the videos usually get blurred or distorted by image stacking and thus need to be handled explicitly. We use image stacking in an innovative way: image registration is applied to small moving objects only, and image warping blurs the stationary background that surrounds the moving objects. Our video data are coming from a small fixed-wing unmanned aerial vehicle (UAV) that acquires top-view gray-value images of urban scenes. Moving objects are mainly cars but also other vehicles such as motorcycles. The resulting images, after applying our proposed image stacking approach, are used to improve baseline algorithms for vehicle detection and segmentation. We improve precision and recall by up to 0.011, which corresponds to a reduction of the number of false positive and false negative detections by more than 3 per second. Furthermore, we show how our proposed image stacking approach can be implemented efficiently.

Measuring cloud thermodynamic phase with shortwave infrared imaging spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, David R.; McCubbin, Ian; Gao, Bo Cai

Shortwave Infrared imaging spectroscopy enables accurate remote mapping of cloud thermodynamic phase at high spatial resolution. We describe a measurement strategy to exploit signatures of liquid and ice absorption in cloud top apparent reflectance spectra from 1.4 to 1.8 μm. This signal is generally insensitive to confounding factors such as solar angles, view angles, and surface albedo. We first evaluate the approach in simulation and then apply it to airborne data acquired in the Calwater-2/ACAPEX campaign of Winter 2015. Here NASA’s “Classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) remotely observed diverse cloud formations while the U.S. Department of Energy ARMmore » Aerial Facility G-1 aircraft measured cloud integral and microphysical properties in situ. Finally, the coincident measurements demonstrate good separation of the thermodynamic phases for relatively homogeneous clouds.« less

Semantic labeling of high-resolution aerial images using an ensemble of fully convolutional networks

NASA Astrophysics Data System (ADS)

Sun, Xiaofeng; Shen, Shuhan; Lin, Xiangguo; Hu, Zhanyi

2017-10-01

High-resolution remote sensing data classification has been a challenging and promising research topic in the community of remote sensing. In recent years, with the rapid advances of deep learning, remarkable progress has been made in this field, which facilitates a transition from hand-crafted features designing to an automatic end-to-end learning. A deep fully convolutional networks (FCNs) based ensemble learning method is proposed to label the high-resolution aerial images. To fully tap the potentials of FCNs, both the Visual Geometry Group network and a deeper residual network, ResNet, are employed. Furthermore, to enlarge training samples with diversity and gain better generalization, in addition to the commonly used data augmentation methods (e.g., rotation, multiscale, and aspect ratio) in the literature, aerial images from other datasets are also collected for cross-scene learning. Finally, we combine these learned models to form an effective FCN ensemble and refine the results using a fully connected conditional random field graph model. Experiments on the ISPRS 2-D Semantic Labeling Contest dataset show that our proposed end-to-end classification method achieves an overall accuracy of 90.7%, a state-of-the-art in the field.

Automatic Feature Detection, Description and Matching from Mobile Laser Scanning Data and Aerial Imagery

NASA Astrophysics Data System (ADS)

Hussnain, Zille; Oude Elberink, Sander; Vosselman, George

2016-06-01

In mobile laser scanning systems, the platform's position is measured by GNSS and IMU, which is often not reliable in urban areas. Consequently, derived Mobile Laser Scanning Point Cloud (MLSPC) lacks expected positioning reliability and accuracy. Many of the current solutions are either semi-automatic or unable to achieve pixel level accuracy. We propose an automatic feature extraction method which involves utilizing corresponding aerial images as a reference data set. The proposed method comprise three steps; image feature detection, description and matching between corresponding patches of nadir aerial and MLSPC ortho images. In the data pre-processing step the MLSPC is patch-wise cropped and converted to ortho images. Furthermore, each aerial image patch covering the area of the corresponding MLSPC patch is also cropped from the aerial image. For feature detection, we implemented an adaptive variant of Harris-operator to automatically detect corner feature points on the vertices of road markings. In feature description phase, we used the LATCH binary descriptor, which is robust to data from different sensors. For descriptor matching, we developed an outlier filtering technique, which exploits the arrangements of relative Euclidean-distances and angles between corresponding sets of feature points. We found that the positioning accuracy of the computed correspondence has achieved the pixel level accuracy, where the image resolution is 12cm. Furthermore, the developed approach is reliable when enough road markings are available in the data sets. We conclude that, in urban areas, the developed approach can reliably extract features necessary to improve the MLSPC accuracy to pixel level.

Archaeological Feature Detection from Archive Aerial Photography with a Sfm-Mvs and Image Enhancement Pipeline

NASA Astrophysics Data System (ADS)

Peppa, M. V.; Mills, J. P.; Fieber, K. D.; Haynes, I.; Turner, S.; Turner, A.; Douglas, M.; Bryan, P. G.

2018-05-01

Understanding and protecting cultural heritage involves the detection and long-term documentation of archaeological remains alongside the spatio-temporal analysis of their landscape evolution. Archive aerial photography can illuminate traces of ancient features which typically appear with different brightness values from their surrounding environment, but are not always well defined. This research investigates the implementation of the Structure-from-Motion - Multi-View Stereo image matching approach with an image enhancement algorithm to derive three epochs of orthomosaics and digital surface models from visible and near infrared historic aerial photography. The enhancement algorithm uses decorrelation stretching to improve the contrast of the orthomosaics so as archaeological features are better detected. Results include 2D / 3D locations of detected archaeological traces stored into a geodatabase for further archaeological interpretation and correlation with benchmark observations. The study also discusses the merits and difficulties of the process involved. This research is based on a European-wide project, entitled "Cultural Heritage Through Time", and the case study research was carried out as a component of the project in the UK.

Unmanned Aerial Vehicle Systems for Remote Estimation of Flooded Areas Based on Complex Image Processing.

PubMed

Popescu, Dan; Ichim, Loretta; Stoican, Florin

2017-02-23

Floods are natural disasters which cause the most economic damage at the global level. Therefore, flood monitoring and damage estimation are very important for the population, authorities and insurance companies. The paper proposes an original solution, based on a hybrid network and complex image processing, to this problem. As first novelty, a multilevel system, with two components, terrestrial and aerial, was proposed and designed by the authors as support for image acquisition from a delimited region. The terrestrial component contains a Ground Control Station, as a coordinator at distance, which communicates via the internet with more Ground Data Terminals, as a fixed nodes network for data acquisition and communication. The aerial component contains mobile nodes-fixed wing type UAVs. In order to evaluate flood damage, two tasks must be accomplished by the network: area coverage and image processing. The second novelty of the paper consists of texture analysis in a deep neural network, taking into account new criteria for feature selection and patch classification. Color and spatial information extracted from chromatic co-occurrence matrix and mass fractal dimension were used as well. Finally, the experimental results in a real mission demonstrate the validity of the proposed methodologies and the performances of the algorithms.

Unmanned Aerial Vehicle Systems for Remote Estimation of Flooded Areas Based on Complex Image Processing

PubMed Central

Popescu, Dan; Ichim, Loretta; Stoican, Florin

2017-01-01

Floods are natural disasters which cause the most economic damage at the global level. Therefore, flood monitoring and damage estimation are very important for the population, authorities and insurance companies. The paper proposes an original solution, based on a hybrid network and complex image processing, to this problem. As first novelty, a multilevel system, with two components, terrestrial and aerial, was proposed and designed by the authors as support for image acquisition from a delimited region. The terrestrial component contains a Ground Control Station, as a coordinator at distance, which communicates via the internet with more Ground Data Terminals, as a fixed nodes network for data acquisition and communication. The aerial component contains mobile nodes—fixed wing type UAVs. In order to evaluate flood damage, two tasks must be accomplished by the network: area coverage and image processing. The second novelty of the paper consists of texture analysis in a deep neural network, taking into account new criteria for feature selection and patch classification. Color and spatial information extracted from chromatic co-occurrence matrix and mass fractal dimension were used as well. Finally, the experimental results in a real mission demonstrate the validity of the proposed methodologies and the performances of the algorithms. PMID:28241479

Small unmanned aerial vehicles (micro-UAVs, drones) in plant ecology1

PubMed Central

Cruzan, Mitchell B.; Weinstein, Ben G.; Grasty, Monica R.; Kohrn, Brendan F.; Hendrickson, Elizabeth C.; Arredondo, Tina M.; Thompson, Pamela G.

2016-01-01

Premise of the study: Low-elevation surveys with small aerial drones (micro–unmanned aerial vehicles [UAVs]) may be used for a wide variety of applications in plant ecology, including mapping vegetation over small- to medium-sized regions. We provide an overview of methods and procedures for conducting surveys and illustrate some of these applications. Methods: Aerial images were obtained by flying a small drone along transects over the area of interest. Images were used to create a composite image (orthomosaic) and a digital surface model (DSM). Vegetation classification was conducted manually and using an automated routine. Coverage of an individual species was estimated from aerial images. Results: We created a vegetation map for the entire region from the orthomosaic and DSM, and mapped the density of one species. Comparison of our manual and automated habitat classification confirmed that our mapping methods were accurate. A species with high contrast to the background matrix allowed adequate estimate of its coverage. Discussion: The example surveys demonstrate that small aerial drones are capable of gathering large amounts of information on the distribution of vegetation and individual species with minimal impact to sensitive habitats. Low-elevation aerial surveys have potential for a wide range of applications in plant ecology. PMID:27672518

Counter Unmanned Aerial Systems Testing: Evaluation of VIS SWIR MWIR and LWIR passive imagers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Birch, Gabriel Carlisle; Woo, Bryana Lynn

This report contains analysis of unmanned aerial systems as imaged by visible, short-wave infrared, mid-wave infrared, and long-wave infrared passive devices. Testing was conducted at the Nevada National Security Site (NNSS) during the week of August 15, 2016. Target images in all spectral bands are shown and contrast versus background is reported. Calculations are performed to determine estimated pixels-on-target for detection and assessment levels, and the number of pixels needed to cover a hemisphere for detection or assessment at defined distances. Background clutter challenges are qualitatively discussed for different spectral bands, and low contrast scenarios are highlighted for long-wave infraredmore » imagers.« less

Photogrammetric mapping using unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Graça, N.; Mitishita, E.; Gonçalves, J.

2014-11-01

Nowadays Unmanned Aerial Vehicle (UAV) technology has attracted attention for aerial photogrammetric mapping. The low cost and the feasibility to automatic flight along commanded waypoints can be considered as the main advantages of this technology in photogrammetric applications. Using GNSS/INS technologies the images are taken at the planned position of the exposure station and the exterior orientation parameters (position Xo, Yo, Zo and attitude ω, φ, χ) of images can be direct determined. However, common UAVs (off-the-shelf) do not replace the traditional aircraft platform. Overall, the main shortcomings are related to: difficulties to obtain the authorization to perform the flight in urban and rural areas, platform stability, safety flight, stability of the image block configuration, high number of the images and inaccuracies of the direct determination of the exterior orientation parameters of the images. In this paper are shown the obtained results from the project photogrammetric mapping using aerial images from the SIMEPAR UAV system. The PIPER J3 UAV Hydro aircraft was used. It has a micro pilot MP2128g. The system is fully integrated with 3-axis gyros/accelerometers, GPS, pressure altimeter, pressure airspeed sensors. A Sony Cyber-shot DSC-W300 was calibrated and used to get the image block. The flight height was close to 400 m, resulting GSD near to 0.10 m. The state of the art of the used technology, methodologies and the obtained results are shown and discussed. Finally advantages/shortcomings found in the study and main conclusions are presented

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

PubMed

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

Toward autonomous avian-inspired grasping for micro aerial vehicles.

PubMed

Thomas, Justin; Loianno, Giuseppe; Polin, Joseph; Sreenath, Koushil; Kumar, Vijay

2014-06-01

Micro aerial vehicles, particularly quadrotors, have been used in a wide range of applications. However, the literature on aerial manipulation and grasping is limited and the work is based on quasi-static models. In this paper, we draw inspiration from agile, fast-moving birds such as raptors, that are able to capture moving prey on the ground or in water, and develop similar capabilities for quadrotors. We address dynamic grasping, an approach to prehensile grasping in which the dynamics of the robot and its gripper are significant and must be explicitly modeled and controlled for successful execution. Dynamic grasping is relevant for fast pick-and-place operations, transportation and delivery of objects, and placing or retrieving sensors. We show how this capability can be realized (a) using a motion capture system and (b) without external sensors relying only on onboard sensors. In both cases we describe the dynamic model, and trajectory planning and control algorithms. In particular, we present a methodology for flying and grasping a cylindrical object using feedback from a monocular camera and an inertial measurement unit onboard the aerial robot. This is accomplished by mapping the dynamics of the quadrotor to a level virtual image plane, which in turn enables dynamically-feasible trajectory planning for image features in the image space, and a vision-based controller with guaranteed convergence properties. We also present experimental results obtained with a quadrotor equipped with an articulated gripper to illustrate both approaches.

a Method for Simultaneous Aerial and Terrestrial Geodata Acquisition for Corridor Mapping

NASA Astrophysics Data System (ADS)

Molina, P.; Blázquez, M.; Sastre, J.; Colomina, I.

2015-08-01

In this paper, we present mapKITE, a new mobile, simultaneous terrestrial and aerial, geodata collection and post-processing method. On one side, the method combines a terrestrial mobile mapping system (TMMS) with an unmanned aerial mapping one, both equipped with remote sensing payloads (at least, a nadir-looking visible-band camera in the UA) by means of which aerial and terrestrial geodata are acquired simultaneously. This tandem geodata acquisition system is based on a terrestrial vehicle (TV) and on an unmanned aircraft (UA) linked by a 'virtual tether', that is, a mechanism based on the real-time supply of UA waypoints by the TV. By means of the TV-to-UA tether, the UA follows the TV keeping a specific relative TV-to-UA spatial configuration enabling the simultaneous operation of both systems to obtain highly redundant and complementary geodata. On the other side, mapKITE presents a novel concept for geodata post-processing favoured by the rich geometrical aspects derived from the mapKITE tandem simultaneous operation. The approach followed for sensor orientation and calibration of the aerial images captured by the UA inherits the principles of Integrated Sensor Orientation (ISO) and adds the pointing-and-scaling photogrammetric measurement of a distinctive element observed in every UA image, which is a coded target mounted on the roof of the TV. By means of the TV navigation system, the orientation of the TV coded target is performed and used in the post-processing UA image orientation approach as a Kinematic Ground Control Point (KGCP). The geometric strength of a mapKITE ISO network is therefore high as it counts with the traditional tie point image measurements, static ground control points, kinematic aerial control and the new point-and-scale measurements of the KGCPs. With such a geometry, reliable system and sensor orientation and calibration and eventual further reduction of the number of traditional ground control points is feasible. The different

Automated hotspot analysis with aerial image CD metrology for advanced logic devices

NASA Astrophysics Data System (ADS)

Buttgereit, Ute; Trautzsch, Thomas; Kim, Min-ho; Seo, Jung-Uk; Yoon, Young-Keun; Han, Hak-Seung; Chung, Dong Hoon; Jeon, Chan-Uk; Meyers, Gary

2014-09-01

Continuously shrinking designs by further extension of 193nm technology lead to a much higher probability of hotspots especially for the manufacturing of advanced logic devices. The CD of these potential hotspots needs to be precisely controlled and measured on the mask. On top of that, the feature complexity increases due to high OPC load in the logic mask design which is an additional challenge for CD metrology. Therefore the hotspot measurements have been performed on WLCD from ZEISS, which provides the benefit of reduced complexity by measuring the CD in the aerial image and qualifying the printing relevant CD. This is especially of advantage for complex 2D feature measurements. Additionally, the data preparation for CD measurement becomes more critical due to the larger amount of CD measurements and the increasing feature diversity. For the data preparation this means to identify these hotspots and mark them automatically with the correct marker required to make the feature specific CD measurement successful. Currently available methods can address generic pattern but cannot deal with the pattern diversity of the hotspots. The paper will explore a method how to overcome those limitations and to enhance the time-to-result in the marking process dramatically. For the marking process the Synopsys WLCD Output Module was utilized, which is an interface between the CATS mask data prep software and the WLCD metrology tool. It translates the CATS marking directly into an executable WLCD measurement job including CD analysis. The paper will describe the utilized method and flow for the hotspot measurement. Additionally, the achieved results on hotspot measurements utilizing this method will be presented.

Modelling and representation issues in automated feature extraction from aerial and satellite images

NASA Astrophysics Data System (ADS)

Sowmya, Arcot; Trinder, John

New digital systems for the processing of photogrammetric and remote sensing images have led to new approaches to information extraction for mapping and Geographic Information System (GIS) applications, with the expectation that data can become more readily available at a lower cost and with greater currency. Demands for mapping and GIS data are increasing as well for environmental assessment and monitoring. Hence, researchers from the fields of photogrammetry and remote sensing, as well as computer vision and artificial intelligence, are bringing together their particular skills for automating these tasks of information extraction. The paper will review some of the approaches used in knowledge representation and modelling for machine vision, and give examples of their applications in research for image understanding of aerial and satellite imagery.

Near Real-Time Georeference of Umanned Aerial Vehicle Images for Post-Earthquake Response

NASA Astrophysics Data System (ADS)

Wang, S.; Wang, X.; Dou, A.; Yuan, X.; Ding, L.; Ding, X.

2018-04-01

The rapid collection of Unmanned Aerial Vehicle (UAV) remote sensing images plays an important role in the fast submitting disaster information and the monitored serious damaged objects after the earthquake. However, for hundreds of UAV images collected in one flight sortie, the traditional data processing methods are image stitching and three-dimensional reconstruction, which take one to several hours, and affect the speed of disaster response. If the manual searching method is employed, we will spend much more time to select the images and the find images do not have spatial reference. Therefore, a near-real-time rapid georeference method for UAV remote sensing disaster data is proposed in this paper. The UAV images are achieved georeference combined with the position and attitude data collected by UAV flight control system, and the georeferenced data is organized by means of world file which is developed by ESRI. The C # language is adopted to compile the UAV images rapid georeference software, combined with Geospatial Data Abstraction Library (GDAL). The result shows that it can realize rapid georeference of remote sensing disaster images for up to one thousand UAV images within one minute, and meets the demand of rapid disaster response, which is of great value in disaster emergency application.

Monitoring and Assuring the Quality of Digital Aerial Data

NASA Technical Reports Server (NTRS)

Christopherson, Jon

2007-01-01

This viewgraph presentation explains the USGS plan for monitoring and assuring the quality of digital aerial data. The contents include: 1) History of USGS Aerial Imaging Involvement; 2) USGS Research and Results; 3) Outline of USGS Quality Assurance Plan; 4) Other areas of Interest; and 5) Summary

Optimizing Radiometric Fidelity to Enhance Aerial Image Change Detection Utilizing Digital Single Lens Reflex (DSLR) Cameras

NASA Astrophysics Data System (ADS)

Kerr, Andrew D.

Determining optimal imaging settings and best practices related to the capture of aerial imagery using consumer-grade digital single lens reflex (DSLR) cameras, should enable remote sensing scientists to generate consistent, high quality, and low cost image data sets. Radiometric optimization, image fidelity, image capture consistency and repeatability were evaluated in the context of detailed image-based change detection. The impetus for this research is in part, a dearth of relevant, contemporary literature, on the utilization of consumer grade DSLR cameras for remote sensing, and the best practices associated with their use. The main radiometric control settings on a DSLR camera, EV (Exposure Value), WB (White Balance), light metering, ISO, and aperture (f-stop), are variables that were altered and controlled over the course of several image capture missions. These variables were compared for their effects on dynamic range, intra-frame brightness variation, visual acuity, temporal consistency, and the detectability of simulated cracks placed in the images. This testing was conducted from a terrestrial, rather than an airborne collection platform, due to the large number of images per collection, and the desire to minimize inter-image misregistration. The results point to a range of slightly underexposed image exposure values as preferable for change detection and noise minimization fidelity. The makeup of the scene, the sensor, and aerial platform, influence the selection of the aperture and shutter speed which along with other variables, allow for estimation of the apparent image motion (AIM) motion blur in the resulting images. The importance of the image edges in the image application, will in part dictate the lowest usable f-stop, and allow the user to select a more optimal shutter speed and ISO. The single most important camera capture variable is exposure bias (EV), with a full dynamic range, wide distribution of DN values, and high visual contrast and

Low-resolution ship detection from high-altitude aerial images

NASA Astrophysics Data System (ADS)

Qi, Shengxiang; Wu, Jianmin; Zhou, Qing; Kang, Minyang

2018-02-01

Ship detection from optical images taken by high-altitude aircrafts such as unmanned long-endurance airships and unmanned aerial vehicles has broad applications in marine fishery management, ship monitoring and vessel salvage. However, the major challenge is the limited capability of information processing on unmanned high-altitude platforms. Furthermore, in order to guarantee the wide detection range, unmanned aircrafts generally cruise at high altitudes, resulting in imagery with low-resolution targets and strong clutters suffered by heavy clouds. In this paper, we propose a low-resolution ship detection method to extract ships from these high-altitude optical images. Inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, we propose the facet kernel filtering to rapidly suppress cluttered backgrounds and delineate candidate target regions from the sea surface. Then, the principal component analysis (PCA) is used to compute the orientation of the target axis, followed by a simplified histogram of oriented gradient (HOG) descriptor to characterize the ship shape property. Finally, support vector machine (SVM) is applied to discriminate real targets and false alarms. Experimental results show that the proposed method actually has high efficiency in low-resolution ship detection.

Control of a Quadcopter Aerial Robot Using Optic Flow Sensing

NASA Astrophysics Data System (ADS)

Hurd, Michael Brandon

This thesis focuses on the motion control of a custom-built quadcopter aerial robot using optic flow sensing. Optic flow sensing is a vision-based approach that can provide a robot the ability to fly in global positioning system (GPS) denied environments, such as indoor environments. In this work, optic flow sensors are used to stabilize the motion of quadcopter robot, where an optic flow algorithm is applied to provide odometry measurements to the quadcopter's central processing unit to monitor the flight heading. The optic-flow sensor and algorithm are capable of gathering and processing the images at 250 frames/sec, and the sensor package weighs 2.5 g and has a footprint of 6 cm2 in area. The odometry value from the optic flow sensor is then used a feedback information in a simple proportional-integral-derivative (PID) controller on the quadcopter. Experimental results are presented to demonstrate the effectiveness of using optic flow for controlling the motion of the quadcopter aerial robot. The technique presented herein can be applied to different types of aerial robotic systems or unmanned aerial vehicles (UAVs), as well as unmanned ground vehicles (UGV).

Automatic Sea Bird Detection from High Resolution Aerial Imagery

NASA Astrophysics Data System (ADS)

Mader, S.; Grenzdörffer, G. J.

2016-06-01

Great efforts are presently taken in the scientific community to develop computerized and (fully) automated image processing methods allowing for an efficient and automatic monitoring of sea birds and marine mammals in ever-growing amounts of aerial imagery. Currently the major part of the processing, however, is still conducted by especially trained professionals, visually examining the images and detecting and classifying the requested subjects. This is a very tedious task, particularly when the rate of void images regularly exceeds the mark of 90%. In the content of this contribution we will present our work aiming to support the processing of aerial images by modern methods from the field of image processing. We will especially focus on the combination of local, region-based feature detection and piecewise global image segmentation for automatic detection of different sea bird species. Large image dimensions resulting from the use of medium and large-format digital cameras in aerial surveys inhibit the applicability of image processing methods based on global operations. In order to efficiently handle those image sizes and to nevertheless take advantage of globally operating segmentation algorithms, we will describe the combined usage of a simple performant feature detector based on local operations on the original image with a complex global segmentation algorithm operating on extracted sub-images. The resulting exact segmentation of possible candidates then serves as a basis for the determination of feature vectors for subsequent elimination of false candidates and for classification tasks.

Automatic digital surface model (DSM) generation from aerial imagery data

NASA Astrophysics Data System (ADS)

Zhou, Nan; Cao, Shixiang; He, Hongyan; Xing, Kun; Yue, Chunyu

2018-04-01

Aerial sensors are widely used to acquire imagery for photogrammetric and remote sensing application. In general, the images have large overlapped region, which provide a lot of redundant geometry and radiation information for matching. This paper presents a POS supported dense matching procedure for automatic DSM generation from aerial imagery data. The method uses a coarse-to-fine hierarchical strategy with an effective combination of several image matching algorithms: image radiation pre-processing, image pyramid generation, feature point extraction and grid point generation, multi-image geometrically constraint cross-correlation (MIG3C), global relaxation optimization, multi-image geometrically constrained least squares matching (MIGCLSM), TIN generation and point cloud filtering. The image radiation pre-processing is used in order to reduce the effects of the inherent radiometric problems and optimize the images. The presented approach essentially consists of 3 components: feature point extraction and matching procedure, grid point matching procedure and relational matching procedure. The MIGCLSM method is used to achieve potentially sub-pixel accuracy matches and identify some inaccurate and possibly false matches. The feasibility of the method has been tested on different aerial scale images with different landcover types. The accuracy evaluation is based on the comparison between the automatic extracted DSMs derived from the precise exterior orientation parameters (EOPs) and the POS.

An enhanced multi-view vertical line locus matching algorithm of object space ground primitives based on positioning consistency for aerial and space images

NASA Astrophysics Data System (ADS)

Zhang, Ka; Sheng, Yehua; Wang, Meizhen; Fu, Suxia

2018-05-01

The traditional multi-view vertical line locus (TMVLL) matching method is an object-space-based method that is commonly used to directly acquire spatial 3D coordinates of ground objects in photogrammetry. However, the TMVLL method can only obtain one elevation and lacks an accurate means of validating the matching results. In this paper, we propose an enhanced multi-view vertical line locus (EMVLL) matching algorithm based on positioning consistency for aerial or space images. The algorithm involves three components: confirming candidate pixels of the ground primitive in the base image, multi-view image matching based on the object space constraints for all candidate pixels, and validating the consistency of the object space coordinates with the multi-view matching result. The proposed algorithm was tested using actual aerial images and space images. Experimental results show that the EMVLL method successfully solves the problems associated with the TMVLL method, and has greater reliability, accuracy and computing efficiency.

Converting aerial imagery to application maps

USDA-ARS?s Scientific Manuscript database

Over the last couple of years in Agricultural Aviation and at the 2014 and 2015 NAAA conventions, we have written about and presented both single-camera and two-camera imaging systems for use on agricultural aircraft. Many aerial applicators have shown a great deal of interest in the imaging systems...

High clearance phenotyping systems for season-long measurement of corn, sorghum and other row crops to complement unmanned aerial vehicle systems

NASA Astrophysics Data System (ADS)

Murray, Seth C.; Knox, Leighton; Hartley, Brandon; Méndez-Dorado, Mario A.; Richardson, Grant; Thomasson, J. Alex; Shi, Yeyin; Rajan, Nithya; Neely, Haly; Bagavathiannan, Muthukumar; Dong, Xuejun; Rooney, William L.

2016-05-01

The next generation of plant breeding progress requires accurately estimating plant growth and development parameters to be made over routine intervals within large field experiments. Hand measurements are laborious and time consuming and the most promising tools under development are sensors carried by ground vehicles or unmanned aerial vehicles, with each specific vehicle having unique limitations. Previously available ground vehicles have primarily been restricted to monitoring shorter crops or early growth in corn and sorghum, since plants taller than a meter could be damaged by a tractor or spray rig passing over them. Here we have designed two and already constructed one of these self-propelled ground vehicles with adjustable heights that can clear mature corn and sorghum without damage (over three meters of clearance), which will work for shorter row crops as well. In addition to regular RGB image capture, sensor suites are incorporated to estimate plant height, vegetation indices, canopy temperature and photosynthetically active solar radiation, all referenced using RTK GPS to individual plots. These ground vehicles will be useful to validate data collected from unmanned aerial vehicles and support hand measurements taken on plots.

Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring

USGS Publications Warehouse

Gillan, Jeffrey K.; Karl, Jason W.; Duniway, Michael; Elaksher, Ahmed

2014-01-01

Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of

Object-based Image Classification of Arctic Sea Ice and Melt Ponds through Aerial Photos

NASA Astrophysics Data System (ADS)

Miao, X.; Xie, H.; Li, Z.; Lei, R.

2013-12-01

The last six years have marked the lowest Arctic summer sea ice extents in the modern era, with a new record summer minimum (3.4 million km2) set on 13 September 2012. It has been predicted that the Arctic could be free of summer ice within the next 25-30. The loss of Arctic summer ice could have serious consequences, such as higher water temperature due to the positive feedback of albedo, more powerful and frequent storms, rising sea levels, diminished habitats for polar animals, and more pollution due to fossil fuel exploitation and/ or increased traffic through the Northwest/ Northeast Passage. In these processes, melt ponds play an important role in Earth's radiation balance since they strongly absorb solar radiation rather than reflecting it as snow and ice do. Therefore, it is necessary to develop the ability of predicting the sea ice/ melt pond extents and space-time evolution, which is pivotal to prepare for the variation and uncertainty of the future environment, political, economic, and military needs. A lot of efforts have been put into Arctic sea ice modeling to simulate sea ice processes. However, these sea ice models were initiated and developed based on limited field surveys, aircraft or satellite image data. Therefore, it is necessary to collect high resolution sea ice aerial photo in a systematic way to tune up, validate, and improve models. Currently there are many sea ice aerial photos available, such as Chinese Arctic Exploration (CHINARE 2008, 2010, 2012), SHEBA 1998 and HOTRAX 2005. However, manually delineating of sea ice and melt pond from these images is time-consuming and labor-intensive. In this study, we use the object-based remote sensing classification scheme to extract sea ice and melt ponds efficiently from 1,727 aerial photos taken during the CHINARE 2010. The algorithm includes three major steps as follows. (1) Image segmentation groups the neighboring pixels into objects according to the similarity of spectral and texture

Online Aerial Terrain Mapping for Ground Robot Navigation

PubMed Central

Peterson, John; Chaudhry, Haseeb; Abdelatty, Karim; Bird, John; Kochersberger, Kevin

2018-01-01

This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle’s overhead view to inform the ground vehicle’s path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles. PMID:29461496

Online Aerial Terrain Mapping for Ground Robot Navigation.

PubMed

Peterson, John; Chaudhry, Haseeb; Abdelatty, Karim; Bird, John; Kochersberger, Kevin

2018-02-20

This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle's overhead view to inform the ground vehicle's path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles.

Entropy-aware projected Landweber reconstruction for quantized block compressive sensing of aerial imagery

NASA Astrophysics Data System (ADS)

Liu, Hao; Li, Kangda; Wang, Bing; Tang, Hainie; Gong, Xiaohui

2017-01-01

A quantized block compressive sensing (QBCS) framework, which incorporates the universal measurement, quantization/inverse quantization, entropy coder/decoder, and iterative projected Landweber reconstruction, is summarized. Under the QBCS framework, this paper presents an improved reconstruction algorithm for aerial imagery, QBCS, with entropy-aware projected Landweber (QBCS-EPL), which leverages the full-image sparse transform without Wiener filter and an entropy-aware thresholding model for wavelet-domain image denoising. Through analyzing the functional relation between the soft-thresholding factors and entropy-based bitrates for different quantization methods, the proposed model can effectively remove wavelet-domain noise of bivariate shrinkage and achieve better image reconstruction quality. For the overall performance of QBCS reconstruction, experimental results demonstrate that the proposed QBCS-EPL algorithm significantly outperforms several existing algorithms. With the experiment-driven methodology, the QBCS-EPL algorithm can obtain better reconstruction quality at a relatively moderate computational cost, which makes it more desirable for aerial imagery applications.

Vehicle detection in aerial surveillance using dynamic Bayesian networks.

PubMed

Cheng, Hsu-Yung; Weng, Chih-Chia; Chen, Yi-Ying

2012-04-01

We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.

Automated Snow Extent Mapping Based on Orthophoto Images from Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Niedzielski, Tomasz; Spallek, Waldemar; Witek-Kasprzak, Matylda

2018-04-01

The paper presents the application of the k-means clustering in the process of automated snow extent mapping using orthophoto images generated using the Structure-from-Motion (SfM) algorithm from oblique aerial photographs taken by unmanned aerial vehicle (UAV). A simple classification approach has been implemented to discriminate between snow-free and snow-covered terrain. The procedure uses the k-means clustering and classifies orthophoto images based on the three-dimensional space of red-green-blue (RGB) or near-infrared-red-green (NIRRG) or near-infrared-green-blue (NIRGB) bands. To test the method, several field experiments have been carried out, both in situations when snow cover was continuous and when it was patchy. The experiments have been conducted using three fixed-wing UAVs (swinglet CAM by senseFly, eBee by senseFly, and Birdie by FlyTech UAV) on 10/04/2015, 23/03/2016, and 16/03/2017 within three test sites in the Izerskie Mountains in southwestern Poland. The resulting snow extent maps, produced automatically using the classification method, have been validated against real snow extents delineated through a visual analysis and interpretation offered by human analysts. For the simplest classification setup, which assumes two classes in the k-means clustering, the extent of snow patches was estimated accurately, with areal underestimation of 4.6% (RGB) and overestimation of 5.5% (NIRGB). For continuous snow cover with sparse discontinuities at places where trees or bushes protruded from snow, the agreement between automatically produced snow extent maps and observations was better, i.e. 1.5% (underestimation with RGB) and 0.7-0.9% (overestimation, either with RGB or with NIRRG). Shadows on snow were found to be mainly responsible for the misclassification.

Aerial vehicles collision avoidance using monocular vision

NASA Astrophysics Data System (ADS)

Balashov, Oleg; Muraviev, Vadim; Strotov, Valery

2016-10-01

In this paper image-based collision avoidance algorithm that provides detection of nearby aircraft and distance estimation is presented. The approach requires a vision system with a single moving camera and additional information about carrier's speed and orientation from onboard sensors. The main idea is to create a multi-step approach based on a preliminary detection, regions of interest (ROI) selection, contour segmentation, object matching and localization. The proposed algorithm is able to detect small targets but unlike many other approaches is designed to work with large-scale objects as well. To localize aerial vehicle position the system of equations relating object coordinates in space and observed image is solved. The system solution gives the current position and speed of the detected object in space. Using this information distance and time to collision can be estimated. Experimental research on real video sequences and modeled data is performed. Video database contained different types of aerial vehicles: aircrafts, helicopters, and UAVs. The presented algorithm is able to detect aerial vehicles from several kilometers under regular daylight conditions.

Geometric Calibration and Validation of Ultracam Aerial Sensors

NASA Astrophysics Data System (ADS)

Gruber, Michael; Schachinger, Bernhard; Muick, Marc; Neuner, Christian; Tschemmernegg, Helfried

2016-03-01

We present details of the calibration and validation procedure of UltraCam Aerial Camera systems. Results from the laboratory calibration and from validation flights are presented for both, the large format nadir cameras and the oblique cameras as well. Thus in this contribution we show results from the UltraCam Eagle and the UltraCam Falcon, both nadir mapping cameras, and the UltraCam Osprey, our oblique camera system. This sensor offers a mapping grade nadir component together with the four oblique camera heads. The geometric processing after the flight mission is being covered by the UltraMap software product. Thus we present details about the workflow as well. The first part consists of the initial post-processing which combines image information as well as camera parameters derived from the laboratory calibration. The second part, the traditional automated aerial triangulation (AAT) is the step from single images to blocks and enables an additional optimization process. We also present some special features of our software, which are designed to better support the operator to analyze large blocks of aerial images and to judge the quality of the photogrammetric set-up.

Kite Aerial Photography (KAP) as a Tool for Field Teaching

ERIC Educational Resources Information Center

Sander, Lasse

2014-01-01

Kite aerial photography (KAP) is proposed as a creative tool for geography field teaching and as a medium to approach the complexity of readily available geodata. The method can be integrated as field experiment, surveying technique or group activity. The acquired aerial images can instantaneously be integrated in geographic information systems…

Learning Scene Categories from High Resolution Satellite Image for Aerial Video Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheriyadat, Anil M

2011-01-01

Automatic scene categorization can benefit various aerial video processing applications. This paper addresses the problem of predicting the scene category from aerial video frames using a prior model learned from satellite imagery. We show that local and global features in the form of line statistics and 2-D power spectrum parameters respectively can characterize the aerial scene well. The line feature statistics and spatial frequency parameters are useful cues to distinguish between different urban scene categories. We learn the scene prediction model from highresolution satellite imagery to test the model on the Columbus Surrogate Unmanned Aerial Vehicle (CSUAV) dataset ollected bymore » high-altitude wide area UAV sensor platform. e compare the proposed features with the popular Scale nvariant Feature Transform (SIFT) features. Our experimental results show that proposed approach outperforms te SIFT model when the training and testing are conducted n disparate data sources.« less

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

PubMed Central

Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references. PMID:29581722

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification.

PubMed

Yu, Yunlong; Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles

PubMed Central

Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe

2017-01-01

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l’information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N-th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work. PMID:28718788

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles.

PubMed

Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe; Thom, Christian

2017-07-18

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l'information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N -th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work.

Mapping rock forming minerals at Boundary Canyon, Death Valey National Park, California, using aerial SEBASS thermal infrared hyperspectral image data

NASA Astrophysics Data System (ADS)

Aslett, Zan; Taranik, James V.; Riley, Dean N.

2018-02-01

Aerial spatially enhanced broadband array spectrograph system (SEBASS) long-wave infrared (LWIR) hyperspectral image data were used to map the distribution of rock-forming minerals indicative of sedimentary and meta-sedimentary lithologies around Boundary Canyon, Death Valley, California, USA. Collection of data over the Boundary Canyon detachment fault (BCDF) facilitated measurement of numerous lithologies representing a contact between the relatively unmetamorphosed Grapevine Mountains allochthon and the metamorphosed core complex of the Funeral Mountains autochthon. These included quartz-rich sandstone, quartzite, conglomerate, and alluvium; muscovite-rich schist, siltstone, and slate; and carbonate-rich dolomite, limestone, and marble, ranging in age from late Precambrian to Quaternary. Hyperspectral data were reduced in dimensionality and processed to statistically identify and map unique emissivity spectra endmembers. Some minerals (e.g., quartz and muscovite) dominate multiple lithologies, resulting in a limited ability to differentiate them. Abrupt variations in image data emissivity amongst pelitic schists corresponded to amphibolite; these rocks represent gradation from greenschist- to amphibolite-metamorphic facies lithologies. Although the full potential of LWIR hyperspectral image data may not be fully utilized within this study area due to lack of measurable spectral distinction between rocks of similar bulk mineralogy, the high spectral resolution of the image data was useful in characterizing silicate- and carbonate-based sedimentary and meta-sedimentary rocks in proximity to fault contacts, as well as for interpreting some mineral mixtures.

Measured Noise from Small Unmanned Aerial Vehicles

NASA Technical Reports Server (NTRS)

Cabell, Randolph; McSwain, Robert; Grosveld, Ferdinand

2016-01-01

Proposed uses of small unmanned aerial vehicles (UAVs), including home package delivery, have the potential to expose large portions of communities to a new noise source. This paper discusses results of flyover noise measurements of four small UAVs, including an internal combustion-powered model airplane and three battery-powered multicopters. Basic noise characteristics of these vehicles are discussed, including spectral properties and sound level metrics such as sound pressure level, effective perceived noise level, and sound exposure level. The size and aerodynamic characteristics of the multicopters in particular make their flight path susceptible to atmospheric disturbances such as wind gusts. These gusts, coupled with a flight control system that varies rotor speed to maintain vehicle stability, create an unsteady acoustic signature. The spectral variations resulting from this unsteadiness are explored, in both hover and flyover conditions for the multicopters. The time varying noise, which differs from the relatively steady noise generated by large transport aircraft, may complicate the prediction of human annoyance using conventional sound level metrics.

Combining satellite, aerial and ground measurements to assess forest carbon stocks in Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Beaumont, Benjamin; Bouvy, Alban; Stephenne, Nathalie; Mathoux, Pierre; Bastin, Jean-François; Baudot, Yves; Akkermans, Tom

2015-04-01

Monitoring tropical forest carbon stocks changes has been a rising topic in the recent years as a result of REDD+ mechanisms negotiations. Such monitoring will be mandatory for each project/country willing to benefit from these financial incentives in the future. Aerial and satellite remote sensing technologies offer cost advantages in implementing large scale forest inventories. Despite the recent progress made in the use of airborne LiDAR for carbon stocks estimation, no widely operational and cost effective method has yet been delivered for central Africa forest monitoring. Within the Maï Ndombe region of Democratic Republic of Congo, the EO4REDD project develops a method combining satellite, aerial and ground measurements. This combination is done in three steps: [1] mapping and quantifying forest cover changes using an object-based semi-automatic change detection (deforestation and forest degradation) methodology based on very high resolution satellite imagery (RapidEye), [2] developing an allometric linear model for above ground biomass measurements based on dendrometric parameters (tree crown areas and heights) extracted from airborne stereoscopic image pairs and calibrated using ground measurements of individual trees on a data set of 18 one hectare plots and [3] relating these two products to assess carbon stocks changes at a regional scale. Given the high accuracies obtained in [1] (> 80% for deforestation and 77% for forest degradation) and the suitable, but still to be improved with a larger calibrating sample, model (R² of 0.7) obtained in [2], EO4REDD products can be seen as a valid and replicable option for carbon stocks monitoring in tropical forests. Further improvements are planned to strengthen the cost effectiveness value and the REDD+ suitability in the second phase of EO4REDD. This second phase will include [A] specific model developments per forest type; [B] measurements of afforestation, reforestation and natural regeneration processes and

Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring.

PubMed

Gillan, Jeffrey K; Karl, Jason W; Duniway, Michael; Elaksher, Ahmed

2014-11-01

Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of

Pipeline monitoring with unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kochetkova, L. I.

2018-05-01

Pipeline leakage during transportation of combustible substances leads to explosion and fire thus causing death of people and destruction of production and accommodation facilities. Continuous pipeline monitoring allows identifying leaks in due time and quickly taking measures for their elimination. The paper describes the solution of identification of pipeline leakage using unmanned aerial vehicles. It is recommended to apply the spectral analysis with input RGB signal to identify pipeline damages. The application of multi-zone digital images allows defining potential spill of oil hydrocarbons as well as possible soil pollution. The method of multi-temporal digital images within the visible region makes it possible to define changes in soil morphology for its subsequent analysis. The given solution is cost efficient and reliable thus allowing reducing timing and labor resources in comparison with other methods of pipeline monitoring.

A fast and mobile system for registration of low-altitude visual and thermal aerial images using multiple small-scale UAVs

NASA Astrophysics Data System (ADS)

Yahyanejad, Saeed; Rinner, Bernhard

2015-06-01

The use of multiple small-scale UAVs to support first responders in disaster management has become popular because of their speed and low deployment costs. We exploit such UAVs to perform real-time monitoring of target areas by fusing individual images captured from heterogeneous aerial sensors. Many approaches have already been presented to register images from homogeneous sensors. These methods have demonstrated robustness against scale, rotation and illumination variations and can also cope with limited overlap among individual images. In this paper we focus on thermal and visual image registration and propose different methods to improve the quality of interspectral registration for the purpose of real-time monitoring and mobile mapping. Images captured by low-altitude UAVs represent a very challenging scenario for interspectral registration due to the strong variations in overlap, scale, rotation, point of view and structure of such scenes. Furthermore, these small-scale UAVs have limited processing and communication power. The contributions of this paper include (i) the introduction of a feature descriptor for robustly identifying corresponding regions of images in different spectrums, (ii) the registration of image mosaics, and (iii) the registration of depth maps. We evaluated the first method using a test data set consisting of 84 image pairs. In all instances our approach combined with SIFT or SURF feature-based registration was superior to the standard versions. Although we focus mainly on aerial imagery, our evaluation shows that the presented approach would also be beneficial in other scenarios such as surveillance and human detection. Furthermore, we demonstrated the advantages of the other two methods in case of multiple image pairs.

Integrating dynamic and distributed compressive sensing techniques to enhance image quality of the compressive line sensing system for unmanned aerial vehicles application

NASA Astrophysics Data System (ADS)

Ouyang, Bing; Hou, Weilin; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.; Gong, Cuiling

2017-07-01

The compressive line sensing imaging system adopts distributed compressive sensing (CS) to acquire data and reconstruct images. Dynamic CS uses Bayesian inference to capture the correlated nature of the adjacent lines. An image reconstruction technique that incorporates dynamic CS in the distributed CS framework was developed to improve the quality of reconstructed images. The effectiveness of the technique was validated using experimental data acquired in an underwater imaging test facility. Results that demonstrate contrast and resolution improvements will be presented. The improved efficiency is desirable for unmanned aerial vehicles conducting long-duration missions.

Towards collaboration between unmanned aerial and ground vehicles for precision agriculture

NASA Astrophysics Data System (ADS)

Bhandari, Subodh; Raheja, Amar; Green, Robert L.; Do, Dat

2017-05-01

This paper presents the work being conducted at Cal Poly Pomona on the collaboration between unmanned aerial and ground vehicles for precision agriculture. The unmanned aerial vehicles (UAVs), equipped with multispectral/hyperspectral cameras and RGB cameras, take images of the crops while flying autonomously. The images are post processed or can be processed onboard. The processed images are used in the detection of unhealthy plants. Aerial data can be used by the UAVs and unmanned ground vehicles (UGVs) for various purposes including care of crops, harvest estimation, etc. The images can also be useful for optimized harvesting by isolating low yielding plants. These vehicles can be operated autonomously with limited or no human intervention, thereby reducing cost and limiting human exposure to agricultural chemicals. The paper discuss the autonomous UAV and UGV platforms used for the research, sensor integration, and experimental testing. Methods for ground truthing the results obtained from the UAVs will be used. The paper will also discuss equipping the UGV with a robotic arm for removing the unhealthy plants and/or weeds.

Spectral properties of agricultural crops and soils measured from space, aerial, field, and laboratory sensors

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Vanderbilt, V. C.; Robinson, B. F.; Daughtry, C. S. T.

1981-01-01

Investigations of the multispectral reflectance characteristics of crops and soils as measured from laboratory, field, aerial, and satellite sensor systems are reviewed. The relationships of important biological and physical characteristics to the spectral properties of crops and soils are addressed.

Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response.

PubMed

Ofli, Ferda; Meier, Patrick; Imran, Muhammad; Castillo, Carlos; Tuia, Devis; Rey, Nicolas; Briant, Julien; Millet, Pauline; Reinhard, Friedrich; Parkan, Matthew; Joost, Stéphane

2016-03-01

Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resolution of aerial imagery is an order of magnitude higher than the imagery produced by the most sophisticated commercial satellites today. Both the United States Federal Emergency Management Agency (FEMA) and the European Commission's Joint Research Center (JRC) have noted that aerial imagery will inevitably present a big data challenge. The purpose of this article is to get ahead of this future challenge by proposing a hybrid crowdsourcing and real-time machine learning solution to rapidly process large volumes of aerial data for disaster response in a time-sensitive manner. Crowdsourcing can be used to annotate features of interest in aerial images (such as damaged shelters and roads blocked by debris). These human-annotated features can then be used to train a supervised machine learning system to learn to recognize such features in new unseen images. In this article, we describe how this hybrid solution for image analysis can be implemented as a module (i.e., Aerial Clicker) to extend an existing platform called Artificial Intelligence for Disaster Response (AIDR), which has already been deployed to classify microblog messages during disasters using its Text Clicker module and in response to Cyclone Pam, a category 5 cyclone that devastated Vanuatu in March 2015. The hybrid solution we present can be applied to both aerial and satellite imagery and has applications beyond disaster response such as wildlife protection, human rights, and archeological exploration. As a proof of concept, we recently piloted this solution using very high-resolution aerial photographs of a wildlife reserve in Namibia to support rangers with their wildlife conservation efforts (SAVMAP project, http://lasig.epfl.ch/savmap ). The

Aerial secure display by use of polarization-processing display with retarder film and retro-reflector

NASA Astrophysics Data System (ADS)

Ito, Shusei; Uchida, Keitaro; Mizushina, Haruki; Suyama, Shiro; Yamamoto, Hirotsugu

2017-02-01

Security is one of the big issues in automated teller machine (ATM). In ATM, two types of security have to be maintained. One is to secure displayed information. The other is to secure screen contamination. This paper gives a solution for these two security issues. In order to secure information against peeping at the screen, we utilize visual cryptography for displayed information and limit the viewing zone. Furthermore, an aerial information screen with aerial imaging by retro-reflection, named AIRR enables users to avoid direct touch on the information screen. The purpose of this paper is to propose an aerial secure display technique that ensures security of displayed information as well as security against contamination problem on screen touch. We have developed a polarization-processing display that is composed of a backlight, a polarizer, a background LCD panel, a gap, a half-wave retarder, and a foreground LCD panel. Polarization angle is rotated with the LCD panels. We have constructed a polarization encryption code set. Size of displayed images are designed to limit the viewing position. Furthermore, this polarization-processing display has been introduced into our aerial imaging optics, which employs a reflective polarizer and a retro-reflector covered with a quarter-wave retarder. Polarization-modulated light forms the real image over the reflective polarizer. We have successfully formed aerial information screen that shows the secret image with a limited viewing position. This is the first realization of aerial secure display by use of polarization-processing display with retarder-film and retro-reflector.

The study of integration about measurable image and 4D production

NASA Astrophysics Data System (ADS)

Zhang, Chunsen; Hu, Pingbo; Niu, Weiyun

2008-12-01

In this paper, we create the geospatial data of three-dimensional (3D) modeling by the combination of digital photogrammetry and digital close-range photogrammetry. For large-scale geographical background, we make the establishment of DEM and DOM combination of three-dimensional landscape model based on the digital photogrammetry which uses aerial image data to make "4D" (DOM: Digital Orthophoto Map, DEM: Digital Elevation Model, DLG: Digital Line Graphic and DRG: Digital Raster Graphic) production. For the range of building and other artificial features which the users are interested in, we realize that the real features of the three-dimensional reconstruction adopting the method of the digital close-range photogrammetry can come true on the basis of following steps : non-metric cameras for data collection, the camera calibration, feature extraction, image matching, and other steps. At last, we combine three-dimensional background and local measurements real images of these large geographic data and realize the integration of measurable real image and the 4D production.The article discussed the way of the whole flow and technology, achieved the three-dimensional reconstruction and the integration of the large-scale threedimensional landscape and the metric building.

A case study of comparing radiometrically calibrated reflectance of an image mosaic from unmanned aerial system with that of a single image from manned aircraft over a same area

USDA-ARS?s Scientific Manuscript database

Although conventional high-altitude airborne remote sensing and low-altitude unmanned aerial system (UAS) based remote sensing share many commonalities, one of the major differences between the two remote sensing platforms is that the latter has much smaller image footprint. To cover the same area o...

Complex Building Detection Through Integrating LIDAR and Aerial Photos

NASA Astrophysics Data System (ADS)

Zhai, R.

2015-02-01

This paper proposes a new approach on digital building detection through the integration of LiDAR data and aerial imagery. It is known that most building rooftops are represented by different regions from different seed pixels. Considering the principals of image segmentation, this paper employs a new region based technique to segment images, combining both the advantages of LiDAR and aerial images together. First, multiple seed points are selected by taking several constraints into consideration in an automated way. Then, the region growing procedures proceed by combining the elevation attribute from LiDAR data, visibility attribute from DEM (Digital Elevation Model), and radiometric attribute from warped images in the segmentation. Through this combination, the pixels with similar height, visibility, and spectral attributes are merged into one region, which are believed to represent the whole building area. The proposed methodology was implemented on real data and competitive results were achieved.

Aerial Explorers

NASA Technical Reports Server (NTRS)

Young, Larry A.; Pisanich, Greg; Ippolito, Corey

2005-01-01

This paper presents recent results from a mission architecture study of planetary aerial explorers. In this study, several mission scenarios were developed in simulation and evaluated on success in meeting mission goals. This aerial explorer mission architecture study is unique in comparison with previous Mars airplane research activities. The study examines how aerial vehicles can find and gain access to otherwise inaccessible terrain features of interest. The aerial explorer also engages in a high-level of (indirect) surface interaction, despite not typically being able to takeoff and land or to engage in multiple flights/sorties. To achieve this goal, a new mission paradigm is proposed: aerial explorers should be considered as an additional element in the overall Entry, Descent, Landing System (EDLS) process. Further, aerial vehicles should be considered primarily as carrier/utility platforms whose purpose is to deliver air-deployed sensors and robotic devices, or symbiotes, to those high-value terrain features of interest.

Measurement of atmospheric surface layer turbulence using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bailey, Sean; Canter, Caleb

2017-11-01

We describe measurements of the turbulence within the atmospheric surface layer using highly instrumented and autonomous unmanned aerial vehicles (UAVs). Results from the CLOUDMAP measurement campaign in Stillwater Oklahoma are presented including turbulence statistics measured during the transition from stably stratified to convective conditions. The measurements were made using pre-fabricated fixed-wing remote-control aircraft adapted to fly autonomously and carry multi-hole pressure probes, pressure, temperature and humidity sensors. Two aircraft were flown simultaneously, with one flying a flight path intended to profile the boundary layer up to 100 m and the other flying at a constant fixed altitude of 50 m. The evolution of various turbulent statistics was determined from these flights, including Reynolds stresses, correlations, spectra and structure functions. These results were compared to those measured by a sonic anemometer located on a 7.5 m tower. This work was supported by the National Science Foundation through Grant #CBET-1351411 and by National Science Foundation award #1539070, Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics (CLOUDMAP).

Measurement of atmospheric surface layer turbulence using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Witte, Brandon; Smith, Lorli; Schlagenhauf, Cornelia; Bailey, Sean

2016-11-01

We describe measurements of the turbulence within the atmospheric surface layer using highly instrumented and autonomous unmanned aerial vehicles (UAVs). Results from the CLOUDMAP measurement campaign in Stillwater Oklahoma are presented including turbulence statistics measured during the transition from stably stratified to convective conditions. The measurements were made using pre-fabricated fixed-wing remote-control aircraft adapted to fly autonomously and carry multi-hole pressure probes, pressure, temperature and humidity sensors. Two aircraft were flown simultaneously, with one flying a flight path intended to profile the boundary layer up to 100 m and the other flying at a constant fixed altitude of 50 m. The evolution of various turbulent statistics was determined from these flights, including Reynolds stresses, correlations, spectra and structure functions. These results were compared to those measured by a sonic anemometer located on a 7.5 m tower. This work was supported by the National Science Foundation through Grant #CBET-1351411 and by National Science Foundation award #1539070, Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics (CLOUDMAP).

Measurement of greenhouse gases in UAE by using Unmanned Aerial Vehicle (UAV)

NASA Astrophysics Data System (ADS)

Abou-Elnour, Ali; Odeh, Mohamed; Abdelrhman, Mohammed; Balkis, Ahmed; Amira, Abdelraouf

2017-04-01

In the present work, a reliable and low cost system has been designed and implemented to measure greenhouse gases (GHG) in United Arab Emirates (UAE) by using unmanned aerial vehicle (UAV). A set of accurate gas, temperature, pressure, humidity sensors are integrated together with a wireless communication system on a microcontroller based platform to continuously measure the required data. The system instantaneously sends the measured data to a center monitoring unit via the wireless communication system. In addition, the proposed system has the features that all measurements are recorded directly in a storage device to allow effective monitoring in regions with weak or no wireless coverage. The obtained data will be used in all further sophisticated calculations for environmental research and monitoring purposes.

Theoretical study for aerial image intensity in resist in high numerical aperture projection optics and experimental verification with one-dimensional patterns

NASA Astrophysics Data System (ADS)

Shibuya, Masato; Takada, Akira; Nakashima, Toshiharu

2016-04-01

In optical lithography, high-performance exposure tools are indispensable to obtain not only fine patterns but also preciseness in pattern width. Since an accurate theoretical method is necessary to predict these values, some pioneer and valuable studies have been proposed. However, there might be some ambiguity or lack of consensus regarding the treatment of diffraction by object, incoming inclination factor onto image plane in scalar imaging theory, and paradoxical phenomenon of the inclined entrance plane wave onto image in vector imaging theory. We have reconsidered imaging theory in detail and also phenomenologically resolved the paradox. By comparing theoretical aerial image intensity with experimental pattern width for one-dimensional pattern, we have validated our theoretical consideration.

Surveying a Landslide in a Road Embankment Using Unmanned Aerial Vehicle Photogrammetry

NASA Astrophysics Data System (ADS)

Carvajal, F.; Agüera, F.; Pérez, M.

2011-09-01

Most of the works of civil engineering, and some others applications, need to be designed using a basic cartography with a suitable scale to the accuracy and extension of the plot.The Unmanned Aerial Vehicle (UAV) Photogrammetry covers the gap between classical manned aerial photogrammetry and hand- made surveying techniques because it works in the close-range domain, combining aerial and terrestrial photogrammetry, but also introduces low-cost alternatives. The aim of this work is developing of an accurate and low-cost method to characterize landslides located on the size of a road. It was applied at the kilometric point 339 belonging to the A92 dual carriageway, in the Abla municipal term, province of Almeria, Spain. A photogrammetric project was carried out from a set of images taken from an md4-200 Microdrones with an on-board calibrated camera 12 Megapixels Pentax Optio A40. The flight was previously planned to cover the whole extension of the embankment with three passes composed of 18 photos each one. All the images were taken with the vertical axe and it was registered 85% and 60% longitudinal and transversal overlaps respectively. The accuracy of the products, with planimetric and altimetric errors of 0.049 and 0.108m repectively, lets to take measurements of the landslide and projecting preventive and palliative actuations.

Preliminary applications of Landsat images and aerial photography for determining land-use, geologic, and hydrologic characteristics, Yampa River basin, Colorado and Wyoming

USGS Publications Warehouse

Heimes, F.J.; Moore, G.K.; Steele, T.D.

1978-01-01

Expanded energy- and recreation-related activities in the Yampa River basin, Colorado and Wyoming, have caused a rapid increase in economic development which will result in increased demand and competition for natural resources. In planning for efficient allocation of the basin 's natural resources, Landsat images and small-scale color and color-infrared photographs were used for selected geologic, hydrologic and land-use applications within the Yampa River basin. Applications of Landsat data included: (1) regional land-use classification and mapping, (2) lineament mapping, and (3) areal snow-cover mapping. Results from the Landsat investigations indicated that: (1) Landsat land-use classification maps, at a regional level, compared favorably with areal land-use patterns that were defined from available ground information, (2) lineaments were mapped in sufficient detail using recently developed techniques for interpreting aerial photographs, (3) snow cover generally could be mapped for large areas with the exception of some densely forested areas of the basin and areas having a large percentage of winter-season cloud cover. Aerial photographs were used for estimation of turbidity for eight stream locations in the basin. Spectral reflectance values obtained by digitizing photographs were compared with measured turbidity values. Results showed strong correlations (variances explained of greater than 90 percent) between spectral reflectance obtained from color photographs and measured turbidity values. (Woodard-USGS)

Metadata-assisted nonuniform atmospheric scattering model of image haze removal for medium-altitude unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Liu, Chunlei; Ding, Wenrui; Li, Hongguang; Li, Jiankun

2017-09-01

Haze removal is a nontrivial work for medium-altitude unmanned aerial vehicle (UAV) image processing because of the effects of light absorption and scattering. The challenges are attributed mainly to image distortion and detail blur during the long-distance and large-scale imaging process. In our work, a metadata-assisted nonuniform atmospheric scattering model is proposed to deal with the aforementioned problems of medium-altitude UAV. First, to better describe the real atmosphere, we propose a nonuniform atmospheric scattering model according to the aerosol distribution, which directly benefits the image distortion correction. Second, considering the characteristics of long-distance imaging, we calculate the depth map, which is an essential clue to modeling, on the basis of UAV metadata information. An accurate depth map reduces the color distortion compared with the depth of field obtained by other existing methods based on priors or assumptions. Furthermore, we use an adaptive median filter to address the problem of fuzzy details caused by the global airlight value. Experimental results on both real flight and synthetic images demonstrate that our proposed method outperforms four other existing haze removal methods.

Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas

NASA Astrophysics Data System (ADS)

Wu, Bo; Xie, Linfu; Hu, Han; Zhu, Qing; Yau, Eric

2018-05-01

Photorealistic three-dimensional (3D) models are fundamental to the spatial data infrastructure of a digital city, and have numerous potential applications in areas such as urban planning, urban management, urban monitoring, and urban environmental studies. Recent developments in aerial oblique photogrammetry based on aircraft or unmanned aerial vehicles (UAVs) offer promising techniques for 3D modeling. However, 3D models generated from aerial oblique imagery in urban areas with densely distributed high-rise buildings may show geometric defects and blurred textures, especially on building façades, due to problems such as occlusion and large camera tilt angles. Meanwhile, mobile mapping systems (MMSs) can capture terrestrial images of close-range objects from a complementary view on the ground at a high level of detail, but do not offer full coverage. The integration of aerial oblique imagery with terrestrial imagery offers promising opportunities to optimize 3D modeling in urban areas. This paper presents a novel method of integrating these two image types through automatic feature matching and combined bundle adjustment between them, and based on the integrated results to optimize the geometry and texture of the 3D models generated from aerial oblique imagery. Experimental analyses were conducted on two datasets of aerial and terrestrial images collected in Dortmund, Germany and in Hong Kong. The results indicate that the proposed approach effectively integrates images from the two platforms and thereby improves 3D modeling in urban areas.

Online phase measuring profilometry for rectilinear moving object by image correction

NASA Astrophysics Data System (ADS)

Yuan, Han; Cao, Yi-Ping; Chen, Chen; Wang, Ya-Pin

2015-11-01

In phase measuring profilometry (PMP), the object must be static for point-to-point reconstruction with the captured deformed patterns. While the object is rectilinearly moving online, the size and pixel position differences of the object in different captured deformed patterns do not meet the point-to-point requirement. We propose an online PMP based on image correction to measure the three-dimensional shape of the rectilinear moving object. In the proposed method, the deformed patterns captured by a charge-coupled diode camera are reprojected from the oblique view to an aerial view first and then translated based on the feature points of the object. This method makes the object appear stationary in the deformed patterns. Experimental results show the feasibility and efficiency of the proposed method.

Monitoring morphological changes in an arid zone by spaceborne images and aerial photography between 1945 - 2009; the Yamin Plateau, Israel

NASA Astrophysics Data System (ADS)

Hetz, Guy; Blumberg, Dan; Avraham, Dody; Cohen, Hai

2010-05-01

This research focuses on a geomorphic mapping of the Yamin Plateau in southern Israel which is part of the Yamin-Rotem Syncline and covers about 200 km2. This area has been restricted since the 1950s and therefore, provides a unique opportunity to study undisturbed geomorphic processes. Nowadays, the national nuclear waste depository is located in this area accepting waste from industrial factories, research institutes and hospitals. This is the main reason why environmental processes are of major interest in terms of landform changes in space and time. The exposed geology section of the Yamin Plateau mostly consists of the Miocene Hazeva Group where sedimentary processes started 20 million years ago and continued for 12-14 million years. Two formations of the Miocene Hazeva Group appear in the study area Zefa and Rotem. The compositions of these two formations are similar and sometimes defined as "the main sand body" in the Hazeva Group. The restriction of the area stopped the grazing and let the development of a biological soil crust on the surface. The research objective was to document and characterize landform changes from 1945 until 2009 within the Yamin Plateau based on spaceborne images and aerial photography. All the parameters we extracted in the laboratory were validated with field measurements. A combination of the spaceborne images, aerial photography and field measurements leads us to the following conclusions: The research results show that soil stabilization processes took place earlier than the area closure. Inspite of decreasing precipitation tendencies as measured during the last 50 years in Yamin Plateau, the vegetation cover increased from 55% in 1945 to 67% in 2009. The main reason for this is the area closure and reduction in grazing along with developing of vegetation and biological soil crusts. Field studies and image processing of aerial photographs and recent QuickBird images alongside grain-size distribution show that in the past there

Aerial LED signage by use of crossed-mirror array

NASA Astrophysics Data System (ADS)

Yamamoto, Hirotsugu; Kujime, Ryousuke; Bando, Hiroki; Suyama, Shiro

2013-03-01

3D representation of digital signage improves its significance and rapid notification of important points. Real 3D display techniques such as volumetric 3D displays are effective for use of 3D for public signs because it provides not only binocular disparity but also motion parallax and other cues, which will give 3D impression even people with abnormal binocular vision. Our goal is to realize aerial 3D LED signs. We have specially designed and fabricated a reflective optical device to form an aerial image of LEDs with a wide field angle. The developed reflective optical device composed of crossed-mirror array (CMA). CMA contains dihedral corner reflectors at each aperture. After double reflection, light rays emitted from an LED will converge into the corresponding image point. The depth between LED lamps is represented in the same depth in the floating 3D image. Floating image of LEDs was formed in wide range of incident angle with a peak reflectance at 35 deg. The image size of focused beam (point spread function) agreed to the apparent aperture size.

Aerial Radiological Measuring System (ARMS): systems, procedures and sensitivity (1976)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyns, P K

1976-07-01

This report describes the Aerial Radiological Measuring System (ARMS) designed and operated by EG and G, Inc., for the Energy Research and Development Administration's (ERDA) Division of Operational Safety with the cooperation of the Nuclear Regulatory Commission. Designed to rapidly survey large areas for low-level man-made radiation, the ARMS has also proven extremely useful in locating lost radioactive sources of relatively low activity. The system consists of sodium iodide scintillation detectors, data formatting and recording equipment, positioning equipment, meteorological instruments, direct readout hardware, and data analysis equipment. The instrumentation, operational procedures, data reduction techniques and system sensitivities are described, togethermore » with their applications and sample results.« less

Overall design of imaging spectrometer on-board light aircraft

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhongqi, H.; Zhengkui, C.; Changhua, C.

1996-11-01

Aerial remote sensing is the earliest remote sensing technical system and has gotten rapid development in recent years. The development of aerial remote sensing was dominated by high to medium altitude platform in the past, and now it is characterized by the diversity platform including planes of high-medium-low flying altitude, helicopter, airship, remotely controlled airplane, glider, and balloon. The widely used and rapidly developed platform recently is light aircraft. Early in the close of 1970s, Beijing Research Institute of Uranium Geology began aerial photography and geophysical survey using light aircraft, and put forward the overall design scheme of light aircraftmore » imaging spectral application system (LAISAS) in 19905. LAISAS is comprised of four subsystem. They are called measuring platform, data acquiring subsystem, ground testing and data processing subsystem respectively. The principal instruments of LAISAS include measuring platform controlled by inertia gyroscope, aerial spectrometer with high spectral resolution, imaging spectrometer, 3-channel scanner, 128-channel imaging spectrometer, GPS, illuminance-meter, and devices for atmospheric parameters measuring, ground testing, data correction and processing. LAISAS has the features of integrity from data acquisition to data processing and to application; of stability which guarantees the image quality and is comprised of measuring, ground testing device, and in-door data correction system; of exemplariness of integrated the technology of GIS, GPS, and Image Processing System; of practicality which embodied LAISAS with flexibility and high ratio of performance to cost. So, it can be used in the fields of fundamental research of Remote Sensing and large-scale mapping for resource exploration, environmental monitoring, calamity prediction, and military purpose.« less

Completely optical orientation determination for an unstabilized aerial three-line camera

NASA Astrophysics Data System (ADS)

Wohlfeil, Jürgen

2010-10-01

Aerial line cameras allow the fast acquisition of high-resolution images at low costs. Unfortunately the measurement of the camera's orientation with the necessary rate and precision is related with large effort, unless extensive camera stabilization is used. But also stabilization implicates high costs, weight, and power consumption. This contribution shows that it is possible to completely derive the absolute exterior orientation of an unstabilized line camera from its images and global position measurements. The presented approach is based on previous work on the determination of the relative orientation of subsequent lines using optical information from the remote sensing system. The relative orientation is used to pre-correct the line images, in which homologous points can reliably be determined using the SURF operator. Together with the position measurements these points are used to determine the absolute orientation from the relative orientations via bundle adjustment of a block of overlapping line images. The approach was tested at a flight with the DLR's RGB three-line camera MFC. To evaluate the precision of the resulting orientation the measurements of a high-end navigation system and ground control points are used.

Advanced Tie Feature Matching for the Registration of Mobile Mapping Imaging Data and Aerial Imagery

NASA Astrophysics Data System (ADS)

Jende, P.; Peter, M.; Gerke, M.; Vosselman, G.

2016-06-01

Mobile Mapping's ability to acquire high-resolution ground data is opposing unreliable localisation capabilities of satellite-based positioning systems in urban areas. Buildings shape canyons impeding a direct line-of-sight to navigation satellites resulting in a deficiency to accurately estimate the mobile platform's position. Consequently, acquired data products' positioning quality is considerably diminished. This issue has been widely addressed in the literature and research projects. However, a consistent compliance of sub-decimetre accuracy as well as a correction of errors in height remain unsolved. We propose a novel approach to enhance Mobile Mapping (MM) image orientation based on the utilisation of highly accurate orientation parameters derived from aerial imagery. In addition to that, the diminished exterior orientation parameters of the MM platform will be utilised as they enable the application of accurate matching techniques needed to derive reliable tie information. This tie information will then be used within an adjustment solution to correct affected MM data. This paper presents an advanced feature matching procedure as a prerequisite to the aforementioned orientation update. MM data is ortho-projected to gain a higher resemblance to aerial nadir data simplifying the images' geometry for matching. By utilising MM exterior orientation parameters, search windows may be used in conjunction with a selective keypoint detection and template matching. Originating from different sensor systems, however, difficulties arise with respect to changes in illumination, radiometry and a different original perspective. To respond to these challenges for feature detection, the procedure relies on detecting keypoints in only one image. Initial tests indicate a considerable improvement in comparison to classic detector/descriptor approaches in this particular matching scenario. This method leads to a significant reduction of outliers due to the limited availability

Estimation of carbon storage based on individual tree detection in Pinus densiflora stands using a fusion of aerial photography and LiDAR data.

PubMed

Kim, So-Ra; Kwak, Doo-Ahn; Lee, Woo-Kyun; oLee, Woo-Kyun; Son, Yowhan; Bae, Sang-Won; Kim, Choonsig; Yoo, Seongjin

2010-07-01

The objective of this study was to estimate the carbon storage capacity of Pinus densiflora stands using remotely sensed data by combining digital aerial photography with light detection and ranging (LiDAR) data. A digital canopy model (DCM), generated from the LiDAR data, was combined with aerial photography for segmenting crowns of individual trees. To eliminate errors in over and under-segmentation, the combined image was smoothed using a Gaussian filtering method. The processed image was then segmented into individual trees using a marker-controlled watershed segmentation method. After measuring the crown area from the segmented individual trees, the individual tree diameter at breast height (DBH) was estimated using a regression function developed from the relationship observed between the field-measured DBH and crown area. The above ground biomass of individual trees could be calculated by an image-derived DBH using a regression function developed by the Korea Forest Research Institute. The carbon storage, based on individual trees, was estimated by simple multiplication using the carbon conversion index (0.5), as suggested in guidelines from the Intergovernmental Panel on Climate Change. The mean carbon storage per individual tree was estimated and then compared with the field-measured value. This study suggested that the biomass and carbon storage in a large forest area can be effectively estimated using aerial photographs and LiDAR data.

Cadastral Audit and Assessments Using Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Cunningham, K.; Walker, G.; Stahlke, E.; Wilson, R.

2011-09-01

Ground surveys and remote sensing are integral to establishing fair and equitable property valuations necessary for real property taxation. The International Association of Assessing Officers (IAAO) has embraced aerial and street-view imaging as part of its standards related to property tax assessments and audits. New technologies, including unmanned aerial systems (UAS) paired with imaging sensors, will become more common as local governments work to ensure their cadastre and tax rolls are both accurate and complete. Trends in mapping technology have seen an evolution in platforms from large, expensive manned aircraft to very small, inexpensive UAS. Traditional methods of photogrammetry have also given way to new equipment and sensors: digital cameras, infrared imagers, light detection and ranging (LiDAR) laser scanners, and now synthetic aperture radar (SAR). At the University of Alaska Fairbanks (UAF), we work extensively with unmanned aerial systems equipped with each of these newer sensors. UAF has significant experience flying unmanned systems in the US National Airspace, having begun in 1969 with scientific rockets and expanded to unmanned aircraft in 2003. Ongoing field experience allows UAF to partner effectively with outside organizations to test and develop leading-edge research in UAS and remote sensing. This presentation will discuss our research related to various sensors and payloads for mapping. We will also share our experience with UAS and optical systems for creating some of the first cadastral surveys in rural Alaska.

Unmanned aerial vehicles (UAVs) for surveying marine fauna: a dugong case study.

PubMed

Hodgson, Amanda; Kelly, Natalie; Peel, David

2013-01-01

Aerial surveys of marine mammals are routinely conducted to assess and monitor species' habitat use and population status. In Australia, dugongs (Dugong dugon) are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs) may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km(2) area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph) capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98%) were subjectively classed as 'certain' (unmistakably dugongs). Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys.

Unmanned Aerial Vehicles (UAVs) for Surveying Marine Fauna: A Dugong Case Study

PubMed Central

Hodgson, Amanda; Kelly, Natalie; Peel, David

2013-01-01

Aerial surveys of marine mammals are routinely conducted to assess and monitor species’ habitat use and population status. In Australia, dugongs (Dugong dugon) are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs) may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km2 area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph) capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98%) were subjectively classed as ‘certain’ (unmistakably dugongs). Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys. PMID:24223967

Assessing Long-Term Seagrass Changes by Integrating a High-Spatial Resolution Image, Historical Aerial Photography and Field Data

NASA Astrophysics Data System (ADS)

Leon-Perez, M.; Hernandez, W. J.; Armstrong, R.

2016-02-01

Reported cases of seagrass loss have increased over the last 40 years, increasing the awareness of the need for assessing seagrass health. In situ monitoring has been the main method to assess spatial and temporal changes in seagrass ecosystem. Although remote sensing techniques with multispectral imagery have been recently used for these purposes, long-term analysis is limited to the sensor's mission life. The objective of this project is to determine long-term changes in seagrass habitat cover at Caja de Muertos Island Nature Reserve, by combining in situ data with a satellite image and historical aerial photography. A current satellite imagery of the WorldView-2 sensor was used to generate a 2014 benthic habitat map for the study area. The multispectral image was pre-processed using: conversion of digital numbers to radiance, and atmospheric and water column corrections. Object-based image analysis was used to segment the image into polygons representing different benthic habitats and to classify those habitats according to the classification scheme developed for this project. The scheme include the following benthic habitat categories: seagrass (sparse, dense and very dense), colonized hard bottom (sparse, dense and very dense), sand and mix algae on unconsolidated sediments. Field work was used to calibrate the satellite-derived benthic maps and to asses accuracy of the final products. In addition, a time series of satellite imagery and historic aerial photography from 1950 to 2014 provided data to assess long-term changes in seagrass habitat cover within the Reserve. Preliminary results show an increase in seagrass habitat cover, contrasting with the worldwide declining trend. The results of this study will provide valuable information for the conservation and management of seagrass habitat in the Caja de Muertos Island Nature Reserve.

Unmanned Aerial Vehicle (UAV) associated DTM quality evaluation and hazard assessment

NASA Astrophysics Data System (ADS)

Huang, Mei-Jen; Chen, Shao-Der; Chao, Yu-Jui; Chiang, Yi-Lin; Chang, Kuo-Jen

2014-05-01

Taiwan, due to the high seismicity and high annual rainfall, numerous landslides triggered every year and severe impacts affect the island. Concerning to the catastrophic landslides, the key information of landslide, including range of landslide, volume estimation and the subsequent evolution are important when analyzing the triggering mechanism, hazard assessment and mitigation. Thus, the morphological analysis gives a general overview for the landslides and been considered as one of the most fundamental information. We try to integrate several technologies, especially by Unmanned Aerial Vehicle (UAV) and multi-spectral camera, to decipher the consequence and the potential hazard, and the social impact. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precious information. Benefited of the advancing of informatics, remote-sensing and electric technologies, the Unmanned Aerial Vehicle (UAV) photogrammetry mas been improve significantly. The study tries to integrate several methods, including, 1) Remote-sensing images gathered by Unmanned Aerial Vehicle (UAV) and by aerial photos taken in different periods; 2) field in-situ geologic investigation; 3) Differential GPS, RTK GPS and Ground LiDAR field in-site geoinfomatics measurements; 4) Construct the DTMs before and after landslide, as well as the subsequent periods using UAV and aerial photos; 5) Discrete element method should be applied to understand the geomaterial composing the slope failure, for predicting earthquake-induced and rainfall-induced landslides displacement. First at all, we evaluate the Microdrones MD4-1000 UAV airphotos derived Digital Terrain Model (DTM). The ground resolution of the DSM point cloud of could be as high as 10 cm. By integrated 4 ground control point within an area of 56 hectares, compared with LiDAR DSM and filed RTK-GPS surveying, the mean error is as low as 6cm with a standard deviation of 17cm. The quality of the

Unmanned Aerial Systems and Spectroscopy for Remote Sensing Applications in Archaeology

NASA Astrophysics Data System (ADS)

Themistocleous, K.; Agapiou, A.; Cuca, B.; Hadjimitsis, D. G.

2015-04-01

Remote sensing has open up new dimensions in archaeological research. Although there has been significant progress in increasing the resolution of space/aerial sensors and image processing, the detection of the crop (and soil marks) formations, which relate to buried archaeological remains, are difficult to detect since these marks may not be visible in the images if observed over different period or at different spatial/spectral resolution. In order to support the improvement of earth observation remote sensing technologies specifically targeting archaeological research, a better understanding of the crop/soil marks formation needs to be studied in detail. In this paper the contribution of both Unmanned Aerial Systems as well ground spectroradiometers is discussed in a variety of examples applied in the eastern Mediterranean region (Cyprus and Greece) as well in Central Europe (Hungary). In- situ spectroradiometric campaigns can be applied for the removal of atmospheric impact to simultaneous satellite overpass images. In addition, as shown in this paper, the systematic collection of ground truth data prior to the satellite/aerial acquisition can be used to detect the optimum temporal and spectral resolution for the detection of stress vegetation related to buried archaeological remains. Moreover, phenological studies of the crops from the area of interest can be simulated to the potential sensors based on their Relative Response Filters and therefore prepare better the satellite-aerial campaigns. Ground data and the use of Unmanned Aerial Systems (UAS) can provide an increased insight for studying the formation of crop and soil marks. New algorithms such as vegetation indices and linear orthogonal equations for the enhancement of crop marks can be developed based on the specific spectral characteristics of the area. As well, UAS can be used for remote sensing applications in order to document, survey and model cultural heritage and archaeological sites.

Registration of Laser Scanning Point Clouds and Aerial Images Using either Artificial or Natural Tie Features

NASA Astrophysics Data System (ADS)

Rönnholm, P.; Haggrén, H.

2012-07-01

Integration of laser scanning data and photographs is an excellent combination regarding both redundancy and complementary. Applications of integration vary from sensor and data calibration to advanced classification and scene understanding. In this research, only airborne laser scanning and aerial images are considered. Currently, the initial registration is solved using direct orientation sensors GPS and inertial measurements. However, the accuracy is not usually sufficient for reliable integration of data sets, and thus the initial registration needs to be improved. A registration of data from different sources requires searching and measuring of accurate tie features. Usually, points, lines or planes are preferred as tie features. Therefore, the majority of resent methods rely highly on artificial objects, such as buildings, targets or road paintings. However, in many areas no such objects are available. For example in forestry areas, it would be advantageous to be able to improve registration between laser data and images without making additional ground measurements. Therefore, there is a need to solve registration using only natural features, such as vegetation and ground surfaces. Using vegetation as tie features is challenging, because the shape and even location of vegetation can change because of wind, for example. The aim of this article was to compare registration accuracies derived by using either artificial or natural tie features. The test area included urban objects as well as trees and other vegetation. In this area, two registrations were performed, firstly, using mainly built objects and, secondly, using only vegetation and ground surface. The registrations were solved applying the interactive orientation method. As a result, using artificial tie features leaded to a successful registration in all directions of the coordinate system axes. In the case of using natural tie features, however, the detection of correct heights was difficult causing

Emissions from Southeastern U.S. Grasslands and Pine Savannas: Comparison of Aerial and Ground Field Measurements with Laboratory Burns

EPA Science Inventory

Emissions from prescribed burns of forest and grass stands in western Florida were measured by simultaneous aerial and ground sampling. Results were compared with biomass gathered from the same stands and tested in an open burn laboratory test facility. Measurements included pol...

Use of Aerial Hyperspectral Imaging For Monitoring Forest Health

Treesearch

Milton O. Smith; Nolan J. Hess; Stephen Gulick; Lori G. Eckhardt; Roger D. Menard

2004-01-01

This project evaluates the effectiveness of aerial hyperspectral digital imagery in the assessment of forest health of loblolly stands in central Alabama. The imagery covers 50 square miles, in Bibb and Hale Counties, south of Tuscaloosa, AL, which includes intensive managed forest industry sites and National Forest lands with multiple use objectives. Loblolly stands...

Mapping and characterizing selected canopy tree species at the Angkor World Heritage site in Cambodia using aerial data.

PubMed

Singh, Minerva; Evans, Damian; Tan, Boun Suy; Nin, Chan Samean

2015-01-01

At present, there is very limited information on the ecology, distribution, and structure of Cambodia's tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman's rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables.

Mapping and Characterizing Selected Canopy Tree Species at the Angkor World Heritage Site in Cambodia Using Aerial Data

PubMed Central

Singh, Minerva; Evans, Damian; Tan, Boun Suy; Nin, Chan Samean

2015-01-01

At present, there is very limited information on the ecology, distribution, and structure of Cambodia’s tree species to warrant suitable conservation measures. The aim of this study was to assess various methods of analysis of aerial imagery for characterization of the forest mensuration variables (i.e., tree height and crown width) of selected tree species found in the forested region around the temples of Angkor Thom, Cambodia. Object-based image analysis (OBIA) was used (using multiresolution segmentation) to delineate individual tree crowns from very-high-resolution (VHR) aerial imagery and light detection and ranging (LiDAR) data. Crown width and tree height values that were extracted using multiresolution segmentation showed a high level of congruence with field-measured values of the trees (Spearman’s rho 0.782 and 0.589, respectively). Individual tree crowns that were delineated from aerial imagery using multiresolution segmentation had a high level of segmentation accuracy (69.22%), whereas tree crowns delineated using watershed segmentation underestimated the field-measured tree crown widths. Both spectral angle mapper (SAM) and maximum likelihood (ML) classifications were applied to the aerial imagery for mapping of selected tree species. The latter was found to be more suitable for tree species classification. Individual tree species were identified with high accuracy. Inclusion of textural information further improved species identification, albeit marginally. Our findings suggest that VHR aerial imagery, in conjunction with OBIA-based segmentation methods (such as multiresolution segmentation) and supervised classification techniques are useful for tree species mapping and for studies of the forest mensuration variables. PMID:25902148

Volumetric calculation using low cost unmanned aerial vehicle (UAV) approach

NASA Astrophysics Data System (ADS)

Rahman, A. A. Ab; Maulud, K. N. Abdul; Mohd, F. A.; Jaafar, O.; Tahar, K. N.

2017-12-01

Unmanned Aerial Vehicles (UAV) technology has evolved dramatically in the 21st century. It is used by both military and general public for recreational purposes and mapping work. Operating cost for UAV is much cheaper compared to that of normal aircraft and it does not require a large work space. The UAV systems have similar functions with the LIDAR and satellite images technologies. These systems require a huge cost, labour and time consumption to produce elevation and dimension data. Measurement of difficult objects such as water tank can also be done by using UAV. The purpose of this paper is to show the capability of UAV to compute the volume of water tank based on a different number of images and control points. The results were compared with the actual volume of the tank to validate the measurement. In this study, the image acquisition was done using Phantom 3 Professional, which is a low cost UAV. The analysis in this study is based on different volume computations using two and four control points with variety set of UAV images. The results show that more images will provide a better quality measurement. With 95 images and four GCP, the error percentage to the actual volume is about 5%. Four controls are enough to get good results but more images are needed, estimated about 115 until 220 images. All in all, it can be concluded that the low cost UAV has a potential to be used for volume of water and dimension measurement.

Measurement Capabilities of the DOE ARM Aerial Facility

NASA Astrophysics Data System (ADS)

Schmid, B.; Tomlinson, J. M.; Hubbe, J.; Comstock, J. M.; Kluzek, C. D.; Chand, D.; Pekour, M. S.

2012-12-01

The Department of Energy Atmospheric Radiation Measurement (ARM) Program is a climate research user facility operating stationary ground sites in three important climatic regimes that provide long-term measurements of climate relevant properties. ARM also operates mobile ground- and ship-based facilities to conduct shorter field campaigns (6-12 months) to investigate understudied climate regimes around the globe. Finally, airborne observations by ARM's Aerial Facility (AAF) enhance the surface-based ARM measurements by providing high-resolution in situ measurements for process understanding, retrieval algorithm development, and model evaluation that is not possible using ground-based techniques. AAF started out in 2007 as a "virtual hangar" with no dedicated aircraft and only a small number of instruments owned by ARM. In this mode, AAF successfully carried out several missions contracting with organizations and investigators who provided their research aircraft and instrumentation. In 2009, the Battelle owned G-1 aircraft was included in the ARM facility. The G-1 is a large twin turboprop aircraft, capable of measurements up to altitudes of 7.5 km and a range of 2,800 kilometers. Furthermore the American Recovery and Reinvestment Act of 2009 provided funding for the procurement of seventeen new instruments to be used aboard the G-1 and other AAF virtual-hangar aircraft. AAF now executes missions in the virtual- and real-hangar mode producing freely available datasets for studying aerosol, cloud, and radiative processes in the atmosphere. AAF is also heavily engaged in the maturation and testing of newly developed airborne sensors to help foster the next generation of airborne instruments. In the presentation we will showcase science applications based on measurements from recent field campaigns such as CARES, CALWATER and TCAP.

The sky is the limit: reconstructing physical geography fieldwork from an aerial perspective

NASA Astrophysics Data System (ADS)

Williams, R.; Tooth, S.; Gibson, M.; Barrett, B.

2017-12-01

In an era of rapid geographical data acquisition, interpretations of remote sensing products (e.g. aerial photographs, satellite images, digital elevation models) are an integral part of many undergraduate geography degree schemes but there are fewer opportunities for collection and processing of primary remote sensing data. Unmanned aerial vehicles (UAVs) provide a relatively cheap opportunity to introduce the principles and practice of airborne remote sensing into fieldcourses, enabling students to learn about image acquisition, data processing and interpretation of derived products. Three case studies illustrate how a low cost DJI Phantom UAV can be used by students to acquire images that can be processed using off the shelf Structure-from-Motion photogrammetry software. Two case studies are drawn from an international fieldcourse that takes students to field sites that are the focus of current funded research whilst a third case study is from a course in topographic mapping. Results from a student questionnaire and analysis of assessed student reports showed that using UAVs in fieldwork enhanced student engagement with themes on their fieldcourse and equipped them with data processing skills. The derivation of bespoke orthophotos and Digital Elevation Models also provided students with opportunities to gain insight into the various data quality issues that are associated with aerial imagery acquisition and topographic reconstruction, although additional training is required to maximise this potential. Recognition of the successes and limitations of this teaching intervention provides scope for improving exercises that use UAVs and other technologies in future fieldcourses. UAVs are enabling both a reconstruction of how we measure the Earth's surface and a reconstruction of how students do fieldwork.

Aerial Measuring System Sensor Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. S. Detwiler

2002-04-01

This project deals with the modeling the Aerial Measuring System (AMS) fixed-wing and rotary-wing sensor systems, which are critical U.S. Department of Energy's National Nuclear Security Administration (NNSA) Consequence Management assets. The fixed-wing system is critical in detecting lost or stolen radiography or medical sources, or mixed fission products as from a commercial power plant release at high flying altitudes. The helicopter is typically used at lower altitudes to determine ground contamination, such as in measuring americium from a plutonium ground dispersal during a cleanup. Since the sensitivity of these instruments as a function of altitude is crucial in estimatingmore » detection limits of various ground contaminations and necessary count times, a characterization of their sensitivity as a function of altitude and energy is needed. Experimental data at altitude as well as laboratory benchmarks is important to insure that the strong effects of air attenuation are modeled correctly. The modeling presented here is the first attempt at such a characterization of the equipment for flying altitudes. The sodium iodide (NaI) sensors utilized with these systems were characterized using the Monte Carlo N-Particle code (MCNP) developed at Los Alamos National Laboratory. For the fixed wing system, calculations modeled the spectral response for the 3-element NaI detector pod and High-Purity Germanium (HPGe) detector, in the relevant energy range of 50 keV to 3 MeV. NaI detector responses were simulated for both point and distributed surface sources as a function of gamma energy and flying altitude. For point sources, photopeak efficiencies were calculated for a zero radial distance and an offset equal to the altitude. For distributed sources approximating an infinite plane, gross count efficiencies were calculated and normalized to a uniform surface deposition of 1 {micro}Ci/m{sup 2}. The helicopter calculations modeled the transport of americium-241 ({sup

Model-based conifer crown surface reconstruction from multi-ocular high-resolution aerial imagery

NASA Astrophysics Data System (ADS)

Sheng, Yongwei

2000-12-01

Tree crown parameters such as width, height, shape and crown closure are desirable in forestry and ecological studies, but they are time-consuming and labor intensive to measure in the field. The stereoscopic capability of high-resolution aerial imagery provides a way to crown surface reconstruction. Existing photogrammetric algorithms designed to map terrain surfaces, however, cannot adequately extract crown surfaces, especially for steep conifer crowns. Considering crown surface reconstruction in a broader context of tree characterization from aerial images, we develop a rigorous perspective tree image formation model to bridge image-based tree extraction and crown surface reconstruction, and an integrated model-based approach to conifer crown surface reconstruction. Based on the fact that most conifer crowns are in a solid geometric form, conifer crowns are modeled as a generalized hemi-ellipsoid. Both the automatic and semi-automatic approaches are investigated to optimal tree model development from multi-ocular images. The semi-automatic 3D tree interpreter developed in this thesis is able to efficiently extract reliable tree parameters and tree models in complicated tree stands. This thesis starts with a sophisticated stereo matching algorithm, and incorporates tree models to guide stereo matching. The following critical problems are addressed in the model-based surface reconstruction process: (1) the problem of surface model composition from tree models, (2) the occlusion problem in disparity prediction from tree models, (3) the problem of integrating the predicted disparities into image matching, (4) the tree model edge effect reduction on the disparity map, (5) the occlusion problem in orthophoto production, and (6) the foreshortening problem in image matching, which is very serious for conifer crown surfaces. Solutions to the above problems are necessary for successful crown surface reconstruction. The model-based approach was applied to recover the

Aerial photography for sensing plant anomalies

NASA Technical Reports Server (NTRS)

Gausman, H. W.; Cardenas, R.; Hart, W. G.

1970-01-01

Changes in the red tonal response of Kodak Ektrachrome Infrared Aero 8443 film (EIR) are often incorrectly attributed solely to variations in infrared light reflectance of plant leaves, when the primary influence is a difference in visible light reflectance induced by varying chlorophyll contents. Comparisons are made among aerial photographic images of high- and low-chlorophyll foliage. New growth, foot rot, and boron and chloride nutrient toxicites produce low-chlorophyll foliage, and EIR transparency images of light red or white compared with dark-red images of high-chlorophyll foliage. Deposits of the sooty mold fungus that subsists on the honeydew produced by brown soft scale insects, obscure the citrus leaves' green color. Infected trees appear as black images on EIR film transparencies compared with red images of healthy trees.

Assessing a potential solution for spatially referencing of historical aerial photography in South Africa

NASA Astrophysics Data System (ADS)

Denner, Michele; Raubenheimer, Jacobus H.

2018-05-01

Historical aerial photography has become a valuable commodity in any country, as it provides a precise record of historical land management over time. In a developing country, such as South Africa, that has undergone enormous political and social change over the last years, such photography is invaluable as it provides a clear indication of past injustices and serves as an aid to addressing post-apartheid issues such as land reform and land redistribution. National mapping organisations throughout the world have vast repositories of such historical aerial photography. In order to effectively use these datasets in today's digital environment requires that it be georeferenced to an accuracy that is suitable for the intended purpose. Using image-to-image georeferencing techniques, this research sought to determine the accuracies achievable for ortho-rectifying large volumes of historical aerial imagery, against the national standard for ortho-rectification in South Africa, using two different types of scanning equipment. The research conducted four tests using aerial photography from different time epochs over a period of sixty years, where the ortho-rectification matched each test to an already ortho-rectified mosaic of a developed area of mixed land use. The results of each test were assessed in terms of visual accuracy, spatial accuracy and conformance to the national standard for ortho-rectification in South Africa. The results showed a decrease in the overall accuracy of the image as the epoch range between the historical image and the reference image increased. Recommendations on the applications possible given the different epoch ranges and scanning equipment used are provided.

Evaluation of remote sensing aerial systems in existing transportation practices, phase II.

DOT National Transportation Integrated Search

2011-06-01

A low-cost aerial platform represents a flexible tool for acquiring high-resolution images for ground areas of interest. The geo-referencing of objects within these images could benefit civil engineers in a variety of research areas including, but no...

Intra- and interspecific variation in tropical tree and liana phenology derived from Unmanned Aerial Vehicle images

NASA Astrophysics Data System (ADS)

Bohlman, S.; Park, J.; Muller-Landau, H. C.; Rifai, S. W.; Dandois, J. P.

2017-12-01

Phenology is a critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical tree and liana phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. Spectral, texture, and image information was extracted from the UAV images for individual tree crowns, which was then used as inputs for a machine learning algorithm to predict percent leaf and branch cover. We obtained the species identities of 2000 crowns in the images via field mapping. The objectives of this study are to (1) determined if machine learning algorithms, applied to UAV images, can effectively quantify changes in leaf cover, which we term "deciduousness; (2) determine how liana cover effects deciduousness and (3) test how well UAV-derived deciduousness patterns match satellite-derived temporal patterns. Machine learning algorithms trained on a variety of image parameters could effectively determine leaf cover, despite variation in lighting and viewing angles. Crowns with higher liana cover have less overall deciduousness (tree + liana together) than crowns with lower liana cover. Individual crown deciduousness, summed over all crowns measured in the 50-ha plot, showed a similar seasonal pattern as MODIS EVI composited over 10 years. However

Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration

NASA Technical Reports Server (NTRS)

Thakoor, Sarita; Lay, Norman; Hine, Butler; Zornetzer, Steven

2004-01-01

Concepts are being investigated for exploratory missions to Mars based on Bioinspired Engineering of Exploration Systems (BEES), which is a guiding principle of this effort to develop biomorphic explorers. The novelty lies in the use of a robust telecom architecture for mission data return, utilizing multiple local relays (including the lander itself as a local relay and the explorers in the dual role of a local relay) to enable ranges 10 to 1,000 km and downlink of color imagery. As illustrated in Figure 1, multiple microflyers that can be both surface or aerially launched are envisioned in shepherding, metamorphic, and imaging roles. These microflyers imbibe key bio-inspired principles in their flight control, navigation, and visual search operations. Honey-bee inspired algorithms utilizing visual cues to perform autonomous navigation operations such as terrain following will be utilized. The instrument suite will consist of a panoramic imager and polarization imager specifically optimized to detect ice and water. For microflyers, particularly at small sizes, bio-inspired solutions appear to offer better alternate solutions than conventional engineered approaches. This investigation addresses a wide range of interrelated issues, including desired scientific data, sizes, rates, and communication ranges that can be accomplished in alternative mission scenarios. The mission illustrated in Figure 1 offers the most robust telecom architecture and the longest range for exploration with two landers being available as main local relays in addition to an ephemeral aerial probe local relay. The shepherding or metamorphic plane are in their dual role as local relays and image data collection/storage nodes. Appropriate placement of the landing site for the scout lander with respect to the main mission lander can allow coverage of extremely large ranges and enable exhaustive survey of the area of interest. In particular, this mission could help with the path planning and risk

Use of micro unmanned aerial vehicles for roadside condition assessment

DOT National Transportation Integrated Search

2010-12-01

Micro unmanned aerial vehicles (MUAVs) that are equipped with digital imaging systems and global : positioning systems provide a potential opportunity for improving the effectiveness and safety of roadside : condition and inventory surveys. This stud...

Aerial thermography for energy efficiency of buildings: the ChoT project

NASA Astrophysics Data System (ADS)

Mandanici, Emanuele; Conte, Paolo

2016-10-01

The ChoT project aims at analysing the potential of aerial thermal imagery to produce large scale datasets for energetic efficiency analyses and policies in urban environments. It is funded by the Italian Ministry of Education, University and Research (MIUR) in the framework of the SIR 2014 (Scientific Independence of young Researchers) programme. The city of Bologna (Italy) was chosen as the case study. The acquisition of thermal infrared images at different times by multiple aerial flights is one of the main tasks of the project. The present paper provides an overview of the ChoT project, but it delves into some specific aspects of the data processing chain: the computing of the radiometric quantities of the atmosphere, the estimation of surface emissivity (through an object-oriented classification applied on a very high resolution multispectral image, to distinguish among the major roofing materials) and sky-view factor (by means of a digital surface model). To collect ground truth data, the surface temperature of roofs and road pavings was measured at several locations at the same time as the aircraft acquired the thermal images. Furthermore, the emissivity of some roofing materials was estimated by means of a thermal camera and a contact probe. All the surveys were georeferenced by GPS. The results of the first surveying campaign demonstrate the high sensitivity of the model to the variability of the surface emissivity and the atmospheric parameters.

Enhancement of spectral quality of archival aerial photographs using satellite imagery for detection of land cover

NASA Astrophysics Data System (ADS)

Siok, Katarzyna; Jenerowicz, Agnieszka; Woroszkiewicz, Małgorzata

2017-07-01

Archival aerial photographs are often the only reliable source of information about the area. However, these data are single-band data that do not allow unambiguous detection of particular forms of land cover. Thus, the authors of this article seek to develop a method of coloring panchromatic aerial photographs, which enable increasing the spectral information of such images. The study used data integration algorithms based on pansharpening, implemented in commonly used remote sensing programs: ERDAS, ENVI, and PCI. Aerial photos and Landsat multispectral data recorded in 1987 and 2016 were chosen. This study proposes the use of modified intensity-hue-saturation and Brovey methods. The use of these methods enabled the addition of red-green-blue (RGB) components to monochrome images, thus enhancing their interpretability and spectral quality. The limitations of the proposed method relate to the availability of RGB satellite imagery, the accuracy of mutual orientation of the aerial and the satellite data, and the imperfection of archival aerial photographs. Therefore, it should be expected that the results of coloring will not be perfect compared to the results of the fusion of recent data with a similar ground sampling resolution, but still, they will allow a more accurate and efficient classification of land cover registered on archival aerial photographs.

Semantic Segmentation and Difference Extraction via Time Series Aerial Video Camera and its Application

NASA Astrophysics Data System (ADS)

Amit, S. N. K.; Saito, S.; Sasaki, S.; Kiyoki, Y.; Aoki, Y.

2015-04-01

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

Pasadena, California Anaglyph with Aerial Photo Overlay

NASA Technical Reports Server (NTRS)

2000-01-01

This anaglyph shows NASA's Jet Propulsion Laboratory (JPL) in Pasadena, California. Red-blue glasses are required to see the 3-D effect. The surrounding residential areas of La Canada-Flintridge (to the left) and Altadena/Pasadena (to the right) are also shown. JPL is located at the base of the San Gabriel Mountains, an actively growing mountain range, seen towards the top of the image. The large canyon coming out of the mountains (top to bottom of image) is the Arroyo Seco, which is a major drainage channel for the mountains. Sand and gravel removal operations in the lower part of the arroyo (bottom of image) are removing debris brought down by flood and mudflow events. Old landslide scars (lobe-shaped features) are seen in the arroyo, evidence that living near steep canyon slopes in tectonically active areas can be hazardous. The data can also be utilized by recreational users such as hikers enjoying the natural beauty of these rugged mountains.

This anaglyph was generated using topographic data from the Shuttle Radar Topography Mission to create two differing perspectives of a single image, one perspective for each eye. The detailed aerial image was provided by U. S. Geological Survey digital orthophotography. Each point in the image is shifted slightly, depending on its elevation. When viewed through special glasses, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.

The Shuttle Radar Topography Mission (SRTM), launched on February 11,2000, uses the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. The mission is designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, an additional C-band imaging antenna

"A" Is for Aerial Maps and Art

ERIC Educational Resources Information Center

Todd, Reese H.; Delahunty, Tina

2007-01-01

The technology of satellite imagery and remote sensing adds a new dimension to teaching and learning about maps with elementary school children. Just a click of the mouse brings into view some images of the world that could only be imagined a generation ago. Close-up aerial pictures of the school and neighborhood quickly catch the interest of…

Spectral Imaging from Uavs Under Varying Illumination Conditions

NASA Astrophysics Data System (ADS)

Hakala, T.; Honkavaara, E.; Saari, H.; Mäkynen, J.; Kaivosoja, J.; Pesonen, L.; Pölönen, I.

2013-08-01

Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. For applications requiring aerial images, a simple consumer camera provides acceptable data. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. These images can be assembled in spectral data cubes with stereoscopic overlaps. On field the weather conditions vary and the UAV operator often has to decide between flight in sub optimal conditions and no flight. Our objective was to investigate methods for quantitative radiometric processing of images taken under varying illumination conditions, thus expanding the range of weather conditions during which successful imaging flights can be made. A new method that is based on insitu measurement of irradiance either in UAV platform or in ground was developed. We tested the methods in a precision agriculture application using realistic data collected in difficult illumination conditions. Internal homogeneity of the original image data (average coefficient of variation in overlapping images) was 0.14-0.18. In the corrected data, the homogeneity was 0.10-0.12 with a correction based on broadband irradiance measured in UAV, 0.07-0.09 with a correction based on spectral irradiance measurement on ground, and 0.05-0.08 with a radiometric block adjustment based on image data. Our results were very promising, indicating that quantitative UAV based remote sensing could be operational in diverse conditions, which is prerequisite for many environmental remote sensing applications.

Aerial Photography Summary Record System

USGS Publications Warehouse

,

1998-01-01

The Aerial Photography Summary Record System (APSRS) describes aerial photography projects that meet specified criteria over a given geographic area of the United States and its territories. Aerial photographs are an important tool in cartography and a number of other professions. Land use planners, real estate developers, lawyers, environmental specialists, and many other professionals rely on detailed and timely aerial photographs. Until 1975, there was no systematic approach to locate an aerial photograph, or series of photographs, quickly and easily. In that year, the U.S. Geological Survey (USGS) inaugurated the APSRS, which has become a standard reference for users of aerial photographs.

1. NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. NORTHWEST OBLIQUE AERIAL VIEW OF FORT DELAWARE AND PEA PATCH ISLAND. REMAINS OF SEA WALL VISIBLE IN FOREGROUND AND RIGHT OF IMAGE. - Fort Delaware, Sea Wall, Pea Patch Island, Delaware City, New Castle County, DE

Building Roof Segmentation from Aerial Images Using a Line-and Region-Based Watershed Segmentation Technique

PubMed Central

Merabet, Youssef El; Meurie, Cyril; Ruichek, Yassine; Sbihi, Abderrahmane; Touahni, Raja

2015-01-01

In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans) based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc.) affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM), 84% with mean shift, 82% with color structure code (CSC), 80% with efficient graph-based segmentation algorithm (EGBIS) and 71% with JSEG. PMID:25648706

The future of structural fieldwork - UAV assisted aerial photogrammetry

NASA Astrophysics Data System (ADS)

Vollgger, Stefan; Cruden, Alexander

2015-04-01

Unmanned aerial vehicles (UAVs), commonly referred to as drones, are opening new and low cost possibilities to acquire high-resolution aerial images and digital surface models (DSM) for applications in structural geology. UAVs can be programmed to fly autonomously along a user defined grid to systematically capture high-resolution photographs, even in difficult to access areas. The photographs are subsequently processed using software that employ SIFT (scale invariant feature transform) and SFM (structure from motion) algorithms. These photogrammetric routines allow the extraction of spatial information (3D point clouds, digital elevation models, 3D meshes, orthophotos) from 2D images. Depending on flight altitude and camera setup, sub-centimeter spatial resolutions can be achieved. By "digitally mapping" georeferenced 3D models and images, orientation data can be extracted directly and used to analyse the structural framework of the mapped object or area. We present UAV assisted aerial mapping results from a coastal platform near Cape Liptrap (Victoria, Australia), where deformed metasediments of the Palaeozoic Lachlan Fold Belt are exposed. We also show how orientation and spatial information of brittle and ductile structures extracted from the photogrammetric model can be linked to the progressive development of folds and faults in the region. Even though there are both technical and legislative limitations, which might prohibit the use of UAVs without prior commercial licensing and training, the benefits that arise from the resulting high-resolution, photorealistic models can substantially contribute to the collection of new data and insights for applications in structural geology.

Toward Automatic Georeferencing of Archival Aerial Photogrammetric Surveys

NASA Astrophysics Data System (ADS)

Giordano, S.; Le Bris, A.; Mallet, C.

2018-05-01

Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes over the past 100 years. They provide a relatively dense temporal sampling of the territories with very high spatial resolution. Such time series image analysis is a mandatory baseline for a large variety of long-term environmental monitoring studies. The current bottleneck for accurate comparison between epochs is their fine georeferencing step. No fully automatic method has been proposed yet and existing studies are rather limited in terms of area and number of dates. State-of-the art shows that the major challenge is the identification of ground references: cartographic coordinates and their position in the archival images. This task is manually performed, and extremely time-consuming. This paper proposes to use a photogrammetric approach, and states that the 3D information that can be computed is the key to full automation. Its original idea lies in a 2-step approach: (i) the computation of a coarse absolute image orientation; (ii) the use of the coarse Digital Surface Model (DSM) information for automatic absolute image orientation. It only relies on a recent orthoimage+DSM, used as master reference for all epochs. The coarse orthoimage, compared with such a reference, allows the identification of dense ground references and the coarse DSM provides their position in the archival images. Results on two areas and 5 dates show that this method is compatible with long and dense archival aerial image series. Satisfactory planimetric and altimetric accuracies are reported, with variations depending on the ground sampling distance of the images and the location of the Ground Control Points.

Calculated Drag of an Aerial Refueling Assembly Through Airplane Performance Analysis

NASA Technical Reports Server (NTRS)

Vachon, Jake; Ray, Ronald; Calianno, Carl

2004-01-01

This viewgraph document reviews NASA Dryden's work on Aerial refueling, with specific interest in calculating the drag of the refueling system. The aerodynamic drag of an aerial refueling assembly was calculated during the Automated Aerial Refueling project at the NASA Dryden Flight Research Center. An F/A-18A airplane was specially instrumented to obtain accurate fuel flow measurements and to determine engine thrust

True Ortho Generation of Urban Area Using High Resolution Aerial Photos

NASA Astrophysics Data System (ADS)

Hu, Yong; Stanley, David; Xin, Yubin

2016-06-01

The pros and cons of existing methods for true ortho generation are analyzed based on a critical literature review for its two major processing stages: visibility analysis and occlusion compensation. They process frame and pushbroom images using different algorithms for visibility analysis due to the need of perspective centers used by the z-buffer (or alike) techniques. For occlusion compensation, the pixel-based approach likely results in excessive seamlines in the ortho-rectified images due to the use of a quality measure on the pixel-by-pixel rating basis. In this paper, we proposed innovative solutions to tackle the aforementioned problems. For visibility analysis, an elevation buffer technique is introduced to employ the plain elevations instead of the distances from perspective centers by z-buffer, and has the advantage of sensor independency. A segment oriented strategy is developed to evaluate a plain cost measure per segment for occlusion compensation instead of the tedious quality rating per pixel. The cost measure directly evaluates the imaging geometry characteristics in ground space, and is also sensor independent. Experimental results are demonstrated using aerial photos acquired by UltraCam camera.

Monitoring Seabirds and Marine Mammals by Georeferenced Aerial Photography

NASA Astrophysics Data System (ADS)

Kemper, G.; Weidauer, A.; Coppack, T.

2016-06-01

to distinguish biological from non-biological signals. Each detected seabird or marine mammal signal is identified to species level or assigned to a species group and automatically saved into a geo-database for subsequent quality assurance, geo-statistical analyses and data export to third-party users. The relative size of a detected object can be accurately measured which provides key information for species-identification. During the development and testing of this system until 2015, more than 40 surveys have produced around 500.000 digital aerial images, of which some were taken in specially protected areas (SPA) of the Baltic Sea and thus include a wide range of relevant species. Here, we present the technical principles of this comparatively new survey approach and discuss the key methodological challenges related to optimizing survey design and workflow in view of the pending regulatory requirements for effective environmental impact assessments.

Study on Practical Technologies of Aerial Triangulation for Real Scene 3d Moeling with Oblique Photography

NASA Astrophysics Data System (ADS)

Cai, Z.; Liu, W.; Luo, G.; Xiang, Z.

2018-04-01

The key technologies in the real scene 3D modeling of oblique photography mainly include the data acquisition of oblique photography, layout and surveying of photo control points, oblique camera calibration, aerial triangulation, dense matching of multi-angle image, building of triangulation irregular network (TIN) and TIN simplification and automatic texture mapping, among which aerial triangulation is the core and the results of aerial triangulation directly affect the later model effect and the corresponding data accuracy. Starting from this point of view, this paper aims to study the practical technologies of aerial triangulation for real scene 3D modeling with oblique photography and finally proposes a technical method of aerial triangulation with oblique photography which can be put into practice.

The Development and Flight Testing of an Aerially Deployed Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Smith, Andrew

An investigation into the feasibility of aerial deployed unmanned aerial vehicles was completed. The investigation included the development and flight testing of multiple unmanned aerial systems to investigate the different components of potential aerial deployment missions. The project consisted of two main objectives; the first objective dealt with the development of an airframe capable of surviving aerial deployment from a rocket and then self assembling from its stowed configuration into its flight configuration. The second objective focused on the development of an autopilot capable of performing basic guidance, navigation, and control following aerial deployment. To accomplish these two objectives multiple airframes were developed to verify their completion experimentally. The first portion of the project, investigating the feasibility of surviving an aerial deployment, was completed using a fixed wing glider that following a successful deployment had 52 seconds of controlled flight. Before developing the autopilot in the second phase of the project, the glider was significantly upgraded to fix faults discovered in the glider flight testing and to enhance the system capabilities. Unfortunately to conform to outdoor flight restrictions imposed by the university and the Federal Aviation Administration it was required to switch airframes before flight testing of the new fixed wing platform could begin. As a result, an autopilot was developed for a quadrotor and verified experimentally completely indoors to remain within the limits of governing policies.

Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

NASA Astrophysics Data System (ADS)

Li, Xiaoxiao; Myint, Soe W.; Zhang, Yujia; Galletti, Chritopher; Zhang, Xiaoxiang; Turner, Billie L.

2014-12-01

Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

Ultramap v3 - a Revolution in Aerial Photogrammetry

NASA Astrophysics Data System (ADS)

Reitinger, B.; Sormann, M.; Zebedin, L.; Schachinger, B.; Hoefler, M.; Tomasi, R.; Lamperter, M.; Gruber, B.; Schiester, G.; Kobald, M.; Unger, M.; Klaus, A.; Bernoegger, S.; Karner, K.; Wiechert, A.; Ponticelli, M.; Gruber, M.

2012-07-01

In the last years, Microsoft has driven innovation in the aerial photogrammetry community. Besides the market leading camera technology, UltraMap has grown to an outstanding photogrammetric workflow system which enables users to effectively work with large digital aerial image blocks in a highly automated way. Best example is the project-based color balancing approach which automatically balances images to a homogeneous block. UltraMap V3 continues innovation, and offers a revolution in terms of ortho processing. A fully automated dense matching module strives for high precision digital surface models (DSMs) which are calculated either on CPUs or on GPUs using a distributed processing framework. By applying constrained filtering algorithms, a digital terrain model can be derived which in turn can be used for fully automated traditional ortho texturing. By having the knowledge about the underlying geometry, seamlines can be generated automatically by applying cost functions in order to minimize visual disturbing artifacts. By exploiting the generated DSM information, a DSMOrtho is created using the balanced input images. Again, seamlines are detected automatically resulting in an automatically balanced ortho mosaic. Interactive block-based radiometric adjustments lead to a high quality ortho product based on UltraCam imagery. UltraMap v3 is the first fully integrated and interactive solution for supporting UltraCam images at best in order to deliver DSM and ortho imagery.

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

PubMed

Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

2017-02-10

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

Method of radiometric quality assessment of NIR images acquired with a custom sensor mounted on an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Wierzbicki, Damian; Fryskowska, Anna; Kedzierski, Michal; Wojtkowska, Michalina; Delis, Paulina

2018-01-01

Unmanned aerial vehicles are suited to various photogrammetry and remote sensing missions. Such platforms are equipped with various optoelectronic sensors imaging in the visible and infrared spectral ranges and also thermal sensors. Nowadays, near-infrared (NIR) images acquired from low altitudes are often used for producing orthophoto maps for precision agriculture among other things. One major problem results from the application of low-cost custom and compact NIR cameras with wide-angle lenses introducing vignetting. In numerous cases, such cameras acquire low radiometric quality images depending on the lighting conditions. The paper presents a method of radiometric quality assessment of low-altitude NIR imagery data from a custom sensor. The method utilizes statistical analysis of NIR images. The data used for the analyses were acquired from various altitudes in various weather and lighting conditions. An objective NIR imagery quality index was determined as a result of the research. The results obtained using this index enabled the classification of images into three categories: good, medium, and low radiometric quality. The classification makes it possible to determine the a priori error of the acquired images and assess whether a rerun of the photogrammetric flight is necessary.

Landscape Response to the 1980 Eruption of Mount St. Helens: Using Historical Aerial Photography to Measure Surface Change

NASA Astrophysics Data System (ADS)

Sweeney, K.; Major, J. J.

2016-12-01

Advances in structure-from-motion (SfM) photogrammetry and point cloud comparison have fueled a proliferation of studies using modern imagery to monitor geomorphic change. These techniques also have obvious applications for reconstructing historical landscapes from vertical aerial imagery, but known challenges include insufficient photo overlap, systematic "doming" induced by photo-spacing regularity, missing metadata, and lack of ground control. Aerial imagery of landscape change in the North Fork Toutle River (NFTR) following the 1980 eruption of Mount St. Helens is a prime dataset to refine methodologies. In particular, (1) 14-μm film scans are available for 1:9600 images at 4-month intervals from 1980 - 1986, (2) the large magnitude of landscape change swamps systematic error and noise, and (3) stable areas (primary deposit features, roads, etc.) provide targets for both ground control and matching to modern lidar. Using AgiSoft PhotoScan, we create digital surface models from the NFTR imagery and examine how common steps in SfM workflows affect results. Tests of scan quality show high-resolution, professional film scans are superior to office scans of paper prints, reducing spurious points related to scan infidelity and image damage. We confirm earlier findings that cropping and rotating images improves point matching and the final surface model produced by the SfM algorithm. We demonstrate how the iterative closest point algorithm, implemented in CloudCompare and using modern lidar as a reference dataset, can serve as an adequate substitute for absolute ground control. Elevation difference maps derived from our surface models of Mount St. Helens show patterns consistent with field observations, including channel avulsion and migration, though systematic errors remain. We suggest that subtracting an empirical function fit to the long-wavelength topographic signal may be one avenue for correcting systematic error in similar datasets.

Unmanned Aerial Survey of Elephants

PubMed Central

Vermeulen, Cédric; Lejeune, Philippe; Lisein, Jonathan; Sawadogo, Prosper; Bouché, Philippe

2013-01-01

The use of a UAS (Unmanned Aircraft System) was tested to survey large mammals in the Nazinga Game Ranch in the south of Burkina Faso. The Gatewing ×100™ equipped with a Ricoh GR III camera was used to test animal reaction as the UAS passed, and visibility on the images. No reaction was recorded as the UAS passed at a height of 100 m. Observations, made on a set of more than 7000 images, revealed that only elephants (Loxodonta africana) were easily visible while medium and small sized mammals were not. The easy observation of elephants allows experts to enumerate them on images acquired at a height of 100 m. We, therefore, implemented an aerial strip sample count along transects used for the annual wildlife foot count. A total of 34 elephants were recorded on 4 transects, each overflown twice. The elephant density was estimated at 2.47 elephants/km2 with a coefficient of variation (CV%) of 36.10%. The main drawback of our UAS was its low autonomy (45 min). Increased endurance of small UAS is required to replace manned aircraft survey of large areas (about 1000 km of transect per day vs 40 km for our UAS). The monitoring strategy should be adapted according to the sampling plan. Also, the UAS is as expensive as a second-hand light aircraft. However the logistic and flight implementation are easier, the running costs are lower and its use is safer. Technological evolution will make civil UAS more efficient, allowing them to compete with light aircraft for aerial wildlife surveys. PMID:23405088

Use of passive UAS imaging to measure biophysical parameters in a southern Rocky Mountain subalpine forest

NASA Astrophysics Data System (ADS)

Caldwell, M. K.; Sloan, J.; Mladinich, C. S.; Wessman, C. A.

2013-12-01

Unmanned Aerial Systems (UAS) can provide detailed, fine spatial resolution imagery for ecological uses not otherwise obtainable through standard methods. The use of UAS imagery for ecology is a rapidly -evolving field, where the study of forest landscape ecology can be augmented using UAS imagery to scale and validate biophysical data from field measurements to spaceborne observations. High resolution imagery provided by UAS (30 cm2 pixels) offers detailed canopy cover and forest structure data in a time efficient and inexpensive manner. Using a GoPro Hero2 (2 mm focal length) camera mounted in the nose cone of a Raven unmanned system, we collected aerial and thermal data monthly during the summer 2013, over two subalpine forests in the Southern Rocky Mountains in Colorado. These forests are dominated by lodgepole pine (Pinus ponderosae) and have experienced insect-driven (primarily mountain pine beetle; MPB, Dendroctonus ponderosae) mortality. Objectives of this study include observations of forest health variables such as canopy water content (CWC) from thermal imagery and leaf area index (LAI), biomass and forest productivity from the Normalized Difference Vegetation Index (NDVI) from UAS imagery. Observations were, validated with ground measurements. Images were processed using a combination of AgiSoft Photoscan professional software and ENVI remote imaging software. We utilized the software Leaf Area Index Calculator (LAIC) developed by Córcoles et al. (2013) for calculating LAI from digital images and modified to conform to leaf area of needle-leaf trees as in Chen and Cihlar (1996) . LAIC uses a K-means cluster analysis to decipher the RGB levels for each pixel and distinguish between green aboveground vegetation and other materials, and project leaf area per unit of ground surface area (i.e. half total needle surface area per unit area). Preliminary LAIC UAS data shows summer average LAI was 3.8 in the most dense forest stands and 2.95 in less dense

2. AERIAL VIEW OF MINUTEMAN SILOS. Low oblique aerial view ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. AERIAL VIEW OF MINUTEMAN SILOS. Low oblique aerial view (original in color) of the two launch silos, covered. - Edwards Air Force Base, Air Force Rocket Propulsion Laboratory, Missile Silo Type, Test Area 1-100, northeast end of Test Area 1-100 Road, Boron, Kern County, CA

Scaling Sap Flow Results Over Wide Areas Using High-Resolution Aerial Multispectral Digital Imaging, Leaf Area Index (LAI) and MODIS Satellite Imagery in Saltcedar Stands on the Lower Colorado River

NASA Astrophysics Data System (ADS)

Murray, R.; Neale, C.; Nagler, P. L.; Glenn, E. P.

2008-12-01

Heat-balance sap flow sensors provide direct estimates of water movement through plant stems and can be used to accurately measure leaf-level transpiration (EL) and stomatal conductance (GS) over time scales ranging from 20-minutes to a month or longer in natural stands of plants. However, their use is limited to relatively small branches on shrubs or trees, as the gauged stem section needs to be uniformly heated by the heating coil to produce valid measurements. This presents a scaling problem in applying the results to whole plants, stands of plants, and larger landscape areas. We used high-resolution aerial multispectral digital imaging with green, red and NIR bands as a bridge between ground measurements of EL and GS, and MODIS satellite imagery of a flood plain on the Lower Colorado River dominated by saltcedar (Tamarix ramosissima). Saltcedar is considered to be a high-water-use plant, and saltcedar removal programs have been proposed to salvage water. Hence, knowledge of actual saltcedar ET rates is needed on western U.S. rivers. Scaling EL and GS to large landscape units requires knowledge of leaf area index (LAI) over large areas. We used a LAI model developed for riparian habitats on Bosque del Apache, New Mexico, to estimate LAI at our study site on the Colorado River. We compared the model estimates to ground measurements of LAI, determined with a Li-Cor LAI-2000 Plant Canopy Analyzer calibrated by leaf harvesting to determine Specific Leaf Area (SLA) (m2 leaf area per g dry weight leaves) of the different species on the floodplain. LAI could be adequately predicted from NDVI from aerial multispectral imagery and could be cross-calibrated with MODIS NDVI and EVI. Hence, we were able to project point measurements of sap flow and LAI over multiple years and over large areas of floodplain using aerial multispectral imagery as a bridge between ground and satellite data. The methods are applicable to riparian corridors throughout the western U.S.

Method of transmission of dynamic multibit digital images from micro-unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Petrov, E. P.; Kharina, N. L.

2018-01-01

In connection with successful usage of nanotechnologies in remote sensing great attention is paid to the systems in micro-unmanned aerial vehicles (MUAVs) capable to provide high spatial resolution of dynamic multibit digital images (MDI). Limited energy resources on board the MUAV do not allow transferring a large amount of video information in the shortest possible time. It keeps back the broad development of MUAV. The search for methods to shorten the transmission time of dynamic MDIs from MUAV over the radio channel leads to the methods of MDI compression without computational operations onboard the MUAV. The known compression codecs of video information can not be applied because of the limited energy resources. In this paper we propose a method for reducing the transmission time of dynamic MDIs without computational operations and distortions onboard the MUAV. To develop the method a mathematical apparatus of the theory of conditional Markov processes with discrete arguments was used. On its basis a mathematical model for the transformation of the MDI represented by binary images (BI) in the MDI, consisting of groups of neighboring BIs (GBI) transmitted by multiphase (MP) signals, is constructed. The algorithm for multidimensional nonlinear filtering of MP signals is synthesized, realizing the statistical redundancy of the MDI to compensate for the noise stability losses caused by the use of MP signals.

Extraction of Dems and Orthoimages from Archive Aerial Imagery to Support Project Planning in Civil Engineering

NASA Astrophysics Data System (ADS)

Cogliati, M.; Tonelli, E.; Battaglia, D.; Scaioni, M.

2017-12-01

Archive aerial photos represent a valuable heritage to provide information about land content and topography in the past years. Today, the availability of low-cost and open-source solutions for photogrammetric processing of close-range and drone images offers the chance to provide outputs such as DEM's and orthoimages in easy way. This paper is aimed at demonstrating somehow and to which level of accuracy digitized archive aerial photos may be used within a such kind of low-cost software (Agisoft Photoscan Professional®) to generate photogrammetric outputs. Different steps of the photogrammetric processing workflow are presented and discussed. The main conclusion is that this procedure may come to provide some final products, which however do not feature the high accuracy and resolution that may be obtained using high-end photogrammetric software packages specifically designed for aerial survey projects. In the last part a case study is presented about the use of four-epoch archive of aerial images to analyze the area where a tunnel has to be excavated.

Aerial Explorers and Robotic Ecosystems

NASA Technical Reports Server (NTRS)

Young, Larry A.; Pisanich, Greg

2004-01-01

A unique bio-inspired approach to autonomous aerial vehicle, a.k.a. aerial explorer technology is discussed. The work is focused on defining and studying aerial explorer mission concepts, both as an individual robotic system and as a member of a small robotic "ecosystem." Members of this robotic ecosystem include the aerial explorer, air-deployed sensors and robotic symbiotes, and other assets such as rovers, landers, and orbiters.

Inertial instrument system for aerial surveying

USGS Publications Warehouse

Brown, R.H.; Chapman, W.H.; Hanna, W.F.; Mongan, C.E.; Hursh, J.W.

1985-01-01

An inertial guidance system for aerial surveying has been developed under contract to the U.S. Geological Survey. This prototype system, known as the aerial profiling of terrain (APT) system, is designed to determine continuously the positions of points along an aircraft flight path, or the underlying terrain profile, to an accuracy of + or - 0.5 ft (15 cm) vertically and + or - 2 ft (61 cm) horizontally. The system 's objective thus is to accomplish, from a fixed-wing aircraft, what would traditionally be accomplished from ground-based topographic surveys combined with aerial photography and photogrammetry. The two-part strategy for measuring the terrain profile entails: (1) use of an inertial navigator for continuous determination of the three-coordinate position of the aircraft, and (2) use of an eye-safe pulsed laser profiler for continuous measurement of the vertical distance from aircraft to land surface, so that the desired terrain profile can then be directly computed. The APT system, installed in a DeHavilland Twin Otter aircraft, is typically flown at a speed of 115 mph (105 knots) at an altitude of 2,000 ft (610 m) above the terrain. Performance-evaluation flights have shown that the vertical and horizontal accuracy specifications are met. (USGS)

14. Aerial view showing bldg grouping with bldg #2 intact ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. Aerial view showing bldg grouping with bldg #2 intact previous to fire (long pitched roof with 7 distinct dormers near image center) - photo by Eastern Topographics, Wolfeboro, N.H., Sept. 1985 - Lawrence Machine Shop, Building No. 2, Union & Canal Streets, Lawrence, Essex County, MA

Verification of aerial photo stand volume tables for southeast Alaska.

Treesearch

Theodore S. Setzer; Bert R. Mead

1988-01-01

Aerial photo volume tables are used in the multilevel sampling system of Alaska Forest Inventory and Analysis. These volume tables are presented with a description of the data base and methods used to construct the tables. Volume estimates compiled from the aerial photo stand volume tables and associated ground-measured values are compared and evaluated.

Semi-automted analysis of high-resolution aerial images to quantify docks in Upper Midwest glacial lakes

USGS Publications Warehouse

Beck, Marcus W.; Vondracek, Bruce C.; Hatch, Lorin K.; Vinje, Jason

2013-01-01

Lake resources can be negatively affected by environmental stressors originating from multiple sources and different spatial scales. Shoreline development, in particular, can negatively affect lake resources through decline in habitat quality, physical disturbance, and impacts on fisheries. The development of remote sensing techniques that efficiently characterize shoreline development in a regional context could greatly improve management approaches for protecting and restoring lake resources. The goal of this study was to develop an approach using high-resolution aerial photographs to quantify and assess docks as indicators of shoreline development. First, we describe a dock analysis workflow that can be used to quantify the spatial extent of docks using aerial images. Our approach incorporates pixel-based classifiers with object-based techniques to effectively analyze high-resolution digital imagery. Second, we apply the analysis workflow to quantify docks for 4261 lakes managed by the Minnesota Department of Natural Resources. Overall accuracy of the analysis results was 98.4% (87.7% based on ) after manual post-processing. The analysis workflow was also 74% more efficient than the time required for manual digitization of docks. These analyses have immediate relevance for resource planning in Minnesota, whereas the dock analysis workflow could be used to quantify shoreline development in other regions with comparable imagery. These data can also be used to better understand the effects of shoreline development on aquatic resources and to evaluate the effects of shoreline development relative to other stressors.

ARM Unmanned Aerial Systems Implementation Plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmid, Beat; Ivey, Mark

Recent advances in Unmanned Aerial Systems (UAS) coupled with changes in the regulatory environment for operations of UAS in the National Airspace increase the potential value of UAS to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility. UAS include unmanned aerial vehicles (UAV) and tethered balloon systems (TBS). The roles UAVs and TBSs could play within the ARM Facility, particularly science questions they could help address, have been discussed in several workshops, reports, and vision documents, including: This document describes the implementation of a robust and vigorous program for use of UAV and TBS formore » the science missions ARM supports.« less

Aerial photo SBVC1962". Photo no. 360. Low oblique aerial view ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Aerial photo -SBVC-1962". Photo no. 360. Low oblique aerial view of the campus, looking southeast. Stamped on the rear: "Ron Wilhite, Sun-Telegram photo, file, 10/22/62/ - San Bernardino Valley College, 701 South Mount Vernon Avenue, San Bernardino, San Bernardino County, CA

Extracting Semantic Building Models from Aerial Stereo Images and Conversion to Citygml

NASA Astrophysics Data System (ADS)

Sengul, A.

2012-07-01

The collection of geographic data is of primary importance for the creation and maintenance of a GIS. Traditionally the acquisition of 3D information has been the task of photogrammetry using aerial stereo images. Digital photogrammetric systems employ sophisticated software to extract digital terrain models or to plot 3D objects. The demand for 3D city models leads to new applications and new standards. City Geography Mark-up Language (CityGML), a concept for modelling and exchange of 3D city and landscape models, defines the classes and relations for the most relevant topographic objects in cities and regional models with respect to their geometrical, topological, semantically and topological properties. It now is increasingly accepted, since it fulfils the prerequisites required e.g. for risk analysis, urban planning, and simulations. There is a need to include existing 3D information derived from photogrammetric processes in CityGML databases. In order to filling the gap, this paper reports on a framework transferring data plotted by Erdas LPS and Stereo Analyst for ArcGIS software to CityGML using Safe Software's Feature Manupulate Engine (FME)

Use of archive aerial photography for monitoring black mangrove populations

USDA-ARS?s Scientific Manuscript database

A study was conducted on the south Texas Gulf Coast to evaluate archive aerial color-infrared (CIR) photography combined with supervised image analysis techniques to quantify changes in black mangrove [Avicennia germinans (L.) L.] populations over a 26-year period. Archive CIR film from two study si...

Determination of Exterior Orientation Parameters Through Direct Geo-Referencing in a Real-Time Aerial Monitoring System

NASA Astrophysics Data System (ADS)

Kim, H.; Lee, J.; Choi, K.; Lee, I.

2012-07-01

Rapid responses for emergency situations such as natural disasters or accidents often require geo-spatial information describing the on-going status of the affected area. Such geo-spatial information can be promptly acquired by a manned or unmanned aerial vehicle based multi-sensor system that can monitor the emergent situations in near real-time from the air using several kinds of sensors. Thus, we are in progress of developing such a real-time aerial monitoring system (RAMS) consisting of both aerial and ground segments. The aerial segment acquires the sensory data about the target areas by a low-altitude helicopter system equipped with sensors such as a digital camera and a GPS/IMU system and transmits them to the ground segment through a RF link in real-time. The ground segment, which is a deployable ground station installed on a truck, receives the sensory data and rapidly processes them to generate ortho-images, DEMs, etc. In order to generate geo-spatial information, in this system, exterior orientation parameters (EOP) of the acquired images are obtained through direct geo-referencing because it is difficult to acquire coordinates of ground points in disaster area. The main process, since the data acquisition stage until the measurement of EOP, is discussed as follows. First, at the time of data acquisition, image acquisition time synchronized by GPS time is recorded as part of image file name. Second, the acquired data are then transmitted to the ground segment in real-time. Third, by processing software for ground segment, positions/attitudes of acquired images are calculated through a linear interpolation using the GPS time of the received position/attitude data and images. Finally, the EOPs of images are obtained from position/attitude data by deriving the relationships between a camera coordinate system and a GPS/IMU coordinate system. In this study, we evaluated the accuracy of the EOP decided by direct geo-referencing in our system. To perform this

Aerial photography flight quality assessment with GPS/INS and DEM data

NASA Astrophysics Data System (ADS)

Zhao, Haitao; Zhang, Bing; Shang, Jiali; Liu, Jiangui; Li, Dong; Chen, Yanyan; Zuo, Zhengli; Chen, Zhengchao

2018-01-01

The flight altitude, ground coverage, photo overlap, and other acquisition specifications of an aerial photography flight mission directly affect the quality and accuracy of the subsequent mapping tasks. To ensure smooth post-flight data processing and fulfill the pre-defined mapping accuracy, flight quality assessments should be carried out in time. This paper presents a novel and rigorous approach for flight quality evaluation of frame cameras with GPS/INS data and DEM, using geometric calculation rather than image analysis as in the conventional methods. This new approach is based mainly on the collinearity equations, in which the accuracy of a set of flight quality indicators is derived through a rigorous error propagation model and validated with scenario data. Theoretical analysis and practical flight test of an aerial photography mission using an UltraCamXp camera showed that the calculated photo overlap is accurate enough for flight quality assessment of 5 cm ground sample distance image, using the SRTMGL3 DEM and the POSAV510 GPS/INS data. An even better overlap accuracy could be achieved for coarser-resolution aerial photography. With this new approach, the flight quality evaluation can be conducted on site right after landing, providing accurate and timely information for decision making.

Design and realization of an AEC&AGC system for the CCD aerial camera

NASA Astrophysics Data System (ADS)

Liu, Hai ying; Feng, Bing; Wang, Peng; Li, Yan; Wei, Hao yun

2015-08-01

An AEC and AGC(Automatic Exposure Control and Automatic Gain Control) system was designed for a CCD aerial camera with fixed aperture and electronic shutter. The normal AEC and AGE algorithm is not suitable to the aerial camera since the camera always takes high-resolution photographs in high-speed moving. The AEC and AGE system adjusts electronic shutter and camera gain automatically according to the target brightness and the moving speed of the aircraft. An automatic Gamma correction is used before the image is output so that the image is better for watching and analyzing by human eyes. The AEC and AGC system could avoid underexposure, overexposure, or image blurring caused by fast moving or environment vibration. A series of tests proved that the system meet the requirements of the camera system with its fast adjusting speed, high adaptability, high reliability in severe complex environment.

Earth analog image digitization of field, aerial, and lab experiment studies for Planetary Data System archiving.

NASA Astrophysics Data System (ADS)

Williams, D. A.; Nelson, D. M.

2017-12-01

A portion of the earth analog image archive at the Ronald Greeley Center for Planetary Studies (RGCPS)-the NASA Regional Planetary Information Facility at Arizona State University-is being digitized and will be added to the Planetary Data System (PDS) for public use. This will be a first addition of terrestrial data to the PDS specifically for comparative planetology studies. Digitization is separated into four tasks. First is the scanning of aerial photographs of volcanic and aeolian structures and flows. The second task is to scan field site images taken from ground and low-altitude aircraft of volcanic structures, lava flows, lava tubes, dunes, and wind streaks. The third image set to be scanned includes photographs of lab experiments from the NASA Planetary Aeolian Laboratory wind tunnels, vortex generator, and of wax models. Finally, rare NASA documents are being scanned and formatted as PDF files. Thousands of images are to be scanned for this project. Archiving of the data will follow the PDS4 standard, where the entire project is classified as a single bundle, with individual subjects (i.e., the Amboy Crater volcanic structure in the Mojave Desert of California) as collections. Within the collections, each image is considered a product, with a unique ID and associated XML document. Documents describing the image data, including the subject and context, will be included with each collection. Once complete, the data will be hosted by a PDS data node and available for public search and download. As one of the first earth analog datasets to be archived by the PDS, this project could prompt the digitizing and making available of historic datasets from other facilities for the scientific community.

Geodetic glacier mass balances at the push of a button: application of Structure from Motion technology on aerial images in mountain regions

NASA Astrophysics Data System (ADS)

Bolch, T.; Mölg, N.

2017-12-01

The application of Structure-from-Motion (SfM) to generate digital terrain models (DTMs) derived out of images from various kinds of sources has strongly increased in recent years. The major reason for this is its easy-to-use handling in comparison to conventional photogrammetry. In glaciology, DTMs are intensely used, among others, to calculate the geodetic mass balances. Few studies investigated the application of SfM to aerial images in mountainous terrain and results look promising. We tested this technique in a demanding environment in the Swiss Alps including very steep slopes, snow and ice covered terrain. SfM (using the commercial software packages of Agisoft Photoscan and Pix4DMapper) and conventional photogrammetry (ERDAS Photogrammetry) were applied on archival aerial images for nine dates between 1946 and 2005 the results were compared regarding bundle adjustment and final DTM quality. The overall precision of the DTMs could be defined with the use of a modern, high-quality reference DTM by Swisstopo. Results suggest a high performance of SfM to produce DTMs of similar quality as conventional photogrammetry. A ground resolution of high quality (little noise and artefacts) can be up to 50% higher, with 3-6 times less user effort. However, the controls on the commercial SfM software packages are limited in comparison to ERDAS Photogrammetry. SfM performs less reliably when few images with little overlap are processed. Overall, the uncertainty of DTMs from the different software are comparable and mostly within the uncertainty range of the reference DTM, making them highly valuable for glaciological purposes. Even though SfM facilitates the largely automated production of high quality DTMs, the user is not exempt from a thorough quality check, at best with reference data where available.

An aerial radiological survey of the Nevada Test Site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hendricks, T J; Riedhauser, S R

1999-12-01

A team from the Remote Sensing Laboratory conducted an aerial radiological survey of the US Department of Energy's Nevada Test Site including three neighboring areas during August and September 1994. The survey team measured the terrestrial gamma radiation at the Nevada Test Site to determine the levels of natural and man-made radiation. This survey included the areas covered by previous surveys conducted from 1962 through 1993. The results of the aerial survey showed a terrestrial background exposure rate that varied from less than 6 microroentgens per hour (mR/h) to 50 mR/h plus a cosmic-ray contribution that varied from 4.5 mR/hmore » at an elevation of 900 meters (3,000 feet) to 8.5 mR/h at 2,400 meters (8,000 feet). In addition to the principal gamma-emitting, naturally occurring isotopes (potassium-40, thallium-208, bismuth-214, and actinium-228), the man-made radioactive isotopes found in this survey were cobalt-60, cesium-137, europium-152, protactinium-234m an indicator of depleted uranium, and americium-241, which are due to human actions in the survey area. Individual, site-wide plots of gross terrestrial exposure rate, man-made exposure rate, and americium-241 activity (approximating the distribution of all transuranic material) are presented. In addition, expanded plots of individual areas exhibiting these man-made contaminations are given. A comparison is made between the data from this survey and previous aerial radiological surveys of the Nevada Test Site. Some previous ground-based measurements are discussed and related to the aerial data. In regions away from man-made activity, the exposure rates inferred from the gamma-ray measurements collected during this survey agreed very well with the exposure rates inferred from previous aerial surveys.« less

REMOTE SENSING OF SEAGRASS WITH AVIRIS AND HIGH ALTITUDE AERIAL PHOTOGRAPHY

EPA Science Inventory

On May 15,2002 AVIRlS (Advanced VisuaJ/lnfrared Imaging Spectrometer) data and high altitude aerial photographs were acquired tor coastal .waters from Cape Lookout to Oregon Inlet, North Carolina. The study encompasses extensive areas of seagrass, federally protected submersed, r...

Applicability of Unmanned Aerial Vehicles in Research on Aeolian Processes

NASA Astrophysics Data System (ADS)

Algimantas, Česnulevičius; Artūras, Bautrėnas; Linas, Bevainis; Donatas, Ovodas; Kęstutis, Papšys

2018-02-01

Surface dynamics and instabilities are characteristic of aeolian formation. The method of surface comparison is regarded as the most appropriate one for evaluation of the intensity of aeolian processes and the amount of transported sand. The data for surface comparison can be collected by topographic survey measurements and using unmanned aerial vehicles. Time cost for relief microform fixation and measurement executing topographic survey are very high. The method of unmanned aircraft aerial photographs fixation also encounters difficulties because there are no stable clear objects and contours that enable to link aerial photographs, to determine the boundaries of captured territory and to ensure the accuracy of surface measurements. Creation of stationary anchor points is irrational due to intense sand accumulation and deflation in different climate seasons. In September 2015 and in April 2016 the combined methodology was applied for evaluation of intensity of aeolian processes in the Curonian Spit. Temporary signs (marks) were installed on the surface, coordinates of the marks were fixed using GPS and then flight of unmanned aircraft was conducted. The fixed coordinates of marks ensure the accuracy of measuring aerial imagery and the ability to calculate the possible corrections. This method was used to track and measure very small (micro-rank) relief forms (5-10 cm height and 10-20 cm length). Using this method morphometric indicators of micro-terraces caused by sand dunes pressure to gytia layer were measured in a non-contact way. An additional advantage of the method is the ability to accurately link the repeated measurements. The comparison of 3D terrain models showed sand deflation and accumulation areas and quantitative changes in the terrain very clearly.

Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method

PubMed Central

Chen, Chao-I; Koseluk, Robert; Buchanan, Chase; Duerner, Andrew; Jeppesen, Brian; Laux, Hunter

2015-01-01

An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC) algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously. PMID:25970254

Comparison of Aerial and Terrestrial Remote Sensing Techniques for Quantifying Forest Canopy Structural Complexity and Estimating Net Primary Productivity

NASA Astrophysics Data System (ADS)

Fahey, R. T.; Tallant, J.; Gough, C. M.; Hardiman, B. S.; Atkins, J.; Scheuermann, C. M.

2016-12-01

Canopy structure can be an important driver of forest ecosystem functioning - affecting factors such as radiative transfer and light use efficiency, and consequently net primary production (NPP). Both above- (aerial) and below-canopy (terrestrial) remote sensing techniques are used to assess canopy structure and each has advantages and disadvantages. Aerial techniques can cover large geographical areas and provide detailed information on canopy surface and canopy height, but are generally unable to quantitatively assess interior canopy structure. Terrestrial methods provide high resolution information on interior canopy structure and can be cost-effectively repeated, but are limited to very small footprints. Although these methods are often utilized to derive similar metrics (e.g., rugosity, LAI) and to address equivalent ecological questions and relationships (e.g., link between LAI and productivity), rarely are inter-comparisons made between techniques. Our objective is to compare methods for deriving canopy structural complexity (CSC) metrics and to assess the capacity of commonly available aerial remote sensing products (and combinations) to match terrestrially-sensed data. We also assess the potential to combine CSC metrics with image-based analysis to predict plot-based NPP measurements in forests of different ages and different levels of complexity. We use combinations of data from drone-based imagery (RGB, NIR, Red Edge), aerial LiDAR (commonly available medium-density leaf-off), terrestrial scanning LiDAR, portable canopy LiDAR, and a permanent plot network - all collected at the University of Michigan Biological Station. Our results will highlight the potential for deriving functionally meaningful CSC metrics from aerial imagery, LiDAR, and combinations of data sources. We will also present results of modeling focused on predicting plot-level NPP from combinations of image-based vegetation indices (e.g., NDVI, EVI) with LiDAR- or image-derived metrics of

Multi-temporal analysis of aerial images for the investigation of spatial-temporal dynamics of shallow erosion - a case study from the Tyrolean Alps

NASA Astrophysics Data System (ADS)

Wiegand, C.; Geitner, C.; Heinrich, K.; Rutzinger, M.

2012-04-01

Small and shallow eroded areas characterize the landscape of many pastures and meadows in the Alps. The extent of such erosion phenomena varies between 2 m2 and 200 m2. These patches tend to be only a few decimetres thick, with a maximum depth of 2 m. The processes involved are shallow landslides, superficial erosion by snow and livestock trampling. Key parameters that influence the emergence of shallow erosion are the geological, topographical and climatic circumstances in an area as well as its soils, vegetation and land use. The negative impact of this phenomenon includes not only the loss of soil but also the reduced attractiveness of the landscape, especially in tourist regions. One approach identifying and mapping geomorphological elements is remote sensing. The analysis of aerial images is a suitable method for identifying the multi-temporal dynamics of shallow eroded areas because of the good spatial and temporal resolution. For this purpose, we used a pixel-based approach to detect these areas semi-automatically in an orthophoto. In a first step, each aerial image was classified using dynamic thresholds derived from the histogram of the orthophoto. In a second step, the identified areas of erosion were filtered and visually in-terpreted. Based on this procedure, eroded areas with a minimum size of 5 m2 were detected in a test site located in the Inner Schmirn Valley (Tyrol, Austria). The altitude of the test site ranges between 1,980 m and 2,370 m, with a mean inclination of 36°, facing E to SE. Geologically, the slope is part of the "Hohe Tauern Window", characterized by "Bündner schists" deficient in lime and regolith. Until the 1960s, the slope was used as a hay meadow. Orthophotos from 2000, 2003, 2007 and 2010 were used for this investigation. Older aerial images were not suitable because of their lower resolution and poor ortho-rectification. However, they are useful for relating the results of the ten-year time-span to a larger temporal context

Regional albedo of Arctic first-year drift ice in advanced stages of melt from the combination of in situ measurements and aerial imagery

NASA Astrophysics Data System (ADS)

Divine, D. V.; Granskog, M. A.; Hudson, S. R.; Pedersen, C. A.; Karlsen, T. I.; Divina, S. A.; Gerland, S.

2014-07-01

The paper presents a case study of the regional (≈ 150 km) broadband albedo of first year Arctic sea ice in advanced stages of melt, estimated from a combination of in situ albedo measurements and aerial imagery. The data were collected during the eight day ICE12 drift experiment carried out by the Norwegian Polar Institute in the Arctic north of Svalbard at 82.3° N from 26 July to 3 August 2012. The study uses in situ albedo measurements representative of the four main surface types: bare ice, dark melt ponds, bright melt ponds and open water. Images acquired by a helicopter borne camera system during ice survey flights covered about 28 km2. A subset of > 8000 images from the area of homogeneous melt with open water fraction of ≈ 0.11 and melt pond coverage of ≈ 0.25 used in the upscaling yielded a regional albedo estimate of 0.40 (0.38; 0.42). The 95% confidence interval on the estimate was derived using the moving block bootstrap approach applied to sequences of classified sea ice images and albedo of the four surface types treated as random variables. Uncertainty in the mean estimates of surface type albedo from in situ measurements contributed some 95% of the variance of the estimated regional albedo, with the remaining variance resulting from the spatial inhomogeneity of sea ice cover. The results of the study are of relevance for the modeling of sea ice processes in climate simulations. It particularly concerns the period of summer melt, when the optical properties of sea ice undergo substantial changes, which existing sea ice models have significant diffuculty accurately reproducing.

Mapping snow depth in complex alpine terrain with close range aerial imagery - estimating the spatial uncertainties of repeat autonomous aerial surveys over an active rock glacier

NASA Astrophysics Data System (ADS)

Goetz, Jason; Marcer, Marco; Bodin, Xavier; Brenning, Alexander

2017-04-01

Snow depth mapping in open areas using close range aerial imagery is just one of the many cases where developments in structure-from-motion and multi-view-stereo (SfM-MVS) 3D reconstruction techniques have been applied for geosciences - and with good reason. Our ability to increase the spatial resolution and frequency of observations may allow us to improve our understanding of how snow depth distribution varies through space and time. However, to ensure accurate snow depth observations from close range sensing we must adequately characterize the uncertainty related to our measurement techniques. In this study, we explore the spatial uncertainties of snow elevation models for estimation of snow depth in a complex alpine terrain from close range aerial imagery. We accomplish this by conducting repeat autonomous aerial surveys over a snow-covered active-rock glacier located in the French Alps. The imagery obtained from each flight of an unmanned aerial vehicle (UAV) is used to create an individual digital elevation model (DEM) of the snow surface. As result, we obtain multiple DEMs of the snow surface for the same site. These DEMs are obtained from processing the imagery with the photogrammetry software Agisoft Photoscan. The elevation models are also georeferenced within Photoscan using the geotagged imagery from an onboard GNSS in combination with ground targets placed around the rock glacier, which have been surveyed with highly accurate RTK-GNSS equipment. The random error associated with multi-temporal DEMs of the snow surface is estimated from the repeat aerial survey data. The multiple flights are designed to follow the same flight path and altitude above the ground to simulate the optimal conditions of repeat survey of the site, and thus try to estimate the maximum precision associated with our snow-elevation measurement technique. The bias of the DEMs is assessed with RTK-GNSS survey observations of the snow surface elevation of the area on and surrounding

Integrating unmanned aerial systems and LSPIV for rapid, cost-effective stream gauging

NASA Astrophysics Data System (ADS)

Lewis, Quinn W.; Lindroth, Evan M.; Rhoads, Bruce L.

2018-05-01

Quantifying flow in rivers is fundamental to assessments of water supply, water quality, ecological conditions, hydrological responses to storm events, and geomorphological processes. Image-based surface velocity measurements have shown promise in extending the range of discharge conditions that can be measured in the field. The use of Unmanned Aerial Systems (UAS) in image-based measurements of surface velocities has the potential to expand applications of this method. Thus far, few investigations have assessed this potential by evaluating the accuracy and repeatability of discharge measurements using surface velocities obtained from UAS. This study uses large-scale particle image velocimetry (LSPIV) derived from videos captured by cameras on a UAS and a fixed tripod to obtain discharge measurements at ten different stream locations in Illinois, USA. Discharge values are compared to reference values measured by an acoustic Doppler current profiler, a propeller meter, and established stream gauges. The results demonstrate the effects of UAS flight height, camera steadiness and leveling accuracy, video sampling frequency, and LSPIV interrogation area size on surface velocities, and show that the mean difference between fixed and UAS cameras is less than 10%. Differences between LSPIV-derived and reference discharge values are generally less than 20%, not systematically low or high, and not related to site parameters like channel width or depth, indicating that results are relatively insensitive to camera setup and image processing parameters typically required of LSPIV. The results also show that standard velocity indices (between 0.85 and 0.9) recommended for converting surface velocities to depth-averaged velocities yield reasonable discharge estimates, but are best calibrated at specific sites. The study recommends a basic methodology for LSPIV discharge measurements using UAS that is rapid, cost-efficient, and does not require major preparatory work at a

Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

Detecting blind building façades from highly overlapping wide angle aerial imagery

NASA Astrophysics Data System (ADS)

Burochin, Jean-Pascal; Vallet, Bruno; Brédif, Mathieu; Mallet, Clément; Brosset, Thomas; Paparoditis, Nicolas

2014-10-01

This paper deals with the identification of blind building façades, i.e. façades which have no openings, in wide angle aerial images with a decimeter pixel size, acquired by nadir looking cameras. This blindness characterization is in general crucial for real estate estimation and has, at least in France, a particular importance on the evaluation of legal permission of constructing on a parcel due to local urban planning schemes. We assume that we have at our disposal an aerial survey with a relatively high stereo overlap along-track and across-track and a 3D city model of LoD 1, that can have been generated with the input images. The 3D model is textured with the aerial imagery by taking into account the 3D occlusions and by selecting for each façade the best available resolution texture seeing the whole façade. We then parse all 3D façades textures by looking for evidence of openings (windows or doors). This evidence is characterized by a comprehensive set of basic radiometric and geometrical features. The blindness prognostic is then elaborated through an (SVM) supervised classification. Despite the relatively low resolution of the images, we reach a classification accuracy of around 85% on decimeter resolution imagery with 60 × 40 % stereo overlap. On the one hand, we show that the results are very sensitive to the texturing resampling process and to vegetation presence on façade textures. On the other hand, the most relevant features for our classification framework are related to texture uniformity and horizontal aspect and to the maximal contrast of the opening detections. We conclude that standard aerial imagery used to build 3D city models can also be exploited to some extent and at no additional cost for facade blindness characterisation.

Antioxidant property of aerial parts and root of Phyllanthus fraternus Webster, an important medicinal plant.

PubMed

Upadhyay, Richa; Chaurasia, Jitendra Kumar; Tiwari, Kavindra Nath; Singh, Karuna

2014-01-01

In present study free radical scavenging potential of aerial parts and root of Phyllanthus fraternus was investigated. Extraction was done in water and ethanol. Total antioxidant capacity was measured by DPPH free radical scavenging method; ethanolic extract of aerial part was most potent in activity with 50% inhibition at 258 μg/mL concentration. Lipid peroxidation (LPO) was measured in terms of thiobarbituric acid-reactive substances (TBARS) by using egg-yolk homogenates as lipid-rich media with EC₅₀ of aerial part (ethanolic) 1522 μg/mL which was found to be most active. Superoxide (SO) radical scavenging activity was measured using riboflavin-light-nitroblue tetrazolium assay. Ethanolic and aqueous extract of both aerial part and root was almost similar in superoxide radical scavenging activity. Reducing power was determined on the basis of Fe³⁺-Fe⁺ transformation in the presence of extract. Total phenolic and flavonoid contents were also measured by spectroscopic method. Results showed that the ethanolic fraction of aerial part is most active towards antioxidant potential and this activity is related to its polyphenolic content and reducing potential. Thus, P. fraternus extract can be used as potent natural antioxidant.

Combined aerial and terrestrial images for complete 3D documentation of Singosari Temple based on Structure from Motion algorithm

NASA Astrophysics Data System (ADS)

Hidayat, Husnul; Cahyono, A. B.

2016-11-01

Singosaritemple is one of cultural heritage building in East Java, Indonesia which was built in 1300s and restorated in 1934-1937. Because of its history and importance, complete documentation of this temple is required. Nowadays with the advent of low cost UAVs combining aerial photography with terrestrial photogrammetry gives more complete data for 3D documentation. This research aims to make complete 3D model of this landmark from aerial and terrestrial photographs with Structure from Motion algorithm. To establish correct scale, position, and orientation, the final 3D model was georeferenced with Ground Control Points in UTM 49S coordinate system. The result shows that all facades, floor, and upper structures can be modeled completely in 3D. In terms of 3D coordinate accuracy, the Root Mean Square Errors (RMSEs) are RMSEx=0,041 m; RMSEy=0,031 m; RMSEz=0,049 m which represent 0.071 m displacement in 3D space. In addition the mean difference of lenght measurements of the object is 0,057 m. With this accuracy, this method can be used to map the site up to 1:237 scale. Although the accuracy level is still in centimeters, the combined aerial and terrestrial photographs with Structure from Motion algorithm can provide complete and visually interesting 3D model.

A digital photogrammetric method for measuring horizontal surficial movements on the slumgullion earthflow, Hinsdale county, Colorado

USGS Publications Warehouse

Powers, P.S.; Chiarle, M.; Savage, W.Z.

1996-01-01

The traditional approach to making aerial photographic measurements uses analog or analytic photogrammetric equipment. We have developed a digital method for making measurements from aerial photographs which uses geographic information system (GIS) software, and primarily DOS-based personal computers. This method, which is based on the concept that a direct visual comparison can be made between images derived from two sets of aerial photographs taken at different times, was applied to the surface of the active portion of the Slumgullion earthflow in Colorado to determine horizontal displacement vectors from the movements of visually identifiable objects, such as trees and large rocks. Using this method, more of the slide surface can be mapped in a shorter period of time than using the standard photogrammetric approach. More than 800 horizontal displacement vectors were determined on the active earthflow surface using images produced by our digital photogrammetric technique and 1985 (1:12,000-scale) and 1990 (1:6,000-scale) aerial photographs. The resulting displacement field shows, with a 2-m measurement error (??? 10%), that the fastest moving portion of the landslide underwent 15-29 m of horizontal displacement between 1985 and 1990. Copyright ?? 1996 Elsevier Science Ltd.

An autonomous unmanned aerial vehicle sensing system for structural health monitoring of bridges

NASA Astrophysics Data System (ADS)

Reagan, Daniel; Sabato, Alessandro; Niezrecki, Christopher; Yu, Tzuyang; Wilson, Richard

2016-04-01

As civil infrastructure (i.e. bridges, railways, and tunnels) continues to age; the frequency and need to perform inspection more quickly on a broader scale increases. Traditional inspection and monitoring techniques (e.g., visual inspection, mechanical sounding, rebound hammer, cover meter, electrical potential measurements, ultrasound, and ground penetrating radar) may produce inconsistent results, require lane closure, are labor intensive and time-consuming. Therefore, new structural health monitoring systems must be developed that are automated, highly accurate, minimally invasive, and cost effective. Three-dimensional (3D) digital image correlation (DIC) systems have the merits of extracting full-field strain, deformation, and geometry profiles. These profiles can then be stitched together to generate a complete integrity map of the area of interest. Concurrently, unmanned aerial vehicles (UAVs) have emerged as valuable resources for positioning sensing equipment where it is either difficult to measure or poses a risk to human safety. UAVs have the capability to expedite the optical-based measurement process, offer increased accessibility, and reduce interference with local traffic. Within this work, an autonomous unmanned aerial vehicle in conjunction with 3D DIC was developed for monitoring bridges. The capabilities of the proposed system are demonstrated in both laboratory measurements and data collected from bridges currently in service. Potential measurement influences from platform instability, rotor vibration and positioning inaccuracy are also studied in a controlled environment. The results of these experiments show that the combination of autonomous flight with 3D DIC and other non-contact measurement systems provides a valuable and effective civil inspection platform.

Enabling high-quality observations of surface imperviousness for water runoff modelling from unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Tokarczyk, Piotr; Leitao, Joao Paulo; Rieckermann, Jörg; Schindler, Konrad; Blumensaat, Frank

2015-04-01

Modelling rainfall-runoff in urban areas is increasingly applied to support flood risk assessment particularly against the background of a changing climate and an increasing urbanization. These models typically rely on high-quality data for rainfall and surface characteristics of the area. While recent research in urban drainage has been focusing on providing spatially detailed rainfall data, the technological advances in remote sensing that ease the acquisition of detailed land-use information are less prominently discussed within the community. The relevance of such methods increase as in many parts of the globe, accurate land-use information is generally lacking, because detailed image data is unavailable. Modern unmanned air vehicles (UAVs) allow acquiring high-resolution images on a local level at comparably lower cost, performing on-demand repetitive measurements, and obtaining a degree of detail tailored for the purpose of the study. In this study, we investigate for the first time the possibility to derive high-resolution imperviousness maps for urban areas from UAV imagery and to use this information as input for urban drainage models. To do so, an automatic processing pipeline with a modern classification method is tested and applied in a state-of-the-art urban drainage modelling exercise. In a real-life case study in the area of Lucerne, Switzerland, we compare imperviousness maps generated from a consumer micro-UAV and standard large-format aerial images acquired by the Swiss national mapping agency (swisstopo). After assessing their correctness, we perform an end-to-end comparison, in which they are used as an input for an urban drainage model. Then, we evaluate the influence which different image data sources and their processing methods have on hydrological and hydraulic model performance. We analyze the surface runoff of the 307 individual sub-catchments regarding relevant attributes, such as peak runoff and volume. Finally, we evaluate the model

ARM Aerial Facility ArcticShark Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Schmid, B.; Hubbell, M.; Mei, F.; Carroll, P.; Mendoza, A.; Ireland, C.; Lewko, K.

2017-12-01

The TigerShark Block 3 XP-AR "ArcticShark" Unmanned Aerial System (UAS), developed and manufactured by Navmar Applied Sciences Corporation (NASC), is a single-prop, 60 hp rotary-engine platform with a wingspan of 6.5 m and Maximum Gross Takeoff Weight of 295 Kg. The ArcticShark is owned by the U.S. Department of Energy (DOE) and has been operated by Pacific Northwest National Laboratory (PNNL) since March 2017. The UAS will serve as an airborne atmospheric research observatory for DOE ARM, and, once fully operational, can be requested through ARM's annual call for proposals. The Arctic Shark is anticipated to measure a wide range of radiative, aerosol, and cloud properties using a variable instrument payload weighing up to 46 Kg. SATCOM-equipped, it is capable of taking measurements up to altitudes of 5.5 Km over ranges of up to 500 Km. The ArcticShark operates at airspeeds of 30 to 40 m/s, making it capable of slow sampling. With a full fuel load, its endurance exceeds 8 hours. The aircraft and its Mobile Operations Center (MOC) have been hardened specifically for operations in colder temperatures.ArcticShark's design facilitates rapid integration of various types of payloads. 2500 W of its 4000 W electrical systems is dedicated to payload servicing. It has an interior payload volume of almost 85 L and four wing-mounted pylons capable of carrying external probes. Its payload bay volume, electrical power, payload capacity, and flight characteristics enable the ArcticShark to accommodate multiple combinations of payloads in numerous configurations. Many instruments will be provided by the ARM Aerial Facility (AAF), but other organizations may eventually propose instrumentation for specific campaigns. AAF-provided measurement capabilities will include the following atmospheric state and thermodynamics: temperature, pressure, winds; gases: H2O and CO2; up- and down-welling broadband infrared and visible radiation; surface temperature; aerosol number concentration

27. AERIAL VIEW OF ARVFS FIELD TEST SITE AS IT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

27. AERIAL VIEW OF ARVFS FIELD TEST SITE AS IT LOOKED IN 1983. OBLIQUE VIEW FACING EAST. BUNKER IS IN FOREGROUND, PROTECTIVE SHED FOR WFRP AT TOP OF IMAGE. INEL PHOTO NUMBER 83-574-12-1, TAKEN IN 1983. PHOTOGRAPHER: ROMERO. - Idaho National Engineering Laboratory, Advanced Reentry Vehicle Fusing System, Scoville, Butte County, ID

Emission Measurements of Open Area Combustion Sources with an Unmanned Aerial System

EPA Science Inventory

miniaturized sensor/sampler system (“Kolibri”) on a six-motor, unmanned aerial system (UAS) was used to quantify emissions from open burning of obsolete military propellants. The UAS afforded the ability to sample plume emissions at altitude and from a safe distance ...

Efficient content-based low-altitude images correlated network and strips reconstruction

NASA Astrophysics Data System (ADS)

He, Haiqing; You, Qi; Chen, Xiaoyong

2017-01-01

The manual intervention method is widely used to reconstruct strips for further aerial triangulation in low-altitude photogrammetry. Clearly the method for fully automatic photogrammetric data processing is not an expected way. In this paper, we explore a content-based approach without manual intervention or external information for strips reconstruction. Feature descriptors in the local spatial patterns are extracted by SIFT to construct vocabulary tree, in which these features are encoded in terms of TF-IDF numerical statistical algorithm to generate new representation for each low-altitude image. Then images correlated network is reconstructed by similarity measure, image matching and geometric graph theory. Finally, strips are reconstructed automatically by tracing straight lines and growing adjacent images gradually. Experimental results show that the proposed approach is highly effective in automatically rearranging strips of lowaltitude images and can provide rough relative orientation for further aerial triangulation.

7 CFR 1755.506 - Aerial wire services

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Aerial wire services 1755.506 Section 1755.506... § 1755.506 Aerial wire services (a) Aerial services of one through six pairs shall consist of Service...), Specifications and Drawings for Service Installations at Customer Access Locations. The wire used for aerial...

Use of Vertical Aerial Images for Semi-Oblique Mapping

NASA Astrophysics Data System (ADS)

Poli, D.; Moe, K.; Legat, K.; Toschi, I.; Lago, F.; Remondino, F.

2017-05-01

The paper proposes a methodology for the use of the oblique sections of images from large-format photogrammetric cameras, by exploiting the effect of the central perspective geometry in the lateral parts of the nadir images ("semi-oblique" images). The point of origin of the investigation was the execution of a photogrammetric flight over Norcia (Italy), which was seriously damaged after the earthquake of 30/10/2016. Contrary to the original plan of oblique acquisitions, the flight was executed on 15/11/2017 using an UltraCam Eagle camera with focal length 80 mm, and combining two flight plans, rotated by 90º ("crisscross" flight). The images (GSD 5 cm) were used to extract a 2.5D DSM cloud, sampled to a XY-grid size of 2 GSD, a 3D point clouds with a mean spatial resolution of 1 GSD and a 3D mesh model at a resolution of 10 cm of the historic centre of Norcia for a quantitative assessment of the damages. From the acquired nadir images the "semi-oblique" images (forward, backward, left and right views) could be extracted and processed in a modified version of GEOBLY software for measurements and restitution purposes. The potential of such semi-oblique image acquisitions from nadir-view cameras is hereafter shown and commented.

Investigating an Aerial Image First

ERIC Educational Resources Information Center

Wyrembeck, Edward P.; Elmer, Jeffrey S.

2006-01-01

Most introductory optics lab activities begin with students locating the real image formed by a converging lens. The method is simple and straightforward--students move a screen back and forth until the real image is in sharp focus on the screen. Students then draw a simple ray diagram to explain the observation using only two or three special…

Feasibility of determining flat roof heat losses using aerial thermography

NASA Technical Reports Server (NTRS)

Bowman, R. L.; Jack, J. R.

1979-01-01

The utility of aerial thermography for determining rooftop heat losses was investigated experimentally using several completely instrumented test roofs with known thermal resistances. Actual rooftop heat losses were obtained both from in-situ instrumentation and aerial thermography obtained from overflights at an altitude of 305 m. In general, the remotely determined roof surface temperatures agreed very well with those obtained from ground measurements. The roof heat losses calculated using the remotely determined roof temperature agreed to within 17% of those calculated from 1/R delta T using ground measurements. However, this agreement may be fortuitous since the convective component of the heat loss is sensitive to small changes in roof temperature and to the average heat transfer coefficient used, whereas the radiative component is less sensitive. This, at this time, it is felt that an acceptable quantitative determination of roof heat losses using aerial thermography is only feasible when the convective term is accurately known or minimized. The sensitivity of the heat loss determination to environmental conditions was also evaluated. The analysis showed that the most reliable quantitative heat loss determinations can probably be obtained from aerial thermography taken under conditions of total cloud cover with low wind speeds and at low ambient temperatures.

Estimating Mixed Broadleaves Forest Stand Volume Using Dsm Extracted from Digital Aerial Images

NASA Astrophysics Data System (ADS)

Sohrabi, H.

2012-07-01

In mixed old growth broadleaves of Hyrcanian forests, it is difficult to estimate stand volume at plot level by remotely sensed data while LiDar data is absent. In this paper, a new approach has been proposed and tested for estimating stand forest volume. The approach is based on this idea that forest volume can be estimated by variation of trees height at plots. In the other word, the more the height variation in plot, the more the stand volume would be expected. For testing this idea, 120 circular 0.1 ha sample plots with systematic random design has been collected in Tonekaon forest located in Hyrcanian zone. Digital surface model (DSM) measure the height values of the first surface on the ground including terrain features, trees, building etc, which provides a topographic model of the earth's surface. The DSMs have been extracted automatically from aerial UltraCamD images so that ground pixel size for extracted DSM varied from 1 to 10 m size by 1m span. DSMs were checked manually for probable errors. Corresponded to ground samples, standard deviation and range of DSM pixels have been calculated. For modeling, non-linear regression method was used. The results showed that standard deviation of plot pixels with 5 m resolution was the most appropriate data for modeling. Relative bias and RMSE of estimation was 5.8 and 49.8 percent, respectively. Comparing to other approaches for estimating stand volume based on passive remote sensing data in mixed broadleaves forests, these results are more encouraging. One big problem in this method occurs when trees canopy cover is totally closed. In this situation, the standard deviation of height is low while stand volume is high. In future studies, applying forest stratification could be studied.

Anaglyph of Perspective View with Aerial Photo Overlay Pasadena, California

NASA Technical Reports Server (NTRS)

2000-01-01

This anaglyph is a perspective view that shows the western part of the city of Pasadena, California, looking north toward the San Gabriel Mountains. Red-blue glasses are required to see the 3-D effect. Portions of the cities of Altadena and La Canada-Flintridge are also shown. The image was created from two datasets: the Shuttle Radar Topography Mission (SRTM) supplied the elevation data and U. S. Geological Survey digital aerial photography provided the image detail. The Jet Propulsion Laboratory is the cluster of large buildings left of center, at the base of the mountains. This image shows the power of combining data from different sources to create planning tools to study problems that affect large urban areas. In addition to the well-known earthquake hazards, Southern California is affected by a natural cycle of fire and mudflows. Wildfires can strip the mountains of vegetation, increasing the hazards from flooding and mudflows. Data shown in this image can be used to predict both how wildfires spread over the terrain and how mudflows are channeled down the canyons.

This anaglyph was generated using topographic data from the Shuttle Radar Topography Mission to create two differing perspectives of a single image, one perspective for each eye. Each point in the image is shifted slightly, depending on its elevation. When viewed through special glasses, the result is a view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.

The Shuttle Radar Topography Mission (SRTM), launched on February 11, 2000, uses the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. The mission is designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, an additional C

Correction of Line Interleaving Displacement in Frame Captured Aerial Video Imagery

Treesearch

B. Cooke; A. Saucier

1995-01-01

Scientists with the USDA Forest Service are currently assessing the usefulness of aerial video imagery for various purposes including midcycle inventory updates. The potential of video image data for these purposes may be compromised by scan line interleaving displacement problems. Interleaving displacement problems cause features in video raster datasets to have...

User guide for the USGS aerial camera Report of Calibration.

USGS Publications Warehouse

Tayman, W.P.

1984-01-01

Calibration and testing of aerial mapping cameras includes the measurement of optical constants and the check for proper functioning of a number of complicated mechanical and electrical parts. For this purpose the US Geological Survey performs an operational type photographic calibration. This paper is not strictly a scientific paper but rather a 'user guide' to the USGS Report of Calibration of an aerial mapping camera for compliance with both Federal and State mapping specifications. -Author

Exploring the Potential of Aerial Photogrammetry for 3d Modelling of High-Alpine Environments

NASA Astrophysics Data System (ADS)

Legat, K.; Moe, K.; Poli, D.; Bollmannb, E.

2016-03-01

High-alpine areas are subject to rapid topographic changes, mainly caused by natural processes like glacial retreat and other geomorphological processes, and also due to anthropogenic interventions like construction of slopes and infrastructure in skiing resorts. Consequently, the demand for highly accurate digital terrain models (DTMs) in alpine environments has arisen. Public administrations often have dedicated resources for the regular monitoring of glaciers and natural hazard processes. In case of glaciers, traditional monitoring encompasses in-situ measurements of area and length and the estimation of volume and mass changes. Next to field measurements, data for such monitoring programs can be derived from DTMs and digital ortho photos (DOPs). Skiing resorts, on the other hand, require DTMs as input for planning and - more recently - for RTK-GNSS supported ski-slope grooming. Although different in scope, the demand of both user groups is similar: high-quality and up-to-date terrain data for extended areas often characterised by difficult accessibility and large elevation ranges. Over the last two decades, airborne laser scanning (ALS) has replaced photogrammetric approaches as state-of-the-art technology for the acquisition of high-resolution DTMs also in alpine environments. Reasons include the higher productivity compared to (manual) stereo-photogrammetric measurements, canopy-penetration capability, and limitations of photo measurements on sparsely textured surfaces like snow or ice. Nevertheless, the last few years have shown strong technological advances in the field of aerial camera technology, image processing and photogrammetric software which led to new possibilities for image-based DTM generation even in alpine terrain. At Vermessung AVT, an Austrian-based surveying company, and its subsidiary Terra Messflug, very promising results have been achieved for various projects in high-alpine environments, using images acquired by large-format digital

Open Skies aerial photography of selected areas in Central America affected by Hurricane Mitch

USGS Publications Warehouse

Molnia, Bruce; Hallam, Cheryl A.

1999-01-01

Between October 27 and November 1, 1998, Central America was devastated by Hurricane Mitch. Following a humanitarian relief effort, one of the first informational needs was complete aerial photographic coverage of the storm ravaged areas so that the governments of the affected countries, the U.S. agencies planning to provide assistance, and the international relief community could come to the aid of the residents of the devastated area. Between December 4 and 19, 1998 an Open Skies aircraft conducted five successful missions and obtained more than 5,000 high-resolution aerial photographs and more than 15,000 video images. The aerial data are being used by the Reconstruction Task Force and many others who are working to begin rebuilding and to help reduce the risk of future destruction.

The Need of Nested Grids for Aerial and Satellite Images and Digital Elevation Models

NASA Astrophysics Data System (ADS)

Villa, G.; Mas, S.; Fernández-Villarino, X.; Martínez-Luceño, J.; Ojeda, J. C.; Pérez-Martín, B.; Tejeiro, J. A.; García-González, C.; López-Romero, E.; Soteres, C.

2016-06-01

Usual workflows for production, archiving, dissemination and use of Earth observation images (both aerial and from remote sensing satellites) pose big interoperability problems, as for example: non-alignment of pixels at the different levels of the pyramids that makes it impossible to overlay, compare and mosaic different orthoimages, without resampling them and the need to apply multiple resamplings and compression-decompression cycles. These problems cause great inefficiencies in production, dissemination through web services and processing in "Big Data" environments. Most of them can be avoided, or at least greatly reduced, with the use of a common "nested grid" for mutiresolution production, archiving, dissemination and exploitation of orthoimagery, digital elevation models and other raster data. "Nested grids" are space allocation schemas that organize image footprints, pixel sizes and pixel positions at all pyramid levels, in order to achieve coherent and consistent multiresolution coverage of a whole working area. A "nested grid" must be complemented by an appropriate "tiling schema", ideally based on the "quad-tree" concept. In the last years a "de facto standard" grid and Tiling Schema has emerged and has been adopted by virtually all major geospatial data providers. It has also been adopted by OGC in its "WMTS Simple Profile" standard. In this paper we explain how the adequate use of this tiling schema as common nested grid for orthoimagery, DEMs and other types of raster data constitutes the most practical solution to most of the interoperability problems of these types of data.

ISSUES IN DIGITAL IMAGE PROCESSING OF AERIAL PHOTOGRAPHY FOR MAPPING SUBMERSED AQUATIC VEGETATION

EPA Science Inventory

The paper discusses the numerous issues that needed to be addressed when developing a methodology for mapping Submersed Aquatic Vegetation (SAV) from digital aerial photography. Specifically, we discuss 1) choice of film; 2) consideration of tide and weather constraints; 3) in-s...

A workflow for extracting plot-level biophysical indicators from aerially acquired multispectral imagery

USDA-ARS?s Scientific Manuscript database

Advances in technologies associated with unmanned aerial vehicles (UAVs) has allowed for researchers, farmers and agribusinesses to incorporate UAVs coupled with various imaging systems into data collection activities and aid expert systems for making decisions. Multispectral imageries allow for a q...

Cooperative Surveillance and Pursuit Using Unmanned Aerial Vehicles and Unattended Ground Sensors

PubMed Central

Las Fargeas, Jonathan; Kabamba, Pierre; Girard, Anouck

2015-01-01

This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles' paths nominally. The algorithm uses detections from the sensors to predict intruders' locations and selects the vehicles' paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm's completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios. PMID:25591168

A short cut for scaling aerial photos

Treesearch

Earl J. Rogers

1948-01-01

Aerial photos are a handy tool for the forester. They furnish forest data quickly. But when the photo is used as a map, care is necessary - especially in rough country. In flat country photo scales are quite uniform and distances can be measured accurately. But in rough country photo scale varies with changes in elevation, and it is more difficult to measure distances...

Detection of Tree Crowns Based on Reclassification Using Aerial Images and LIDAR Data

NASA Astrophysics Data System (ADS)

Talebi, S.; Zarea, A.; Sadeghian, S.; Arefi, H.

2013-09-01

Tree detection using aerial sensors in early decades was focused by many researchers in different fields including Remote Sensing and Photogrammetry. This paper is intended to detect trees in complex city areas using aerial imagery and laser scanning data. Our methodology is a hierarchal unsupervised method consists of some primitive operations. This method could be divided into three sections, in which, first section uses aerial imagery and both second and third sections use laser scanners data. In the first section a vegetation cover mask is created in both sunny and shadowed areas. In the second section Rate of Slope Change (RSC) is used to eliminate grasses. In the third section a Digital Terrain Model (DTM) is obtained from LiDAR data. By using DTM and Digital Surface Model (DSM) we would get to Normalized Digital Surface Model (nDSM). Then objects which are lower than a specific height are eliminated. Now there are three result layers from three sections. At the end multiplication operation is used to get final result layer. This layer will be smoothed by morphological operations. The result layer is sent to WG III/4 to evaluate. The evaluation result shows that our method has a good rank in comparing to other participants' methods in ISPRS WG III/4, when assessed in terms of 5 indices including area base completeness, area base correctness, object base completeness, object base correctness and boundary RMS. With regarding of being unsupervised and automatic, this method is improvable and could be integrate with other methods to get best results.

Very Large Scale Aerial (VLSA) imagery for assessing postfire bitterbrush recovery

Treesearch

Corey A. Moffet; J. Bret Taylor; D. Terrance Booth

2008-01-01

Very large scale aerial (VLSA) imagery is an efficient tool for monitoring bare ground and cover on extensive rangelands. This study was conducted to determine whether VLSA images could be used to detect differences in antelope bitterbrush (Purshia tridentata Pursh DC) cover and density among similar ecological sites with varying postfire recovery...

Aerial surveillance vehicles augment security at shipping ports

NASA Astrophysics Data System (ADS)

Huck, Robert C.; Al Akkoumi, Muhammad K.; Cheng, Samuel; Sluss, James J., Jr.; Landers, Thomas L.

2008-10-01

With the ever present threat to commerce, both politically and economically, technological innovations provide a means to secure the transportation infrastructure that will allow efficient and uninterrupted freight-flow operations for trade. Currently, freight coming into United States ports is "spot checked" upon arrival and stored in a container yard while awaiting the next mode of transportation. For the most part, only fences and security patrols protect these container storage yards. To augment these measures, the authors propose the use of aerial surveillance vehicles equipped with video cameras and wireless video downlinks to provide a birds-eye view of port facilities to security control centers and security patrols on the ground. The initial investigation described in this paper demonstrates the use of unmanned aerial surveillance vehicles as a viable method for providing video surveillance of container storage yards. This research provides the foundation for a follow-on project to use autonomous aerial surveillance vehicles coordinated with autonomous ground surveillance vehicles for enhanced port security applications.

Airborne remote sensing assessment of the damage to cotton caused by spray drift from aerially applied glyphosate through spray deposition measurements

USDA-ARS?s Scientific Manuscript database

Off-target drift of aerially applied glyphosate can cause plant injury, which is of great concern to farmers and aerial applicators. To determine the extent of crop injury due to near-field drift, an experiment was conducted with a single aerial application of glyphosate. For identification of the d...

Pasadena, California Perspective View with Aerial Photo and Landsat Overlay

NASA Technical Reports Server (NTRS)

2000-01-01

This perspective view shows the western part of the city of Pasadena, California, looking north towards the San Gabriel Mountains. Portions of the cities of Altadena and La Canada-Flintridge are also shown. The image was created from three datasets: the Shuttle Radar Topography Mission (SRTM) supplied the elevation data; Landsat data from November 11, 1986 provided the land surface color (not the sky) and U. S. Geological Survey digital aerial photography provides the image detail. The Rose Bowl, surrounded by a golf course, is the circular feature at the bottom center of the image. The Jet Propulsion Laboratory, is the cluster of large buildings north of the Rose Bowl at the base of the mountains. A large landfill, Scholl Canyon, is the smooth area in the lower left corner of the scene.

This image shows the power of combining data from different sources to create planning tools to study problems that affect large urban areas. In addition to the well-known earthquake hazards, Southern California is affected by a natural cycle of fire and mudflows. Wildfires strip the mountains of vegetation, increasing the hazards from flooding and mudflows for several years afterwards. Data such as shown on this image can be used to predict both how wildfires will spread over the terrain and also how mudflows will be channeled down the canyons.

For a full-resolution, annotated version of this image, please select Figure 1, below: [figure removed for brevity, see original site]

The Shuttle Radar Topography Mission (SRTM), launched on February 11,2000, uses the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. The mission is designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, an additional C-band imaging antenna and improved tracking and navigation

Measuring the Erosion of River Channel Widths Impacted by Watershed Urbanization Using Historic Aerial Photographs and Modern Surveys

NASA Astrophysics Data System (ADS)

Galster, J. C.; Pazzaglia, F. J.; Germanoski, D.

2007-12-01

Land use in a watershed exerts a strong influence on trunk channel form and process. Land use changes act over human time scales which is short enough to measure their effects directly using historic aerial photographs. We show that high-resolution topographic surveys comparing channel form for paired watersheds in the Lehigh Valley, PA are indistinguishable, but have channel widths that have changed dramatically in the past five decades. The two watersheds, Little Lehigh Creek and Sacony Creek, are similar in all respects except they have different amount of urban land use. Aerial photographs of the urbanized Little Lehigh Creek show that a majority of the measured widths (67 of 85) were statistically wider in 1999 than in 1947. In contrast, the measured widths from the agricultural Sacony Creek are more evenly distributed among those that widened (18), narrowed (28), and those that were statistically unchanged (6) from 1946 to 1999. From 1946 to 1999 the only section of Sacony creek that widened was that reach downstream of the only sizable urban area in the watershed. The current land use in Sacony Creek watershed resembles that of 1946, while the Little Lehigh Creek watershed has more than tripled its urban area. These data suggest that the increase in urban areas that subsequently increases peak discharges is the mechanism behind the widening that occurred in the Little Lehigh Creek. These wider channels can affect water quality, aquatic habitat, suspended sediment loads, and river aesthetics.

Low aerial imagery - an assessment of georeferencing errors and the potential for use in environmental inventory

NASA Astrophysics Data System (ADS)

Smaczyński, Maciej; Medyńska-Gulij, Beata

2017-06-01

Unmanned aerial vehicles are increasingly being used in close range photogrammetry. Real-time observation of the Earth's surface and the photogrammetric images obtained are used as material for surveying and environmental inventory. The following study was conducted on a small area (approximately 1 ha). In such cases, the classical method of topographic mapping is not accurate enough. The geodetic method of topographic surveying, on the other hand, is an overly precise measurement technique for the purpose of inventorying the natural environment components. The author of the following study has proposed using the unmanned aerial vehicle technology and tying in the obtained images to the control point network established with the aid of GNSS technology. Georeferencing the acquired images and using them to create a photogrammetric model of the studied area enabled the researcher to perform calculations, which yielded a total root mean square error below 9 cm. The performed comparison of the real lengths of the vectors connecting the control points and their lengths calculated on the basis of the photogrammetric model made it possible to fully confirm the RMSE calculated and prove the usefulness of the UAV technology in observing terrain components for the purpose of environmental inventory. Such environmental components include, among others, elements of road infrastructure, green areas, but also changes in the location of moving pedestrians and vehicles, as well as other changes in the natural environment that are not registered on classical base maps or topographic maps.

The DOE ARM Aerial Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmid, Beat; Tomlinson, Jason M.; Hubbe, John M.

2014-05-01

The Department of Energy Atmospheric Radiation Measurement (ARM) Program is a climate research user facility operating stationary ground sites that provide long-term measurements of climate relevant properties, mobile ground- and ship-based facilities to conduct shorter field campaigns (6-12 months), and the ARM Aerial Facility (AAF). The airborne observations acquired by the AAF enhance the surface-based ARM measurements by providing high-resolution in-situ measurements for process understanding, retrieval-algorithm development, and model evaluation that are not possible using ground- or satellite-based techniques. Several ARM aerial efforts were consolidated into the AAF in 2006. With the exception of a small aircraft used for routinemore » measurements of aerosols and carbon cycle gases, AAF at the time had no dedicated aircraft and only a small number of instruments at its disposal. In this "virtual hangar" mode, AAF successfully carried out several missions contracting with organizations and investigators who provided their research aircraft and instrumentation. In 2009, AAF started managing operations of the Battelle-owned Gulfstream I (G-1) large twin-turboprop research aircraft. Furthermore, the American Recovery and Reinvestment Act of 2009 provided funding for the procurement of over twenty new instruments to be used aboard the G-1 and other AAF virtual-hangar aircraft. AAF now executes missions in the virtual- and real-hangar mode producing freely available datasets for studying aerosol, cloud, and radiative processes in the atmosphere. AAF is also engaged in the maturation and testing of newly developed airborne sensors to help foster the next generation of airborne instruments.« less

The Art of Aerial Warfare

DTIC Science & Technology

2005-03-01

14 3 THE POLITICAL DIMENSIONS OF AERIAL WARFARE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 How Political Effects in...Aerial Warfare . . . . . . Outweigh Military Effects . . . . . . . . . . . . . . . 19 Political Targets Versus Military Targets . . . . . 22...34 4 MILITARY AND POLITICAL EFFECTS OF STRATEGIC ATTACK . . . . . . . . . . . . . . . . . . 35 The Premise of

Estimating snow depth in real time using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Niedzielski, Tomasz; Mizinski, Bartlomiej; Witek, Matylda; Spallek, Waldemar; Szymanowski, Mariusz

2016-04-01

In frame of the project no. LIDER/012/223/L-5/13/NCBR/2014, financed by the National Centre for Research and Development of Poland, we elaborated a fully automated approach for estimating snow depth in real time in the field. The procedure uses oblique aerial photographs taken by the unmanned aerial vehicle (UAV). The geotagged images of snow-covered terrain are processed by the Structure-from-Motion (SfM) method which is used to produce a non-georeferenced dense point cloud. The workflow includes the enhanced RunSFM procedure (keypoint detection using the scale-invariant feature transform known as SIFT, image matching, bundling using the Bundler, executing the multi-view stereo PMVS and CMVS2 software) which is preceded by multicore image resizing. The dense point cloud is subsequently automatically georeferenced using the GRASS software, and the ground control points are borrowed from positions of image centres acquired from the UAV-mounted GPS receiver. Finally, the digital surface model (DSM) is produced which - to improve the accuracy of georeferencing - is shifted using a vector obtained through precise geodetic GPS observation of a single ground control point (GCP) placed on the Laboratory for Unmanned Observations of Earth (mobile lab established at the University of Wroclaw, Poland). The DSM includes snow cover and its difference with the corresponding snow-free DSM or digital terrain model (DTM), following the concept of the digital elevation model of differences (DOD), produces a map of snow depth. Since the final result depends on the snow-free model, two experiments are carried out. Firstly, we show the performance of the entire procedure when the snow-free model reveals a very high resolution (3 cm/px) and is produced using the UAV-taken photographs and the precise GCPs measured by the geodetic GPS receiver. Secondly, we perform a similar exercise but the 1-metre resolution light detection and ranging (LIDAR) DSM or DTM serves as the snow-free model

47 CFR 32.6431 - Aerial wire expense.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Aerial wire expense. 32.6431 Section 32.6431... FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6431 Aerial wire expense. This account shall include expenses associated with aerial wire. ...

47 CFR 32.6431 - Aerial wire expense.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Aerial wire expense. 32.6431 Section 32.6431... FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6431 Aerial wire expense. This account shall include expenses associated with aerial wire. ...

Aerial thermography for energy conservation

NASA Technical Reports Server (NTRS)

Jack, J. R.

1978-01-01

Thermal infrared scanning from an aircraft is a convenient and commercially available means for determining relative rates of energy loss from building roofs. The need to conserve energy as fuel costs makes the mass survey capability of aerial thermography an attractive adjunct to community energy awareness programs. Background information on principles of aerial thermography is presented. Thermal infrared scanning systems, flight and environmental requirements for data acquisition, preparation of thermographs for display, major users and suppliers of thermography, and suggested specifications for obtaining aerial scanning services were reviewed.

An Improved Aerial Target Localization Method with a Single Vector Sensor

PubMed Central

Zhao, Anbang; Bi, Xuejie; Hui, Juan; Zeng, Caigao; Ma, Lin

2017-01-01

This paper focuses on the problems encountered in the actual data processing with the use of the existing aerial target localization methods, analyzes the causes of the problems, and proposes an improved algorithm. Through the processing of the sea experiment data, it is found that the existing algorithms have higher requirements for the accuracy of the angle estimation. The improved algorithm reduces the requirements of the angle estimation accuracy and obtains the robust estimation results. The closest distance matching estimation algorithm and the horizontal distance estimation compensation algorithm are proposed. The smoothing effect of the data after being post-processed by using the forward and backward two-direction double-filtering method has been improved, thus the initial stage data can be filtered, so that the filtering results retain more useful information. In this paper, the aerial target height measurement methods are studied, the estimation results of the aerial target are given, so as to realize the three-dimensional localization of the aerial target and increase the understanding of the underwater platform to the aerial target, so that the underwater platform has better mobility and concealment. PMID:29135956

Application of high resolution images from unmanned aerial vehicles for hydrology and rangeland science

NASA Astrophysics Data System (ADS)

Rango, A.; Vivoni, E. R.; Anderson, C. A.; Perini, N. A.; Saripalli, S.; Laliberte, A.

2012-12-01

A common problem in many natural resource disciplines is the lack of high-enough spatial resolution images that can be used for monitoring and modeling purposes. Advances have been made in the utilization of Unmanned Aerial Vehicles (UAVs) in hydrology and rangeland science. By utilizing low flight altitudes and velocities, UAVs are able to produce high resolution (5 cm) images as well as stereo coverage (with 75% forward overlap and 40% sidelap) to extract digital elevation models (DEM). Another advantage of flying at low altitude is that the potential problems of atmospheric haze obscuration are eliminated. Both small fixed-wing and rotary-wing aircraft have been used in our experiments over two rangeland areas in the Jornada Experimental Range in southern New Mexico and the Santa Rita Experimental Range in southern Arizona. The fixed-wing UAV has a digital camera in the wing and six-band multispectral camera in the nose, while the rotary-wing UAV carries a digital camera as payload. Because we have been acquiring imagery for several years, there are now > 31,000 photos at one of the study sites, and 177 mosaics over rangeland areas have been constructed. Using the DEM obtained from the imagery we have determined the actual catchment areas of three watersheds and compared these to previous estimates. At one site, the UAV-derived watershed area is 4.67 ha which is 22% smaller compared to a manual survey using a GPS unit obtained several years ago. This difference can be significant in constructing a watershed model of the site. From a vegetation species classification, we also determined that two of the shrub types in this small watershed(mesquite and creosote with 6.47 % and 5.82% cover, respectively) grow in similar locations(flat upland areas with deep soils), whereas the most predominant shrub(mariola with 11.9% cover) inhabits hillslopes near stream channels(with steep shallow soils). The positioning of these individual shrubs throughout the catchment using

Person identification from aerial footage by a remote-controlled drone.

PubMed

Bindemann, Markus; Fysh, Matthew C; Sage, Sophie S K; Douglas, Kristina; Tummon, Hannah M

2017-10-19

Remote-controlled aerial drones (or unmanned aerial vehicles; UAVs) are employed for surveillance by the military and police, which suggests that drone-captured footage might provide sufficient information for person identification. This study demonstrates that person identification from drone-captured images is poor when targets are unfamiliar (Experiment 1), when targets are familiar and the number of possible identities is restricted by context (Experiment 2), and when moving footage is employed (Experiment 3). Person information such as sex, race and age is also difficult to access from drone-captured footage (Experiment 4). These findings suggest that such footage provides a particularly poor medium for person identification. This is likely to reflect the sub-optimal quality of such footage, which is subject to factors such as the height and velocity at which drones fly, viewing distance, unfavourable vantage points, and ambient conditions.

Earth mapping - aerial or satellite imagery comparative analysis

NASA Astrophysics Data System (ADS)

Fotev, Svetlin; Jordanov, Dimitar; Lukarski, Hristo

Nowadays, solving the tasks for revision of existing map products and creation of new maps requires making a choice of the land cover image source. The issue of the effectiveness and cost of the usage of aerial mapping systems versus the efficiency and cost of very-high resolution satellite imagery is topical [1, 2, 3, 4]. The price of any remotely sensed image depends on the product (panchromatic or multispectral), resolution, processing level, scale, urgency of task and on whether the needed image is available in the archive or has to be requested. The purpose of the present work is: to make a comparative analysis between the two approaches for mapping the Earth having in mind two parameters: quality and cost. To suggest an approach for selection of the map information sources - airplane-based or spacecraft-based imaging systems with very-high spatial resolution. Two cases are considered: area that equals approximately one satellite scene and area that equals approximately the territory of Bulgaria.

CFD Simulation of Aerial Crop Spraying

NASA Astrophysics Data System (ADS)

Omar, Zamri; Qiang, Kua Yong; Mohd, Sofian; Rosly, Nurhayati

2016-11-01

Aerial crop spraying, also known as crop dusting, is made for aerial application of pesticides or fertilizer. An agricultural aircraft which is converted from an aircraft has been built to combine with the aerial crop spraying for the purpose. In recent years, many studies on the aerial crop spraying were conducted because aerial application is the most economical, large and rapid treatment for the crops. The main objective of this research is to study the airflow of aerial crop spraying system using Computational Fluid Dynamics. This paper is focus on the effect of aircraft speed and nozzle orientation on the distribution of spray droplet at a certain height. Successful and accurate of CFD simulation will improve the quality of spray during the real situation and reduce the spray drift. The spray characteristics and efficiency are determined from the calculated results of CFD. Turbulence Model (k-ɛ Model) is used for the airflow in the fluid domain to achieve a more accurate simulation. Furthermore, spray simulation is done by setting the Flat-fan Atomizer Model of Discrete Phase Model (DPM) at the nozzle exit. The interaction of spray from each flat-fan atomizer can also be observed from the simulation. The evaluation of this study is validation and grid dependency study using field data from industry.

Low-altitude aerial color digital photographic survey of the San Andreas Fault

USGS Publications Warehouse

Lynch, David K.; Hudnut, Kenneth W.; Dearborn, David S.P.

2010-01-01

Ever since 1858, when Gaspard-Félix Tournachon (pen name Félix Nadar) took the first aerial photograph (Professional Aerial Photographers Association 2009), the scientific value and popular appeal of such pictures have been widely recognized. Indeed, Nadar patented the idea of using aerial photographs in mapmaking and surveying. Since then, aerial imagery has flourished, eventually making the leap to space and to wavelengths outside the visible range. Yet until recently, the availability of such surveys has been limited to technical organizations with significant resources. Geolocation required extensive time and equipment, and distribution was costly and slow. While these situations still plague older surveys, modern digital photography and lidar systems acquire well-calibrated and easily shared imagery, although expensive, platform-specific software is sometimes still needed to manage and analyze the data. With current consumer-level electronics (cameras and computers) and broadband internet access, acquisition and distribution of large imaging data sets are now possible for virtually anyone. In this paper we demonstrate a simple, low-cost means of obtaining useful aerial imagery by reporting two new, high-resolution, low-cost, color digital photographic surveys of selected portions of the San Andreas fault in California. All pictures are in standard jpeg format. The first set of imagery covers a 92-km-long section of the fault in Kern and San Luis Obispo counties and includes the entire Carrizo Plain. The second covers the region from Lake of the Woods to Cajon Pass in Kern, Los Angeles, and San Bernardino counties (151 km) and includes Lone Pine Canyon soon after the ground was largely denuded by the Sheep Fire of October 2009. The first survey produced a total of 1,454 oblique digital photographs (4,288 x 2,848 pixels, average 6 Mb each) and the second produced 3,762 nadir images from an elevation of approximately 150 m above ground level (AGL) on the

Absolute High-Precision Localisation of an Unmanned Ground Vehicle by Using Real-Time Aerial Video Imagery for Geo-referenced Orthophoto Registration

NASA Astrophysics Data System (ADS)

Kuhnert, Lars; Ax, Markus; Langer, Matthias; Nguyen van, Duong; Kuhnert, Klaus-Dieter

This paper describes an absolute localisation method for an unmanned ground vehicle (UGV) if GPS is unavailable for the vehicle. The basic idea is to combine an unmanned aerial vehicle (UAV) to the ground vehicle and use it as an external sensor platform to achieve an absolute localisation of the robotic team. Beside the discussion of the rather naive method directly using the GPS position of the aerial robot to deduce the ground robot's position the main focus of this paper lies on the indirect usage of the telemetry data of the aerial robot combined with live video images of an onboard camera to realise a registration of local video images with apriori registered orthophotos. This yields to a precise driftless absolute localisation of the unmanned ground vehicle. Experiments with our robotic team (AMOR and PSYCHE) successfully verify this approach.

Comparative Analysis of the Tour Jete and Aerial with Detailed Analysis of Aerial Takeoff Mechanics

NASA Astrophysics Data System (ADS)

Pierson, Mimi; Coplin, Kim

2006-10-01

Whether internally as muscle tension or from external sources, forces are necessary for all motion. This research focused on athletic rotations where conditions of flight are established during takeoff. By studying reaction forces that produce torques, moments of inertia, and linear and angular differences between distinct rotations around different principle axes of the body (tour jete in ballet - longitudinal axis; aerial in gymnastics - anteroposterior axis), and by looking at the values of angular momentum in the specific mechanics of aerial takeoff, we can gain insight into possible causes of injury, flaws in technique and limitations of athletes. Results showed significant differences in the horizontal and vertical components of takeoff between the tour jete and the aerial, and a realization that torque was produced in different biomechanical planes. Both rotations showed braking forces before takeoff to counteract forward momentum and increase vertical lift, but the angle of applied force varied, and the horizontal components of velocity and force and vertical velocity as well as moment of inertia throughout flight were consistently greater for the aerial. Breakdown of aerial takeoff highlighted the relative importance of the takeoff phases, showing that completion depends fundamentally upon the rotation of the rear foot and torso twisting during takeoff rather than the last foot in contact with the ground.

An accurate and adaptable photogrammetric approach for estimating the mass and body condition of pinnipeds using an unmanned aerial system

PubMed Central

Hinke, Jefferson T.; Perryman, Wayne L.; Goebel, Michael E.; LeRoi, Donald J.

2017-01-01

Measurements of body size and mass are fundamental to pinniped population management and research. Manual measurements tend to be accurate but are invasive and logistically challenging to obtain. Ground-based photogrammetric techniques are less invasive, but inherent limitations make them impractical for many field applications. The recent proliferation of unmanned aerial systems (UAS) in wildlife monitoring has provided a promising new platform for the photogrammetry of free-ranging pinnipeds. Leopard seals (Hydrurga leptonyx) are an apex predator in coastal Antarctica whose body condition could be a valuable indicator of ecosystem health. We aerially surveyed leopard seals of known body size and mass to test the precision and accuracy of photogrammetry from a small UAS. Flights were conducted in January and February of 2013 and 2014 and 50 photogrammetric samples were obtained from 15 unrestrained seals. UAS-derived measurements of standard length were accurate to within 2.01 ± 1.06%, and paired comparisons with ground measurements were statistically indistinguishable. An allometric linear mixed effects model predicted leopard seal mass within 19.40 kg (4.4% error for a 440 kg seal). Photogrammetric measurements from a single, vertical image obtained using UAS provide a noninvasive approach for estimating the mass and body condition of pinnipeds that may be widely applicable. PMID:29186134

An accurate and adaptable photogrammetric approach for estimating the mass and body condition of pinnipeds using an unmanned aerial system.

PubMed

Krause, Douglas J; Hinke, Jefferson T; Perryman, Wayne L; Goebel, Michael E; LeRoi, Donald J

2017-01-01

Measurements of body size and mass are fundamental to pinniped population management and research. Manual measurements tend to be accurate but are invasive and logistically challenging to obtain. Ground-based photogrammetric techniques are less invasive, but inherent limitations make them impractical for many field applications. The recent proliferation of unmanned aerial systems (UAS) in wildlife monitoring has provided a promising new platform for the photogrammetry of free-ranging pinnipeds. Leopard seals (Hydrurga leptonyx) are an apex predator in coastal Antarctica whose body condition could be a valuable indicator of ecosystem health. We aerially surveyed leopard seals of known body size and mass to test the precision and accuracy of photogrammetry from a small UAS. Flights were conducted in January and February of 2013 and 2014 and 50 photogrammetric samples were obtained from 15 unrestrained seals. UAS-derived measurements of standard length were accurate to within 2.01 ± 1.06%, and paired comparisons with ground measurements were statistically indistinguishable. An allometric linear mixed effects model predicted leopard seal mass within 19.40 kg (4.4% error for a 440 kg seal). Photogrammetric measurements from a single, vertical image obtained using UAS provide a noninvasive approach for estimating the mass and body condition of pinnipeds that may be widely applicable.

Satellite Images and Aerial Photographs of the Effects of Hurricanes Katrina and Rita on Coastal Louisiana

USGS Publications Warehouse

Barras, John A.

2007-01-01

-water datasets derived from the Landsat TM satellite imagery were combined with 2001 marsh vegetative communities (Chabreck and others, unpub. data, 2001) to identify land-water configurations by marsh community before and after the hurricanes. Links to the Landsat TM images and aerial photographs are given below (figs. 1-29). Comparison of land area before the storms to land area after the storms is made possible by the inclusion of Landsat TM images and aerial photographs taken in the years and months before the storms. The figures are arranged geographically from east to west to follow the chronology of the effects of the storms. For a more detailed analysis of the changes wrought by these storms, see 'Land Area Changes in Coastal Louisiana After Hurricanes Katrina and Rita' (Barras, in press).

Thermal/structural/optical integrated design for optical sensor mounted on unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Zhang, Gaopeng; Yang, Hongtao; Mei, Chao; Wu, Dengshan; Shi, Kui

2016-01-01

With the rapid development of science and technology and the promotion of many local wars in the world, altitude optical sensor mounted on unmanned aerial vehicle is more widely applied in the airborne remote sensing, measurement and detection. In order to obtain high quality image of the aero optical remote sensor, it is important to analysis its thermal-optical performance on the condition of high speed and high altitude. Especially for the key imaging assembly, such as optical window, the temperature variation and temperature gradient can result in defocus and aberrations in optical system, which will lead to the poor quality image. In order to improve the optical performance of a high speed aerial camera optical window, the thermal/structural/optical integrated design method is developed. Firstly, the flight environment of optical window is analyzed. Based on the theory of aerodynamics and heat transfer, the convection heat transfer coefficient is calculated. The temperature distributing of optical window is simulated by the finite element analysis software. The maximum difference in temperature of the inside and outside of optical window is obtained. Then the deformation of optical window under the boundary condition of the maximum difference in temperature is calculated. The optical window surface deformation is fitted in Zernike polynomial as the interface, the calculated Zernike fitting coefficients is brought in and analyzed by CodeV Optical Software. At last, the transfer function diagrams of the optical system on temperature field are comparatively analyzed. By comparing and analyzing the result, it can be obtained that the optical path difference caused by thermal deformation of the optical window is 138.2 nm, which is under PV ≤1 4λ . The above study can be used as an important reference for other optical window designs.

Weed Mapping in Early-Season Maize Fields Using Object-Based Analysis of Unmanned Aerial Vehicle (UAV) Images

PubMed Central

Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

2013-01-01

The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r2=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (<5% weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance. PMID:24146963

Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images.

PubMed

Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

2013-01-01

The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r(2)=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (<5% weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance.

An Assessment of Stream Confluence Flow Dynamics using Large Scale Particle Image Velocimetry Captured from Unmanned Aerial Systems

NASA Astrophysics Data System (ADS)

Lewis, Q. W.; Rhoads, B. L.

2017-12-01

The merging of rivers at confluences results in complex three-dimensional flow patterns that influence sediment transport, bed morphology, downstream mixing, and physical habitat conditions. The capacity to characterize comprehensively flow at confluences using traditional sensors, such as acoustic Doppler velocimeters and profiles, is limited by the restricted spatial resolution of these sensors and difficulties in measuring velocities simultaneously at many locations within a confluence. This study assesses two-dimensional surficial patterns of flow structure at a small stream confluence in Illinois, USA, using large scale particle image velocimetry (LSPIV) derived from videos captured by unmanned aerial systems (UAS). The method captures surface velocity patterns at high spatial and temporal resolution over multiple scales, ranging from the entire confluence to details of flow within the confluence mixing interface. Flow patterns at high momentum ratio are compared to flow patterns when the two incoming flows have nearly equal momentum flux. Mean surface flow patterns during the two types of events provide details on mean patterns of surface flow in different hydrodynamic regions of the confluence and on changes in these patterns with changing momentum flux ratio. LSPIV data derived from the highest resolution imagery also reveal general characteristics of large-scale vortices that form along the shear layer between the flows during the high-momentum ratio event. The results indicate that the use of LSPIV and UAS is well-suited for capturing in detail mean surface patterns of flow at small confluences, but that characterization of evolving turbulent structures is limited by scale considerations related to structure size, image resolution, and camera instability. Complementary methods, including camera platforms mounted at fixed positions close to the water surface, provide opportunities to accurately characterize evolving turbulent flow structures in confluences.

Aerial video mosaicking using binary feature tracking

NASA Astrophysics Data System (ADS)

Minnehan, Breton; Savakis, Andreas

2015-05-01

Unmanned Aerial Vehicles are becoming an increasingly attractive platform for many applications, as their cost decreases and their capabilities increase. Creating detailed maps from aerial data requires fast and accurate video mosaicking methods. Traditional mosaicking techniques rely on inter-frame homography estimations that are cascaded through the video sequence. Computationally expensive keypoint matching algorithms are often used to determine the correspondence of keypoints between frames. This paper presents a video mosaicking method that uses an object tracking approach for matching keypoints between frames to improve both efficiency and robustness. The proposed tracking method matches local binary descriptors between frames and leverages the spatial locality of the keypoints to simplify the matching process. Our method is robust to cascaded errors by determining the homography between each frame and the ground plane rather than the prior frame. The frame-to-ground homography is calculated based on the relationship of each point's image coordinates and its estimated location on the ground plane. Robustness to moving objects is integrated into the homography estimation step through detecting anomalies in the motion of keypoints and eliminating the influence of outliers. The resulting mosaics are of high accuracy and can be computed in real time.

3D Tree Dimensionality Assessment Using Photogrammetry and Small Unmanned Aerial Vehicles.

PubMed

Gatziolis, Demetrios; Lienard, Jean F; Vogs, Andre; Strigul, Nikolay S

2015-01-01

Detailed, precise, three-dimensional (3D) representations of individual trees are a prerequisite for an accurate assessment of tree competition, growth, and morphological plasticity. Until recently, our ability to measure the dimensionality, spatial arrangement, shape of trees, and shape of tree components with precision has been constrained by technological and logistical limitations and cost. Traditional methods of forest biometrics provide only partial measurements and are labor intensive. Active remote technologies such as LiDAR operated from airborne platforms provide only partial crown reconstructions. The use of terrestrial LiDAR is laborious, has portability limitations and high cost. In this work we capitalized on recent improvements in the capabilities and availability of small unmanned aerial vehicles (UAVs), light and inexpensive cameras, and developed an affordable method for obtaining precise and comprehensive 3D models of trees and small groups of trees. The method employs slow-moving UAVs that acquire images along predefined trajectories near and around targeted trees, and computer vision-based approaches that process the images to obtain detailed tree reconstructions. After we confirmed the potential of the methodology via simulation we evaluated several UAV platforms, strategies for image acquisition, and image processing algorithms. We present an original, step-by-step workflow which utilizes open source programs and original software. We anticipate that future development and applications of our method will improve our understanding of forest self-organization emerging from the competition among trees, and will lead to a refined generation of individual-tree-based forest models.

Software for roof defects recognition on aerial photographs

NASA Astrophysics Data System (ADS)

Yudin, D.; Naumov, A.; Dolzhenko, A.; Patrakova, E.

2018-05-01

The article presents information on software for roof defects recognition on aerial photographs, made with air drones. An areal image segmentation mechanism is described. It allows detecting roof defects – unsmoothness that causes water stagnation after rain. It is shown that HSV-transformation approach allows quick detection of stagnation areas, their size and perimeters, but is sensitive to shadows and changes of the roofing-types. Deep Fully Convolutional Network software solution eliminates this drawback. The tested data set consists of the roofing photos with defects and binary masks for them. FCN approach gave acceptable results of image segmentation in Dice metric average value. This software can be used in inspection automation of roof conditions in the production sector and housing and utilities infrastructure.

Tracking stormwater discharge plumes and water quality of the Tijuana River with multispectral aerial imagery

NASA Astrophysics Data System (ADS)

Svejkovsky, Jan; Nezlin, Nikolay P.; Mustain, Neomi M.; Kum, Jamie B.

2010-04-01

Spatial-temporal characteristics and environmental factors regulating the behavior of stormwater runoff from the Tijuana River in southern California were analyzed utilizing very high resolution aerial imagery, and time-coincident environmental and bacterial sampling data. Thirty nine multispectral aerial images with 2.1-m spatial resolution were collected after major rainstorms during 2003-2008. Utilizing differences in color reflectance characteristics, the ocean surface was classified into non-plume waters and three components of the runoff plume reflecting differences in age and suspended sediment concentrations. Tijuana River discharge rate was the primary factor regulating the size of the freshest plume component and its shorelong extensions to the north and south. Wave direction was found to affect the shorelong distribution of the shoreline-connected fresh plume components much more strongly than wind direction. Wave-driven sediment resuspension also significantly contributed to the size of the oldest plume component. Surf zone bacterial samples collected near the time of each image acquisition were used to evaluate the contamination characteristics of each plume component. The bacterial contamination of the freshest plume waters was very high (100% of surf zone samples exceeded California standards), but the oldest plume areas were heterogeneous, including both polluted and clean waters. The aerial imagery archive allowed study of river runoff characteristics on a plume component level, not previously done with coarser satellite images. Our findings suggest that high resolution imaging can quickly identify the spatial extents of the most polluted runoff but cannot be relied upon to always identify the entire polluted area. Our results also indicate that wave-driven transport is important in distributing the most contaminated plume areas along the shoreline.

3D measurement by digital photogrammetry

NASA Astrophysics Data System (ADS)

Schneider, Carl T.

1993-12-01

Photogrammetry is well known in geodetic surveys as aerial photogrammetry or close range applications as architectural photogrammetry. The photogrammetric methods and algorithms combined with digital cameras and digital image processing methods are now introduced for industrial applications as automation and quality control. The presented paper will describe the photogrammetric and digital image processing algorithms and the calibration methods. These algorithms and methods were demonstrated with application examples. These applications are a digital photogrammetric workstation as a mobil multi purpose 3D measuring tool and a tube measuring system as an example for a single purpose tool.

Profiles of gamma-ray and magnetic data from aerial surveys over the conterminous United States

USGS Publications Warehouse

Duval, Joseph S.; Riggle, Frederic E.

1999-01-01

This publication contains images for the conterminous U.S. generated from geophysical data, software for displaying and analyzing the images, and software for displaying and examining the profile data from the aerial surveys flown as part of the National Uranium Resource Evaluation (NURE) Program of the U.S. Department of Energy. The images included are of gamma-ray data (uranium, thorium, and potassium channels), Bouguer gravity data, isostatic residual gravity data, aeromagnetic anomalies, topography, and topography with bathymetry.

Aerial detection surveys in the United States

Treesearch

E. W. Johnson; D. Wittwer

2006-01-01

Aerial detection surveys, also known as aerial sketchmapping, is a remote sensing technique of observing forest change events from an aircraft and documenting them manually onto a map. Data from aerial surveys have become an important component of the Forest Health Monitoring, a national program designed to determine the status, changes, and trends in indicators of...

An aerial radiological survey of the project Rio Blanco and surrounding area

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singman, L.V.

1994-11-01

A team from the Remote Sensing Laboratory in Las Vegas, Nevada, conducted an aerial radiation survey of the area surrounding ground zero of Project Rio Blanco in the northwestern section of Colorado in June 1993. The object of the survey was to determine if there were man-made radioisotopes on or near the surface resulting from a nuclear explosion in 1972. No indications of surface contamination were found. A search for the cesium-137 radioisotope was negative. The Minimum Detectable Activity for cesium-137 is presented for several detection probabilities. The natural terrestrial exposure rates in units of Roentgens per hour were mappedmore » and are presented in the form of a contour map over-laid on an aerial photograph. A second team made independent ground-based measurements in four places within the survey area. The average agreement of the ground-based with aerial measurements was six percent.« less

Thermal Imaging of Subsurface Coal Fires by means of an Unmanned Aerial Vehicle (UAV) in the Autonomous Province Xinjiang, PRC

NASA Astrophysics Data System (ADS)

Vasterling, Margarete; Schloemer, Stefan; Fischer, Christian; Ehrler, Christoph

2010-05-01

Spontaneous combustion of coal and resulting coal fires lead to very high temperatures in the subsurface. To a large amount the heat is transferred to the surface by convective and conductive transport inducing a more or less pronounced thermal anomaly. During the past decade satellite-based infrared-imaging (ASTER, MODIS) was the method of choice for coal fire detection on a local and regional scale. However, the resolution is by far too low for a detailed analysis of single coal fires which is essential prerequisite for corrective measures (i.e. fire fighting) and calculation of carbon dioxide emission based on a complex correlation between energy release and CO2 generation. Consequently, within the framework of the Sino-German research project "Innovative Technologies for Exploration, Extinction and Monitoring of Coal Fires in Northern China", a new concept was developed and successfully tested. An unmanned aerial vehicle (UAV) was equipped with a lightweight camera for thermografic (resolution 160 by 120 pixel, dynamic range -20 to 250°C) and for visual imaging. The UAV designed as an octocopter is able to hover at GPS controlled waypoints during predefined flight missions. The application of a UAV has several advantages. Compared to point measurements on the ground the thermal imagery quickly provides the spatial distribution of the temperature anomaly with a much better resolution. Areas otherwise not accessible (due to topography, fire induced cracks, etc.) can easily be investigated. The results of areal surveys on two coal fires in Xinjiang are presented. Georeferenced thermal and visual images were mosaicked together and analyzed. UAV-born data do well compared to temperatures measured directly on the ground and cover large areas in detail. However, measuring surface temperature alone is not sufficient. Simultaneous measurements made at the surface and in roughly 15cm depth proved substantial temperature gradients in the upper soil. Thus the temperature

Notable environmental features in some historical aerial photographs from Ashley Country, Arkansas

Treesearch

Don C. Bragg; Robert C. Jr. Weih

2007-01-01

A collection of 1939 aerial photographs from Ashley County, Arkansas was analyzed for its environmental information. Taken by the US Department of Defense (USDOD), these images show a number of features now either obscured or completely eliminated over the passage of time. One notable feature is the widespread coverage of "sand blows" in the eastern quarter...

Bag of Lines (BoL) for Improved Aerial Scene Representation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sridharan, Harini; Cheriyadat, Anil M.

2014-09-22

Feature representation is a key step in automated visual content interpretation. In this letter, we present a robust feature representation technique, referred to as bag of lines (BoL), for high-resolution aerial scenes. The proposed technique involves extracting and compactly representing low-level line primitives from the scene. The compact scene representation is generated by counting the different types of lines representing various linear structures in the scene. Through extensive experiments, we show that the proposed scene representation is invariant to scale changes and scene conditions and can discriminate urban scene categories accurately. We compare the BoL representation with the popular scalemore » invariant feature transform (SIFT) and Gabor wavelets for their classification and clustering performance on an aerial scene database consisting of images acquired by sensors with different spatial resolutions. The proposed BoL representation outperforms the SIFT- and Gabor-based representations.« less

BOREAS Level-0 C-130 Aerial Photography

NASA Technical Reports Server (NTRS)

Newcomer, Jeffrey A.; Dominguez, Roseanne; Hall, Forrest G. (Editor)

2000-01-01

For BOReal Ecosystem-Atmosphere Study (BOREAS), C-130 and other aerial photography was collected to provide finely detailed and spatially extensive documentation of the condition of the primary study sites. The NASA C-130 Earth Resources aircraft can accommodate two mapping cameras during flight, each of which can be fitted with 6- or 12-inch focal-length lenses and black-and-white, natural-color, or color-IR film, depending upon requirements. Both cameras were often in operation simultaneously, although sometimes only the lower resolution camera was deployed. When both cameras were in operation, the higher resolution camera was often used in a more limited fashion. The acquired photography covers the period of April to September 1994. The aerial photography was delivered as rolls of large format (9 x 9 inch) color transparency prints, with imagery from multiple missions (hundreds of prints) often contained within a single roll. A total of 1533 frames were collected from the C-130 platform for BOREAS in 1994. Note that the level-0 C-130 transparencies are not contained on the BOREAS CD-ROM set. An inventory file is supplied on the CD-ROM to inform users of all the data that were collected. Some photographic prints were made from the transparencies. In addition, BORIS staff digitized a subset of the tranparencies and stored the images in JPEG format. The CD-ROM set contains a small subset of the collected aerial photography that were the digitally scanned and stored as JPEG files for most tower and auxiliary sites in the NSA and SSA. See Section 15 for information about how to acquire additional imagery.

Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

NASA Astrophysics Data System (ADS)

Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

2017-09-01

Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Unmanned aerial vehicle: A unique platform for low-altitude remote sensing for crop management

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAV) provide a unique platform for remote sensing to monitor crop fields that complements remote sensing from satellite, aircraft and ground-based platforms. The UAV-based remote sensing is versatile at ultra-low altitude to be able to provide an ultra-high-resolution imag...

Assessing land leveling needs and performance with unmanned aerial system

NASA Astrophysics Data System (ADS)

Enciso, Juan; Jung, Jinha; Chang, Anjin; Chavez, Jose Carlos; Yeom, Junho; Landivar, Juan; Cavazos, Gabriel

2018-01-01

Land leveling is the initial step for increasing irrigation efficiencies in surface irrigation systems. The objective of this paper was to evaluate potential utilization of an unmanned aerial system (UAS) equipped with a digital camera to map ground elevations of a grower's field and compare them with field measurements. A secondary objective was to use UAS data to obtain a digital terrain model before and after land leveling. UAS data were used to generate orthomosaic images and three-dimensional (3-D) point cloud data by applying the structure for motion algorithm to the images. Ground control points (GCPs) were established around the study area, and they were surveyed using a survey grade dual-frequency GPS unit for accurate georeferencing of the geospatial data products. A digital surface model (DSM) was then generated from the 3-D point cloud data before and after laser leveling to determine the topography before and after the leveling. The UAS-derived DSM was compared with terrain elevation measurements acquired from land surveying equipment for validation. Although 0.3% error or root mean square error of 0.11 m was observed between UAS derived and ground measured ground elevation data, the results indicated that UAS could be an efficient method for determining terrain elevation with an acceptable accuracy when there are no plants on the ground, and it can be used to assess the performance of a land leveling project.

The application of GPS precise point positioning technology in aerial triangulation

NASA Astrophysics Data System (ADS)

Yuan, Xiuxiao; Fu, Jianhong; Sun, Hongxing; Toth, Charles

In traditional GPS-supported aerotriangulation, differential GPS (DGPS) positioning technology is used to determine the 3-dimensional coordinates of the perspective centers at exposure time with an accuracy of centimeter to decimeter level. This method can significantly reduce the number of ground control points (GCPs). However, the establishment of GPS reference stations for DGPS positioning is not only labor-intensive and costly, but also increases the implementation difficulty of aerial photography. This paper proposes aerial triangulation supported with GPS precise point positioning (PPP) as a way to avoid the use of the GPS reference stations and simplify the work of aerial photography. Firstly, we present the algorithm for GPS PPP in aerial triangulation applications. Secondly, the error law of the coordinate of perspective centers determined using GPS PPP is analyzed. Thirdly, based on GPS PPP and aerial triangulation software self-developed by the authors, four sets of actual aerial images taken from surveying and mapping projects, different in both terrain and photographic scale, are given as experimental models. The four sets of actual data were taken over a flat region at a scale of 1:2500, a mountainous region at a scale of 1:3000, a high mountainous region at a scale of 1:32000 and an upland region at a scale of 1:60000 respectively. In these experiments, the GPS PPP results were compared with results obtained through DGPS positioning and traditional bundle block adjustment. In this way, the empirical positioning accuracy of GPS PPP in aerial triangulation can be estimated. Finally, the results of bundle block adjustment with airborne GPS controls from GPS PPP are analyzed in detail. The empirical results show that GPS PPP applied in aerial triangulation has a systematic error of half-meter level and a stochastic error within a few decimeters. However, if a suitable adjustment solution is adopted, the systematic error can be eliminated in GPS

Utilization of Local Law Enforcement Aerial Resources in Consequence Management (CM) Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wasiolek, Piotr T.; Malchow, Russell L.

2013-03-12

During the past decade the U.S. Department of Homeland Security (DHS) was instrumental in enhancing the nation’s ability to detect and prevent a radiological or nuclear attack in the highest risk cities. Under the DHS Securing the Cities initiative, nearly 13,000 personnel in the New York City region have been trained in preventive radiological and nuclear detection operations, and nearly 8,500 pieces of radiological detection equipment have been funded. As part of the preventive radiological/nuclear detection (PRND) mission, several cities have received funding to purchase commercial aerial radiation detection systems. In 2008, the U.S. Department of Energy, National Nuclear Securitymore » Administration Aerial Measuring System (AMS) program started providing Mobile Aerial Radiological Surveillance (MARS) training to such assets, resulting in over 150 HAZMAT teams’ officers and pilots from 10 law enforcement organizations and fire departments being trained in the aerial radiation detection. From the beginning, the MARS training course covered both the PRND and consequence management (CM) missions. Even if the law enforcement main focus is PRND, their aerial assets can be utilized in the collection of initial radiation data for post-event radiological CM response. Based on over 50 years of AMS operational experience and information collected during MARS training, this presentation will focus on the concepts of CM response using aerial assets as well as utilizing law enforcement/fire department aerial assets in CM. Also discussed will be the need for establishing closer relationships between local jurisdictions’ aerial radiation detection capabilities and state and local radiation control program directors, radiological health department managers, etc. During radiological events these individuals may become primary experts/advisers to Incident Commanders for radiological emergency response, especially in the early stages of a response. The knowledge of the

Automatic Building Abstraction from Aerial Photogrammetry

NASA Astrophysics Data System (ADS)

Ley, A.; Hänsch, R.; Hellwich, O.

2017-09-01

Multi-view stereo has been shown to be a viable tool for the creation of realistic 3D city models. Nevertheless, it still states significant challenges since it results in dense, but noisy and incomplete point clouds when applied to aerial images. 3D city modelling usually requires a different representation of the 3D scene than these point clouds. This paper applies a fully-automatic pipeline to generate a simplified mesh from a given dense point cloud. The mesh provides a certain level of abstraction as it only consists of relatively large planar and textured surfaces. Thus, it is possible to remove noise, outlier, as well as clutter, while maintaining a high level of accuracy.

Detecting lost persons using the k-mean method applied to aerial photographs taken by unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Niedzielski, Tomasz; Stec, Magdalena; Wieczorek, Malgorzata; Slopek, Jacek; Jurecka, Miroslawa

2016-04-01

The objective of this work is to discuss the usefulness of the k-mean method in the process of detecting persons on oblique aerial photographs acquired by unmanned aerial vehicles (UAVs). The detection based on the k-mean procedure belongs to one of the modules of a larger Search and Rescue (SAR) system which is being developed at the University of Wroclaw, Poland (research project no. IP2014 032773 financed by the Ministry of Science and Higher Education of Poland). The module automatically processes individual geotagged visual-light UAV-taken photographs or their orthorectified versions. Firstly, we separate red (R), green (G) and blue (B) channels, express raster data as numeric matrices and acquire coordinates of centres of images using the exchangeable image file format (EXIF). Subsequently, we divide the matrices into matrices of smaller dimensions, the latter being associated with the size of spatial window which is suitable for discriminating between human and terrain. Each triplet of the smaller matrices (R, G and B) serves as input spatial data for the k-mean classification. We found that, in several configurations of the k-mean parameters, it is possible to distinguish a separate class which characterizes a person. We compare the skills of this approach by performing two experiments, based on UAV-taken RGB photographs and their orthorectified versions. This allows us to verify the hypothesis that the two exercises lead to similar classifications. In addition, we discuss the performance of the approach for dissimilar spatial windows, hence various dimensions of the above-mentioned matrices, and we do so in order to find the one which offers the most adequate classification. The numerical experiment is carried out using the data acquired during a dedicated observational UAV campaign carried out in the Izerskie Mountains (SW Poland).

Comprehensive emission measurements from prescribed burning in Florida: field and laboratory, aerial and ground

EPA Science Inventory

Simultaneous aerial- and ground-based emission sampling was conducted during prescribed burns at Eglin Air Force Base in November 2012 on a short grass/shrub field and a pine forest. Cumulative emission samples for volatile organic compounds, elemental carbon, organic carbon, c...

Aerospace toxicology overview: aerial application and cabin air quality.

PubMed

Chaturvedi, Arvind K

2011-01-01

Aerospace toxicology is a rather recent development and is closely related to aerospace medicine. Aerospace toxicology can be defined as a field of study designed to address the adverse effects of medications, chemicals, and contaminants on humans who fly within or outside the atmosphere in aviation or on space flights. The environment extending above and beyond the surface of the Earth is referred to as aerospace. The term aviation is frequently used interchangeably with aerospace. The focus of the literature review performed to prepare this paper was on aerospace toxicology-related subject matters, aerial application and aircraft cabin air quality. Among the important topics addressed are the following: · Aerial applications of agricultural chemicals, pesticidal toxicity, and exposures to aerially applied mixtures of chemicals and their associated formulating solvents/surfactants The safety of aerially encountered chemicals and the bioanalytical methods used to monitor exposures to some of them · The presence of fumes and smoke, as well as other contaminants that may generally be present in aircraft/space vehicle cabin air · And importantly, the toxic effects of aerially encountered contaminants, with emphasis on the degradation products of oils, fluids, and lubricants used in aircraft, and finally · Analytical methods used for monitoring human exposure to CO and HCN are addressed in the review, as are the signs and symptoms associated with exposures to these combustion gases. Although many agricultural chemical monitoring studies have been published, few have dealt with the occurrence of such chemicals in aircraft cabin air. However, agricultural chemicals do appear in cabin air; indeed, attempts have been made to establish maximum allowable concentrations for several of the more potentially toxic ones that are found in aircraft cabin air. In this article, I emphasize the need for precautionary measures to be taken to minimize exposures to aerially

Infrared film for aerial photography

USGS Publications Warehouse

Anderson, William H.

1979-01-01

Considerable interest has developed recently in the use of aerial photographs for agricultural management. Even the simplest hand-held aerial photographs, especially those taken with color infrared film, often provide information not ordinarily available through routine ground observation. When fields are viewed from above, patterns and variations become more apparent, often allowing problems to be spotted which otherwise may go undetected.

Quantitative analysis of drainage obtained from aerial photographs and RBV/LANDSAT images

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Formaggio, A. R.; Epiphanio, J. C. N.; Filho, M. V.

1981-01-01

Data obtained from aerial photographs (1:60,000) and LANDSAT return beam vidicon imagery (1:100,000) concerning drainage density, drainage texture, hydrography density, and the average length of channels were compared. Statistical analysis shows that significant differences exist in data from the two sources. The highly drained area lost more information than the less drained area. In addition, it was observed that the loss of information about the number of rivers was higher than that about the length of the channels.

Hyperspatial Thermal Imaging of Surface Hydrothermal Features at Pilgrim Hot Springs, Alaska using a small Unmanned Aerial System (sUAS)

NASA Astrophysics Data System (ADS)

Haselwimmer, C. E.; Wilson, R.; Upton, C.; Prakash, A.; Holdmann, G.; Walker, G.

2013-12-01

Thermal remote sensing provides a valuable tool for mapping and monitoring surface hydrothermal features associated with geothermal activity. The increasing availability of low-cost, small Unmanned Aerial Systems (sUAS) with integrated thermal imaging sensors offers a means to undertake very high spatial resolution (hyperspatial), quantitative thermal remote sensing of surface geothermal features in support of exploration and long-term monitoring efforts. Results from the deployment of a quadcopter sUAS equipped with a thermal camera over Pilgrim Hot Springs, Alaska for detailed mapping and heat flux estimation for hot springs, seeps, and thermal pools are presented. Hyperspatial thermal infrared imagery (4 cm pixels) was acquired over Pilgrim Hot Springs in July 2013 using a FLIR TAU 640 camera operating from an Aeryon Scout sUAS flying at an altitude of 40m. The registered and mosaicked thermal imagery is calibrated to surface temperature values using in-situ measurements of uniform blackbody tarps and the temperatures of geothermal and other surface pools acquired with a series of water temperature loggers. Interpretation of the pre-processed thermal imagery enables the delineation of hot springs, the extents of thermal pools, and the flow and mixing of individual geothermal outflow plumes with an unprecedented level of detail. Using the surface temperatures of thermal waters derived from the FLIR data and measured in-situ meteorological parameters the hot spring heat flux and outflow rate is calculated using a heat budget model for a subset of the thermal drainage. The heat flux/outflow rate estimates derived from the FLIR data are compared against in-situ measurements of the hot spring outflow rate recorded at the time of the thermal survey.

47 CFR 32.2421 - Aerial cable.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Aerial cable. 32.2421 Section 32.2421 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES UNIFORM SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Balance Sheet Accounts § 32.2421 Aerial cable. (a...

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

NASA Astrophysics Data System (ADS)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

Unmanned Aerial Vehicles Produce High-Resolution Seasonally-Relevant Imagery for Classifying Wetland Vegetation

NASA Astrophysics Data System (ADS)

Marcaccio, J. V.; Markle, C. E.; Chow-Fraser, P.

2015-08-01

With recent advances in technology, personal aerial imagery acquired with unmanned aerial vehicles (UAVs) has transformed the way ecologists can map seasonal changes in wetland habitat. Here, we use a multi-rotor (consumer quad-copter, the DJI Phantom 2 Vision+) UAV to acquire a high-resolution (< 8 cm) composite photo of a coastal wetland in summer 2014. Using validation data collected in the field, we determine if a UAV image and SWOOP (Southwestern Ontario Orthoimagery Project) image (collected in spring 2010) differ in their classification of type of dominant vegetation type and percent cover of three plant classes: submerged aquatic vegetation, floating aquatic vegetation, and emergent vegetation. The UAV imagery was more accurate than available SWOOP imagery for mapping percent cover of submergent and floating vegetation categories, but both were able to accurately determine the dominant vegetation type and percent cover of emergent vegetation. Our results underscore the value and potential for affordable UAVs (complete quad-copter system < 3,000 CAD) to revolutionize the way ecologists obtain imagery and conduct field research. In Canada, new UAV regulations make this an easy and affordable way to obtain multiple high-resolution images of small (< 1.0 km2) wetlands, or portions of larger wetlands throughout a year.

An aerial radiological survey of Maralinga and EMU, South Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tipton, W J; Berry, H A; Fritzsche, A E

An aerial radiological survey was conducted over the former British nuclear test ranges at Maralinga and Emu in South Australia from May through July 1987. The survey covered an area of approximately 1,550 square kilometers which included the nine major trial sites, where a nuclear yield occurred, and all the minor trial sites, where physics experiments were conducted. Flight lines were flown at an altitude of 30 meters with line spacings of 50, 100, and 200 meters depending on the area and whether man-made contamination was present. Results of the aerial survey were processed for americium-241 (used to determine plutoniummore » contamination), cesium-137, cobalt-60, and uranium-238. The aerial survey also detected the presence of europium-152, a soil activation product, in the immediate vicinity of the major trial ground zeros. Ground measurements were also made at approximately 120 locations using a high-resolution germanium detector to provide supplemental data for the aerial survey. This survey was conducted as part of a series of studies being conducted over a two to three-year timeframe to obtain information from which options and associated costs can be formulated about the decontamination and possible rehabilitation of the former nuclear test sites.« less

Use of 35-mm color aerial photography to acquire mallard sex ratio data

USGS Publications Warehouse

Ferguson, Edgar L.; Jorde, Dennis G.; Sease, John L.

1981-01-01

A conventional 35-mm camera equipped with an f2.8 135-mm lens and ASA 64 color film was used to acquire sex ratio data on mallards (Anas platyrhynchos) wintering in the Platte River Valley of south-central Nebraska. Prelight focusing for a distance of 30.5 metres and setting of shutter speed at 1/2000 of a second eliminated focusing and reduced image motion problems and resulted in high-resolution, large-scale aerial photography of small targets. This technique has broad application to the problem of determining sex ratios of various species of waterfowl concentrated on wintering and staging areas. The aerial photographic method was cheaper than the ground ocular method when costs were compared on a per-100 bird basis.

Application possibilities of aerial and terrain data evaluation in particulate pollution effects

NASA Astrophysics Data System (ADS)

Kozma-Bognar, V.; Berke, J.; Martin, G.

2012-04-01

Recently, remote sensing has become a widely used technology in order to acquire information about our environment. Data collected using remote sensing technology indispensible criteria to recognise and monitor environmental problems caused by contamination from various human activities. According to great technological change and development in the previous decade high spectral and geometric resolution sensors are more often used. The higher resolution technology allows getting more accurate and reliable results in the research processes of the environmental pollution impacts. At University of Pannonia, Georgikon Faculty (Hungary) plant-soil-atmosphere system analyses are carried out for detecting the potential harmful effects of heavy metal pollution originated from vehicle industry. Related to this research at the Department of Meteorology and Water Management, black carbon and cadmium pollution effects are being analysed on maize crops. Testing area is situated at Agro-meteorological Research Station in Keszthely, where the first time in 2011 aerial imaging technology was used in parallel with field analyses. The experiment aims to analyses correlation of the field data with aerial data. During aerial photography were taken in different spectral bands (Visible, Near Infrared, Far Infrared). High intensity, spectral and spatial resolution data was an important part of the multitemporal imagine sensing and evaluating technology, therefore original technical solutions were applied. These resolutions served accurate plot-level evaluation. Fractal structure and intensity measurement evaluation methods were applied to examine black carbon and cadmium polluted and control maize canopy after data pre-processing. Research also focused on the examination of potential negative or positive effects of irrigation so that differences between irrigated and non-irrigated maize was investigated. For the period of growing season of 2011 time-series analyses were carried out in

Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems

NASA Astrophysics Data System (ADS)

Longmore, S. N.; Collins, R. P.; Pfeifer, S.; Fox, S. E.; Mulero-Pazmany, M.; Bezombes, F.; Goodwind, A.; de Juan Ovelar, M.; Knapen, J. H.; Wich, S. A.

2017-02-01

In this paper we describe an unmanned aerial system equipped with a thermal-infrared camera and software pipeline that we have developed to monitor animal populations for conservation purposes. Taking a multi-disciplinary approach to tackle this problem, we use freely available astronomical source detection software and the associated expertise of astronomers, to efficiently and reliably detect humans and animals in aerial thermal-infrared footage. Combining this astronomical detection software with existing machine learning algorithms into a single, automated, end-to-end pipeline, we test the software using aerial video footage taken in a controlled, field-like environment. We demonstrate that the pipeline works reliably and describe how it can be used to estimate the completeness of different observational datasets to objects of a given type as a function of height, observing conditions etc. - a crucial step in converting video footage to scientifically useful information such as the spatial distribution and density of different animal species. Finally, having demonstrated the potential utility of the system, we describe the steps we are taking to adapt the system for work in the field, in particular systematic monitoring of endangered species at National Parks around the world.

Drogue pose estimation for unmanned aerial vehicle autonomous aerial refueling system based on infrared vision sensor

NASA Astrophysics Data System (ADS)

Chen, Shanjun; Duan, Haibin; Deng, Yimin; Li, Cong; Zhao, Guozhi; Xu, Yan

2017-12-01

Autonomous aerial refueling is a significant technology that can significantly extend the endurance of unmanned aerial vehicles. A reliable method that can accurately estimate the position and attitude of the probe relative to the drogue is the key to such a capability. A drogue pose estimation method based on infrared vision sensor is introduced with the general goal of yielding an accurate and reliable drogue state estimate. First, by employing direct least squares ellipse fitting and convex hull in OpenCV, a feature point matching and interference point elimination method is proposed. In addition, considering the conditions that some infrared LEDs are damaged or occluded, a missing point estimation method based on perspective transformation and affine transformation is designed. Finally, an accurate and robust pose estimation algorithm improved by the runner-root algorithm is proposed. The feasibility of the designed visual measurement system is demonstrated by flight test, and the results indicate that our proposed method enables precise and reliable pose estimation of the probe relative to the drogue, even in some poor conditions.

Deformation during the 1975-1984 Krafla rifting crisis, NE Iceland, measured from historical optical imagery

NASA Astrophysics Data System (ADS)

Hollingsworth, James; Leprince, SéBastien; Ayoub, FrançOis; Avouac, Jean-Philippe

2012-11-01

We measure the displacement field resulting from the 1975-1984 Krafla rifting crisis, NE Iceland, using optical image correlation. Images are processed using the COSI-Corr software package. Surface extension is accommodated on normal faults and fissures which bound the rift zone, in response to dike injection at depth. Correlation of declassified KH-9 spy and SPOT5 satellite images reveals extension between 1977-2002 (2.5 m average opening over 80 km), while correlation of aerial photos between 1957-1990 provide measurements of the total extension (average 4.3 m opening over 80 km). Our results show ˜8 m of opening immediately north of Krafla caldera, decreasing to 3-4 m at the northern end of the rift. Correlation of aerial photos from 1957-1976 reveal a bi-modal pattern of opening along the rift during the early crisis, which may indicate either two different magma sources located at either end of the rift zone (a similar pattern of opening was observed in the 2005 Afar rift crisis in East Africa), or variations in rock strength along the rift. Our results provide new information on how past dike injection events accommodate long-term plate spreading, as well as providing more details on the Krafla rift crisis. This study also highlights the potential of optical image correlation using inexpensive declassified spy satellite and aerial photos to measure deformation of the Earth's surface going back many decades, thus providing a new tool for measuring Earth surface dynamics, e.g. glaciers, landsliding, coastal erosion, volcano monitoring and earthquake studies, when InSAR and GPS data are not available.

3D Tree Dimensionality Assessment Using Photogrammetry and Small Unmanned Aerial Vehicles

PubMed Central

2015-01-01

Detailed, precise, three-dimensional (3D) representations of individual trees are a prerequisite for an accurate assessment of tree competition, growth, and morphological plasticity. Until recently, our ability to measure the dimensionality, spatial arrangement, shape of trees, and shape of tree components with precision has been constrained by technological and logistical limitations and cost. Traditional methods of forest biometrics provide only partial measurements and are labor intensive. Active remote technologies such as LiDAR operated from airborne platforms provide only partial crown reconstructions. The use of terrestrial LiDAR is laborious, has portability limitations and high cost. In this work we capitalized on recent improvements in the capabilities and availability of small unmanned aerial vehicles (UAVs), light and inexpensive cameras, and developed an affordable method for obtaining precise and comprehensive 3D models of trees and small groups of trees. The method employs slow-moving UAVs that acquire images along predefined trajectories near and around targeted trees, and computer vision-based approaches that process the images to obtain detailed tree reconstructions. After we confirmed the potential of the methodology via simulation we evaluated several UAV platforms, strategies for image acquisition, and image processing algorithms. We present an original, step-by-step workflow which utilizes open source programs and original software. We anticipate that future development and applications of our method will improve our understanding of forest self-organization emerging from the competition among trees, and will lead to a refined generation of individual-tree-based forest models. PMID:26393926

Aerial Refueling Boom/Receptacle Guide

DTIC Science & Technology

2017-07-28

Alleviation System; AR – Aerial Refueling; IDS – Independent Disconnect System; PDL – Pilot Director Lights; PSIG – Pounds per square inch gauge; TMF...proprietary, sensitive, classified or otherwise restricted information. ARSAG documents, as prepared, are not DOD, MOD or NATO standards, but provide...Boom Nozzle Disconnect Provisions, Aerial Refueling Fuel System and Tanker Aids and Cues for the Receiver Aircraft. Also included are Receiver

Aerial Photography

NASA Technical Reports Server (NTRS)

1985-01-01

John Hill, a pilot and commercial aerial photographer, needed an information base. He consulted NERAC and requested a search of the latest developments in camera optics. NERAC provided information; Hill contacted the manufacturers of camera equipment and reduced his photographic costs significantly.

Fusion of monocular cues to detect man-made structures in aerial imagery

NASA Technical Reports Server (NTRS)

Shufelt, Jefferey; Mckeown, David M.

1991-01-01

The extraction of buildings from aerial imagery is a complex problem for automated computer vision. It requires locating regions in a scene that possess properties distinguishing them as man-made objects as opposed to naturally occurring terrain features. It is reasonable to assume that no single detection method can correctly delineate or verify buildings in every scene. A cooperative-methods paradigm is useful in approaching the building extraction problem. Using this paradigm, each extraction technique provides information which can be added or assimilated into an overall interpretation of the scene. Thus, the main objective is to explore the development of computer vision system that integrates the results of various scene analysis techniques into an accurate and robust interpretation of the underlying three dimensional scene. The problem of building hypothesis fusion in aerial imagery is discussed. Building extraction techniques are briefly surveyed, including four building extraction, verification, and clustering systems. A method for fusing the symbolic data generated by these systems is described, and applied to monocular image and stereo image data sets. Evaluation methods for the fusion results are described, and the fusion results are analyzed using these methods.

Yellow River Icicle Hazard Dynamic Monitoring Using UAV Aerial Remote Sensing Technology

NASA Astrophysics Data System (ADS)

Wang, H. B.; Wang, G. H.; Tang, X. M.; Li, C. H.

2014-02-01

Monitoring the response of Yellow River icicle hazard change requires accurate and repeatable topographic surveys. A new method based on unmanned aerial vehicle (UAV) aerial remote sensing technology is proposed for real-time data processing in Yellow River icicle hazard dynamic monitoring. The monitoring area is located in the Yellow River ice intensive care area in southern BaoTou of Inner Mongolia autonomous region. Monitoring time is from the 20th February to 30th March in 2013. Using the proposed video data processing method, automatic extraction covering area of 7.8 km2 of video key frame image 1832 frames took 34.786 seconds. The stitching and correcting time was 122.34 seconds and the accuracy was better than 0.5 m. Through the comparison of precise processing of sequence video stitching image, the method determines the change of the Yellow River ice and locates accurate positioning of ice bar, improving the traditional visual method by more than 100 times. The results provide accurate aid decision information for the Yellow River ice prevention headquarters. Finally, the effect of dam break is repeatedly monitored and ice break five meter accuracy is calculated through accurate monitoring and evaluation analysis.

47 CFR 32.2431 - Aerial wire.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Aerial wire. 32.2431 Section 32.2431... FOR TELECOMMUNICATIONS COMPANIES Instructions for Balance Sheet Accounts § 32.2431 Aerial wire. (a) This account shall include the original cost of bare line wire and other material used in the...

47 CFR 32.2431 - Aerial wire.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Aerial wire. 32.2431 Section 32.2431... FOR TELECOMMUNICATIONS COMPANIES Instructions for Balance Sheet Accounts § 32.2431 Aerial wire. (a) This account shall include the original cost of bare line wire and other material used in the...

Control surface in aerial triangulation

NASA Astrophysics Data System (ADS)

Jaw, Jen-Jer

With the increased availability of surface-related sensors, the collection of surface information becomes easier and more straightforward than ever before. In this study, the author proposes a model in which the surface information is integrated into the aerial triangulation workflow by hypothesizing plane observations in the object space, the estimated object points via photo measurements (or matching) together with the adjusted surface points would provide a better point group describing the surface. The algorithms require no special structure of surface points and involve no interpolation process. The suggested measuring strategy (pairwise measurements) results in a quite fluent and favorable working environment when taking measurements. Furthermore, the extension of the model employing the the surface plane finds itself useful in tying photo models. The proposed model has been proven working by the simulation and carried out in the photogrammetric laboratory.

First Experiences Using Small Unmanned Aerial Vehicles for Volcano Observation in the Visible Range

NASA Astrophysics Data System (ADS)

Buschmann, M.; Krüger, L.; Bange, J.

2007-05-01

~megapixel. On a field campaign in 2005, the performance of the system was evaluated at the two active Ecuadorian volcanoes Cotopaxi and El~Reventador. After hand-launch at Mt. Cotopaxi, the autopilot brought the aircraft up to 7,000~m above sea level (starting from a plateau on 4,500~m a.s.l.), with temperatures around the freezing point. At El~Reventador active lava flows were documented in the tropical montane rain forest. Since the position and attitude of the aircraft is recorded within the autopilot system, the single aerial images can be referenced automatically after the flight to form a mosaic of images. The whole processing chain from mission planning to image mosaic takes less than half a day. Besides the technical details of this cost-effective remote sensing system, the results of the measurement campaign in 2005 will be presented. An outlook will discuss the installation of other payload for thermal imaging or air sampling.

Identification of disrupted surfaces due to military activity at the Ft. Irwin National Training Center: An aerial photograph and satellite image analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCarthy, L.E.; Marsh, S.E.; Lee, C.

1996-07-01

Concern for environmental management of our natural resources is most often focused on the anthropogenic impacts placed upon these resources. Desert landscapes, in particular, are fragile environments, and minimal stresses on surficial materials can greatly increase the rate and character of erosional responses. The National Training Center, Ft. Irwin, located in the middle of the Mojave Desert, California, provides an isolated study area of intense ORV activity occurring over a 50-year period. Geomorphic surfaces, and surficial disruption from two study sites within the Ft. Irwin area were mapped from 1947, 1:28,400, and 1993 1:12,000 black and white aerial photographs. Severalmore » field checks were conducted to verify this mapping. However, mapping from black and white aerial photography relies heavily on tonal differences, patterns, and morphological criteria. Satellite imagery, sensitive to changes in mineralogy, can help improve the ability to distinguish geomorphic units in desert regions. In order to assess both the extent of disrupted surfaces and the surficial geomorphology discemable from satellite imagery, analysis was done on SPOT panchromatic and Landsat Thematic Mapper (TM) multispectral imagery acquired during the spring of 1987 and 1993. The resulting classified images provide a clear indication of the capabilities of the satellite data to aid in the delineation of disrupted geomorphic surfaces.« less

Similar Running Economy With Different Running Patterns Along the Aerial-Terrestrial Continuum.

PubMed

Lussiana, Thibault; Gindre, Cyrille; Hébert-Losier, Kim; Sagawa, Yoshimasa; Gimenez, Philippe; Mourot, Laurent

2017-04-01

No unique or ideal running pattern is the most economical for all runners. Classifying the global running patterns of individuals into 2 categories (aerial and terrestrial) using the Volodalen method could permit a better understanding of the relationship between running economy (RE) and biomechanics. The main purpose was to compare the RE of aerial and terrestrial runners. Two coaches classified 58 runners into aerial (n = 29) or terrestrial (n = 29) running patterns on the basis of visual observations. RE, muscle activity, kinematics, and spatiotemporal parameters of both groups were measured during a 5-min run at 12 km/h on a treadmill. Maximal oxygen uptake (V̇O 2 max) and peak treadmill speed (PTS) were assessed during an incremental running test. No differences were observed between aerial and terrestrial patterns for RE, V̇O 2 max, and PTS. However, at 12 km/h, aerial runners exhibited earlier gastrocnemius lateralis activation in preparation for contact, less dorsiflexion at ground contact, higher coactivation indexes, and greater leg stiffness during stance phase than terrestrial runners. Terrestrial runners had more pronounced semitendinosus activation at the start and end of the running cycle, shorter flight time, greater leg compression, and a more rear-foot strike. Different running patterns were associated with similar RE. Aerial runners appear to rely more on elastic energy utilization with a rapid eccentric-concentric coupling time, whereas terrestrial runners appear to propel the body more forward rather than upward to limit work against gravity. Excluding runners with a mixed running pattern from analyses did not affect study interpretation.

Measuring water level in rivers and lakes from lightweight Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Jakobsen, Jakob; Olesen, Daniel; Reyna-Gutierrez, Jose Antonio; Bauer-Gottwein, Peter

2017-05-01

The assessment of hydrologic dynamics in rivers, lakes, reservoirs and wetlands requires measurements of water level, its temporal and spatial derivatives, and the extent and dynamics of open water surfaces. Motivated by the declining number of ground-based measurement stations, research efforts have been devoted to the retrieval of these hydraulic properties from spaceborne platforms in the past few decades. However, due to coarse spatial and temporal resolutions, spaceborne missions have several limitations when assessing the water level of terrestrial surface water bodies and determining complex water dynamics. Unmanned Aerial Vehicles (UAVs) can fill the gap between spaceborne and ground-based observations, and provide high spatial resolution and dense temporal coverage data, in quick turn-around time, using flexible payload design. This study focused on categorizing and testing sensors, which comply with the weight constraint of small UAVs (around 1.5 kg), capable of measuring the range to water surface. Subtracting the measured range from the vertical position retrieved by the onboard Global Navigation Satellite System (GNSS) receiver, we can determine the water level (orthometric height). Three different ranging payloads, which consisted of a radar, a sonar and an in-house developed camera-based laser distance sensor (CLDS), have been evaluated in terms of accuracy, precision, maximum ranging distance and beam divergence. After numerous flights, the relative accuracy of the overall system was estimated. A ranging accuracy better than 0.5% of the range and a maximum ranging distance of 60 m were achieved with the radar. The CLDS showed the lowest beam divergence, which is required to avoid contamination of the signal from interfering surroundings for narrow fields of view. With the GNSS system delivering a relative vertical accuracy better than 3-5 cm, water level can be retrieved with an overall accuracy better than 5-7 cm.

An improved algorithm of mask image dodging for aerial image

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Zou, Songbai; Zuo, Zhiqi

2011-12-01

The technology of Mask image dodging based on Fourier transform is a good algorithm in removing the uneven luminance within a single image. At present, the difference method and the ratio method are the methods in common use, but they both have their own defects .For example, the difference method can keep the brightness uniformity of the whole image, but it is deficient in local contrast; meanwhile the ratio method can work better in local contrast, but sometimes it makes the dark areas of the original image too bright. In order to remove the defects of the two methods effectively, this paper on the basis of research of the two methods proposes a balance solution. Experiments show that the scheme not only can combine the advantages of the difference method and the ratio method, but also can avoid the deficiencies of the two algorithms.

Characterization of optical frequency transfer over 154  km of aerial fiber.

PubMed

Gozzard, David R; Schediwy, Sascha W; Wallace, Bruce; Gamatham, Romeo; Grainge, Keith

2017-06-01

We present measurements of the frequency transfer stability and analysis of the noise characteristics of an optical signal propagating over aerial suspended fiber links up to 153.6 km in length. The measured frequency transfer stability over these links is on the order of 10^-11 at an integration time of 1 s dropping to 10^-12 for integration times longer than 100 s. We show that wind-loading of the cable spans is the dominant source of short-timescale noise on the fiber links. We also report an attempt to stabilize the optical frequency transfer over these aerial links.

Preliminary Design of Aerial Spraying System for Microlight Aircraft

NASA Astrophysics Data System (ADS)

Omar, Zamri; Idris, Nurfazliawati; Rahim, M. Zulafif

2017-10-01

Undoubtedly agricultural is an important sector because it provides essential nutrients for human, and consequently is among the biggest sector for economic growth worldwide. It is crucial to ensure crops production is protected from any plant diseases and pests. Thus aerial spraying system on crops is developed to facilitate farmers to for crops pests control and it is very effective spraying method especially for large and hilly crop areas. However, the use of large aircraft for aerial spaying has a relatively high operational cost. Therefore, microlight aircraft is proposed to be used for crops aerial spraying works for several good reasons. In this paper, a preliminary design of aerial spraying system for microlight aircraft is proposed. Engineering design methodology is adopted in the development of the aerial sprayer and steps involved design are discussed thoroughly. A preliminary design for the microlight to be attached with an aerial spraying system is proposed.

Aerial Measuring System (AMS)/Israel Atomic Energy Commission (IAEC) Joint Comparison Study Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wasiolek, P.; Halevy, I.

Under the 13th Bilateral Meeting to Combat Nuclear Terrorism conducted on January 8–9, 2013, the committee approved the development of a cost-effective proposal to conduct a Comparison Study of the Aerial Measuring System (AMS) of the U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA) and Israel Atomic Energy Commission (IAEC). The study was to be held at the Remote Sensing Laboratory (RSL), Nellis Air Force Base, Las Vegas, Nevada, with measurements at the Nevada National Security Site (NNSS). The goal of the AMS and the IAEC joint survey was to compare the responses of the two agencies’ aerialmore » radiation detection systems to varied radioactive surface contamination levels and isotopic composition experienced at the NNSS, and the differing data processing techniques utilized by the respective teams. Considering that for the comparison both teams were using custom designed and built systems, the main focus of the short campaign was to investigate the impact of the detector size and data analysis techniques used by both teams. The AMS system, SPectral Advanced Radiological Computer System, Model A (SPARCS-A), designed and built by RSL, incorporates four different size sodium iodide (NaI) crystals: 1" × 1", 2" × 4" × 4", 2" × 4" ×16", and an “up-looking” 2" × 4" × 4". The Israel AMS System, Air RAM 2000, was designed by the IAEC Nuclear Research Center – Negev (NRCN) and built commercially by ROTEM Industries (Israel) and incorporates two 2" diameter × 2" long NaI crystals. The operational comparison was conducted at RSL-Nellis in Las Vegas, Nevada, during week of June 24–27, 2013. The Israeli system, Air RAM 2000, was shipped to RSL-Nellis and mounted together with the DOE SPARCS on a DOE Bell-412 helicopter for a series of aerial comparison measurements at local test ranges, including the Desert Rock Airport and Area 3 at the NNSS. A 4-person Israeli team from the IAEC NRCN supported the activity together

The Kilauea 1974 Flow: Quantitative Morphometry of Lava Flows using Low Altitude Aerial Image Data using a Kite-based Platform in the Field

NASA Astrophysics Data System (ADS)

Scheidt, S. P.; Whelley, P.; Hamilton, C.; Bleacher, J. E.; Garry, W. B.

2015-12-01

The December 31, 1974 lava flow from Kilauea Caldera, Hawaii within the Hawaii Volcanoes National Park was selected for field campaigns as a terrestrial analog for Mars in support of NASA Planetary Geology and Geophysics (PGG) research and the Remote, In Situ and Synchrotron Studies for Science and Exploration (RIS4E) node of the Solar System Exploration Research Virtual Institute (SSERVI) program). The lava flow was a rapidly emplaced unit that was strongly influenced by existing topography, which favored the formation of a tributary lava flow system. The unit includes a diverse range of surface textures (e.g., pāhoehoe, ´áā, and transitional lavas), and structural features (e.g., streamlined islands, pits, and interactions with older tumuli). However, these features are generally below the threshold of visibility within previously acquired airborne and spacecraft data. In this study, we have generated unique, high-resolution digital images using low-altitude Kite Aerial Photography (KAP) system during field campaigns in 2014 and 2015 (National Park Service permit #HAVO-2012-SCI-0025). The kite-based mapping platform (nadir-viewing) and a radio-controlled gimbal (allowing pointing) provided similar data as from an unmanned aerial vehicle (UAV), but with longer flight time, larger total data volumes per sortie, and fewer regulatory challenges and cost. Images acquired from KAP and UAVs are used to create orthomosaics and DEMs using Multi-View Stereo-Photogrammetry (MVSP) software. The 3-Dimensional point clouds are extremely dense, resulting in a grid resolution of < 2 cm. Airborne Light Detection and Ranging (LiDAR) / Terrestrial Laser Scanning (TLS) data have been collected for these areas and provide a basis of comparison or "ground truth" for the photogrammetric data. Our results show a good comparison with LiDAR/TLS data, each offering their own unique advantages and potential for data fusion.

“Comprehensive emission measurements from prescribed burning in Florida: field and laboratory, aerial and ground”

EPA Science Inventory

Simultaneous aerial- and ground-based emission sampling was conducted during prescribed burns at Eglin Air Force Base in November 2012 on a short grass/shrub field and a pine forest. Cumulative emission samples for volatile organic comounds, elemental carbon, organic carbon, ch...

Configuration and specifications of an Unmanned Aerial Vehicle (UAV) for early site specific weed management.

PubMed

Torres-Sánchez, Jorge; López-Granados, Francisca; De Castro, Ana Isabel; Peña-Barragán, José Manuel

2013-01-01

A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site- specific weed management (ESSWM). Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m) were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1) mission planning, 2) UAV flight and image acquisition, and 3) image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index), mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches).

Configuration and Specifications of an Unmanned Aerial Vehicle (UAV) for Early Site Specific Weed Management

PubMed Central

Torres-Sánchez, Jorge; López-Granados, Francisca; De Castro, Ana Isabel; Peña-Barragán, José Manuel

2013-01-01

A new aerial platform has risen recently for image acquisition, the Unmanned Aerial Vehicle (UAV). This article describes the technical specifications and configuration of a UAV used to capture remote images for early season site- specific weed management (ESSWM). Image spatial and spectral properties required for weed seedling discrimination were also evaluated. Two different sensors, a still visible camera and a six-band multispectral camera, and three flight altitudes (30, 60 and 100 m) were tested over a naturally infested sunflower field. The main phases of the UAV workflow were the following: 1) mission planning, 2) UAV flight and image acquisition, and 3) image pre-processing. Three different aspects were needed to plan the route: flight area, camera specifications and UAV tasks. The pre-processing phase included the correct alignment of the six bands of the multispectral imagery and the orthorectification and mosaicking of the individual images captured in each flight. The image pixel size, area covered by each image and flight timing were very sensitive to flight altitude. At a lower altitude, the UAV captured images of finer spatial resolution, although the number of images needed to cover the whole field may be a limiting factor due to the energy required for a greater flight length and computational requirements for the further mosaicking process. Spectral differences between weeds, crop and bare soil were significant in the vegetation indices studied (Excess Green Index, Normalised Green-Red Difference Index and Normalised Difference Vegetation Index), mainly at a 30 m altitude. However, greater spectral separability was obtained between vegetation and bare soil with the index NDVI. These results suggest that an agreement among spectral and spatial resolutions is needed to optimise the flight mission according to every agronomical objective as affected by the size of the smaller object to be discriminated (weed plants or weed patches). PMID:23483997

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) and its operations from an unmanned aerial vehicle (UAV) during the AROMAT campaign

NASA Astrophysics Data System (ADS)

Merlaud, Alexis; Tack, Frederik; Constantin, Daniel; Georgescu, Lucian; Maes, Jeroen; Fayt, Caroline; Mingireanu, Florin; Schuettemeyer, Dirk; Meier, Andreas Carlos; Schönardt, Anja; Ruhtz, Thomas; Bellegante, Livio; Nicolae, Doina; Den Hoed, Mirjam; Allaart, Marc; Van Roozendael, Michel

2018-01-01

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is a compact remote sensing instrument dedicated to mapping trace gases from an unmanned aerial vehicle (UAV). SWING is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27 cm × 12 cm × 8 cm, and 6 W. SWING was developed in parallel with a 2.5 m flying-wing UAV. This unmanned aircraft is electrically powered, has a typical airspeed of 100 km h-1, and can operate at a maximum altitude of 3 km. We present SWING-UAV experiments performed in Romania on 11 September 2014 during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign, which was dedicated to test newly developed instruments in the context of air quality satellite validation. The UAV was operated up to 700 m above ground, in the vicinity of the large power plant of Turceni (44.67° N, 23.41° E; 116 m a. s. l. ). These SWING-UAV flights were coincident with another airborne experiment using the Airborne imaging differential optical absorption spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP), and with ground-based DOAS, lidar, and balloon-borne in situ observations. The spectra recorded during the SWING-UAV flights are analysed with the DOAS technique. This analysis reveals NO2 differential slant column densities (DSCDs) up to 13±0.6×1016 molec cm-2. These NO2 DSCDs are converted to vertical column densities (VCDs) by estimating air mass factors. The resulting NO2 VCDs are up to 4.7±0.4×1016 molec cm-2. The water vapour DSCD measurements, up to 8±0.15×1022 molec cm-2, are used to estimate a volume mixing ratio of water vapour in the boundary layer of 0.013±0.002 mol mol-1. These geophysical quantities are validated with the coincident measurements.

Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing

NASA Technical Reports Server (NTRS)

Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.

2012-01-01

As imagery is collected from an airborne platform, an individual viewing the images wants to know from where on the Earth the images were collected. To do this, some information about the camera needs to be known, such as its position and orientation relative to the Earth. This can be provided by common inertial navigation systems (INS). Once the location of the camera is known, it is useful to project an image onto some representation of the Earth. Due to the non-smooth terrain of the Earth (mountains, valleys, etc.), this projection is highly non-linear. Thus, to ensure accurate projection, one needs to project onto a digital elevation map (DEM). This allows one to view the images overlaid onto a representation of the Earth. A code has been developed that takes an image, a model of the camera used to acquire that image, the pose of the camera during acquisition (as provided by an INS), and a DEM, and outputs an image that has been geo-rectified. The world coordinate of the bounds of the image are provided for viewing purposes. The code finds a mapping from points on the ground (DEM) to pixels in the image. By performing this process for all points on the ground, one can "paint" the ground with the image, effectively performing a projection of the image onto the ground. In order to make this process efficient, a method was developed for finding a region of interest (ROI) on the ground to where the image will project. This code is useful in any scenario involving an aerial imaging platform that moves and rotates over time. Many other applications are possible in processing aerial and satellite imagery.

Collection and Analysis of Crowd Data with Aerial, Rooftop, and Ground Views

DTIC Science & Technology

2014-11-10

collected these datasets using different aircrafts. Erista 8 HL OctaCopter is a heavy-lift aerial platform capable of using high-resolution cinema ...is another high-resolution camera that is cinema grade and high quality, with the capability of capturing videos with 4K resolution at 30 frames per...292.58 Imaging Systems and Accessories Blackmagic Production Camera 4 Crowd Counting using 4K Cameras High resolution cinema grade digital video

mapKITE: a New Paradigm for Simultaneous Aerial and Terrestrial Geodata Acquisition and Mapping

NASA Astrophysics Data System (ADS)

Molina, P.; Blázquez, M.; Sastre, J.; Colomina, I.

2016-06-01

We introduce a new mobile, simultaneous terrestrial and aerial, geodata collection and post-processing method: mapKITE. By combining two mapping technologies such as terrestrial mobile mapping and unmanned aircraft aerial mapping, geodata are simultaneously acquired from air and ground. More in detail, a mapKITE geodata acquisition system consists on an unmanned aircraft and a terrestrial vehicle, which hosts the ground control station. By means of a real-time navigation system on the terrestrial vehicle, real-time waypoints are sent to the aircraft from the ground. By doing so, the aircraft is linked to the terrestrial vehicle through a "virtual tether," acting as a "mapping kite." In the article, we entail the concept of mapKITE as well as the various technologies and techniques involved, from aircraft guidance and navigation based on IMU and GNSS, optical cameras for mapping and tracking, sensor orientation and calibration, etc. Moreover, we report of a new measurement introduced in mapKITE, that is, point-and-scale photogrammetric measurements [of image coordinates and scale] for optical targets of known size installed on the ground vehicle roof. By means of accurate posteriori trajectory determination of the terrestrial vehicle, mapKITE benefits then from kinematic ground control points which are photogrametrically observed by point-and-scale measures. Initial results for simulated configurations show that these measurements added to the usual Integrated Sensor Orientation ones reduce or even eliminate the need of conventional ground control points -therefore, lowering mission costs- and enable selfcalibration of the unmanned aircraft interior orientation parameters in corridor configurations, in contrast to the situation of traditional corridor configurations. Finally, we report about current developments of the first mapKITE prototype, developed under the European Union Research and Innovation programme Horizon 2020. The first mapKITE mission will be held at

Using aerial photography to estimate wood suitable for charcoal in managed oak forests

NASA Astrophysics Data System (ADS)

Ramírez-Mejía, D.; Gómez-Tagle, A.; Ghilardi, A.

2018-02-01

Mexican oak forests (genus Quercus) are frequently used for traditional charcoal production. Appropriate management programs are needed to ensure their long-term use, while conserving the biodiversity and ecosystem services, and associated benefits. A key variable needed to design these programs is the spatial distribution of standing woody biomass. A state-of-the-art methodology using small format aerial photographs was developed to estimate the total aboveground biomass (AGB) and aboveground woody biomass suitable for charcoal making (WSC) in intensively managed oak forests. We used tree crown area (CAap) measurements from very high-resolution (30 cm) orthorectified small format digital aerial photographs as the predictive variable. The CAap accuracy was validated using field measurements of the crown area (CAf). Allometric relationships between: (a) CAap versus AGB, and (b) CAap versus WSC had a high significance level (R 2 > 0.91, p < 0.0001). This approach shows that it is possible to obtain sound biomass estimates as a function of the crown area derived from digital small format aerial photographs.

An Adaptive Altitude Information Fusion Method for Autonomous Landing Processes of Small Unmanned Aerial Rotorcraft

PubMed Central

Lei, Xusheng; Li, Jingjing

2012-01-01

This paper presents an adaptive information fusion method to improve the accuracy and reliability of the altitude measurement information for small unmanned aerial rotorcraft during the landing process. Focusing on the low measurement performance of sensors mounted on small unmanned aerial rotorcraft, a wavelet filter is applied as a pre-filter to attenuate the high frequency noises in the sensor output. Furthermore, to improve altitude information, an adaptive extended Kalman filter based on a maximum a posteriori criterion is proposed to estimate measurement noise covariance matrix in real time. Finally, the effectiveness of the proposed method is proved by static tests, hovering flight and autonomous landing flight tests. PMID:23201993

An Evaluation of the Method of Determining Parallax from Measured Phase Differences.

DTIC Science & Technology

1977-12-01

5bOOé ~ETL—0 145 . ; ‘ , ~ ~“ (L2~I_ _ _ _~l: !~~~flI~~~ I— — — — — _ — — An evaluation of the method of determining parallax from measured phase...using a digi tized aerial image. The method was found to be not as accurate ~nd not as efficier,as conventiona l image ma tching techniques...EVALUATION OF THE METHOD OF DETERMINING PARALLAX FROM MEASURED PHASE DWFERENCES INTRODUCTION The purpose of the report is to describe an evaluation of

Extracting leaf area index using viewing geometry effects-A new perspective on high-resolution unmanned aerial system photography

NASA Astrophysics Data System (ADS)

Roth, Lukas; Aasen, Helge; Walter, Achim; Liebisch, Frank

2018-07-01

Extraction of leaf area index (LAI) is an important prerequisite in numerous studies related to plant ecology, physiology and breeding. LAI is indicative for the performance of a plant canopy and of its potential for growth and yield. In this study, a novel method to estimate LAI based on RGB images taken by an unmanned aerial system (UAS) is introduced. Soybean was taken as the model crop of investigation. The method integrates viewing geometry information in an approach related to gap fraction theory. A 3-D simulation of virtual canopies helped developing and verifying the underlying model. In addition, the method includes techniques to extract plot based data from individual oblique images using image projection, as well as image segmentation applying an active learning approach. Data from a soybean field experiment were used to validate the method. The thereby measured LAI prediction accuracy was comparable with the one of a gap fraction-based handheld device (R2 of 0.92 , RMSE of 0.42 m 2m-2) and correlated well with destructive LAI measurements (R2 of 0.89 , RMSE of 0.41 m2 m-2). These results indicate that, if respecting the range (LAI ≤ 3) the method was tested for, extracting LAI from UAS derived RGB images using viewing geometry information represents a valid alternative to destructive and optical handheld device LAI measurements in soybean. Thereby, we open the door for automated, high-throughput assessment of LAI in plant and crop science.

The sky is the limit? 20 years of small-format aerial photography taken from UAS for monitoring geomorphological processes

NASA Astrophysics Data System (ADS)

Marzolff, Irene

2014-05-01

One hundred years after the first publication on aerial photography taken from unmanned aerial platforms (Arthur Batut 1890), small-format aerial photography (SFAP) became a distinct niche within remote sensing during the 1990s. Geographers, plant biologists, archaeologists and other researchers with geospatial interests re-discovered the usefulness of unmanned platforms for taking high-resolution, low-altitude photographs that could then be digitized and analysed with geographical information systems, (softcopy) photogrammetry and image processing techniques originally developed for digital satellite imagery. Even before the ubiquity of digital consumer-grade cameras and 3D analysis software accessible to the photogrammetric layperson, do-it-yourself remote sensing using kites, blimps, drones and micro air vehicles literally enabled the questing researcher to get their own pictures of the world. As a flexible, cost-effective method, SFAP offered images with high spatial and temporal resolutions that could be ideally adapted to the scales of landscapes, forms and distribution patterns to be monitored. During the last five years, this development has been significantly accelerated by the rapid technological advancements of GPS navigation, autopiloting and revolutionary softcopy-photogrammetry techniques. State-of-the-art unmanned aerial systems (UAS) now allow automatic flight planning, autopilot-controlled aerial surveys, ground control-free direct georeferencing and DEM plus orthophoto generation with centimeter accuracy, all within the space of one day. The ease of use of current UAS and processing software for the generation of high-resolution topographic datasets and spectacular visualizations is tempting and has spurred the number of publications on these issues - but which advancements in our knowledge and understanding of geomorphological processes have we seen and can we expect in the future? This presentation traces the development of the last two decades

Construction of a small and lightweight hyperspectral imaging system

NASA Astrophysics Data System (ADS)

Vogel, Britta; Hünniger, Dirk; Bastian, Georg

2014-05-01

The analysis of the reflected sunlight offers great opportunity to gain information about the environment, including vegetation and soil. In the case of plants the wavelength ratio of the reflected light usually undergoes a change if the state of growth or state of health changes. So the measurement of the reflected light allows drawing conclusions about the state of, amongst others, vegetation. Using a hyperspectral imaging system for data acquisition leads to a large dataset, which can be evaluated with respect to several different questions to obtain various information by one measurement. Based on commercially available plain optical components we developed a small and lightweight hyperspectral imaging system within the INTERREG IV A-Project SMART INSPECTORS. The project SMART INSPECTORS [Smart Aerial Test Rigs with Infrared Spectrometers and Radar] deals with the fusion of airborne visible and infrared imaging remote sensing instruments and wireless sensor networks for precision agriculture and environmental research. A high performance camera was required in terms of good signal, good wavelength resolution and good spatial resolution, while severe constraints of size, proportions and mass had to be met due to the intended use on small unmanned aerial vehicles. The detector was chosen to operate without additional cooling. The refractive and focusing optical components were identified by supporting works with an optical raytracing software and a self-developed program. We present details of design and construction of our camera system, test results to confirm the optical simulation predictions as well as our first measurements.

Near real-time shadow detection and removal in aerial motion imagery application

NASA Astrophysics Data System (ADS)

Silva, Guilherme F.; Carneiro, Grace B.; Doth, Ricardo; Amaral, Leonardo A.; Azevedo, Dario F. G. de

2018-06-01

This work presents a method to automatically detect and remove shadows in urban aerial images and its application in an aerospace remote monitoring system requiring near real-time processing. Our detection method generates shadow masks and is accelerated by GPU programming. To obtain the shadow masks, we converted images from RGB to CIELCh model, calculated a modified Specthem ratio, and applied multilevel thresholding. Morphological operations were used to reduce shadow mask noise. The shadow masks are used in the process of removing shadows from the original images using the illumination ratio of the shadow/non-shadow regions. We obtained shadow detection accuracy of around 93% and shadow removal results comparable to the state-of-the-art while maintaining execution time under real-time constraints.

Autonomous Acquisition of Science Quality Spectra from Unmanned Aerial Systems

NASA Technical Reports Server (NTRS)

Mandl, Daniel; Campbell, Petya; Sohlberg, Robert; Cappelaere, Pat; Ong, Lawrence

2017-01-01

This is a presentation on a technique for using Unmanned Aerial Systems with intelligent sensing to create science quality data. In this particular case, the team used two spectrometers with high spectral resolution and developed a technique to have the spectrometers self calibrate so that it is possible to take the measurements within the allocated 10 minute flight times. Because there is both upwelling and downwelling foreoptics on each of the two spectrometers, it becomes slow to set the calibration up for all four possibilities which relates to the integration time and then take the measurements. If light conditions change too rapidly then the measurements won't be scaled so that the spectra max is at least 85% of the instrument max but not saturated. This process was more difficult then it appeared due to the complexity of determining the integration time before light conditions changed and before the battery runs our of charge to fly the Unmanned Aerial System. This presentation goes over the results for the first few flight days and the planned future flight experiments.

California sea lion (Zalophus californianus) aerial hearing sensitivity measured using auditory steady-state response and psychophysical methods.

PubMed

Mulsow, Jason; Finneran, James J; Houser, Dorian S

2011-04-01

Although electrophysiological methods of measuring the hearing sensitivity of pinnipeds are not yet as refined as those for dolphins and porpoises, they appear to be a promising supplement to traditional psychophysical procedures. In order to further standardize electrophysiological methods with pinnipeds, a within-subject comparison of psychophysical and auditory steady-state response (ASSR) measures of aerial hearing sensitivity was conducted with a 1.5-yr-old California sea lion. The psychophysical audiogram was similar to those previously reported for otariids, with a U-shape, and thresholds near 10 dB re 20 μPa at 8 and 16 kHz. ASSR thresholds measured using both single and multiple simultaneous amplitude-modulated tones closely reproduced the psychophysical audiogram, although the mean ASSR thresholds were elevated relative to psychophysical thresholds. Differences between psychophysical and ASSR thresholds were greatest at the low- and high-frequency ends of the audiogram. Thresholds measured using the multiple ASSR method were not different from those measured using the single ASSR method. The multiple ASSR method was more rapid than the single ASSR method, and allowed for threshold measurements at seven frequencies in less than 20 min. The multiple ASSR method may be especially advantageous for hearing sensitivity measurements with otariid subjects that are untrained for psychophysical procedures.

Employing unmanned aerial vehicle to monitor the health condition of wind turbines

NASA Astrophysics Data System (ADS)

Huang, Yishuo; Chiang, Chih-Hung; Hsu, Keng-Tsang; Cheng, Chia-Chi

2018-04-01

Unmanned aerial vehicle (UAV) can gather the spatial information of huge structures, such as wind turbines, that can be difficult to obtain with traditional approaches. In this paper, the UAV used in the experiments is equipped with high resolution camera and thermal infrared camera. The high resolution camera can provide a series of images with resolution up to 10 Megapixels. Those images can be used to form the 3D model using the digital photogrammetry technique. By comparing the 3D scenes of the same wind turbine at different times, possible displacement of the supporting tower of the wind turbine, caused by ground movement or foundation deterioration may be determined. The recorded thermal images are analyzed by applying the image segmentation methods to the surface temperature distribution. A series of sub-regions are separated by the differences of the surface temperature. The high-resolution optical image and the segmented thermal image are fused such that the surface anomalies are more easily identified for wind turbines.

Measuring laser reflection cross-sections of small unmanned aerial vehicles for laser detection, ranging and tracking

NASA Astrophysics Data System (ADS)

Laurenzis, Martin; Bacher, Emmanuel; Christnacher, Frank

2017-05-01

An increasing number of incidents are reported where small unmanned aerial vehicles (UAV) are involved flying at low altitude. Thus UAVs are becoming more and more a serious threat in civilian and military scenarios leading to serious danger to safety or privacy issues. In this context, the detection and tracking of small UAV flying at low altitude in urban environment or near background structures is a challenge for state of the art detection technologies. In this paper, we focus on detection, tracking and identification by laser sensing technologies that are Laser Gated Viewing and scanning LiDAR. The laser reflection cross-sections (LRCS) has direct impact on the probability to detection and capability for range measurement. Here, we present methods to determine the laser reflection cross-sections by experimental and computational approaches.

Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral Indices for Early-Growth Evaluation of Maize Performance under Phosphorus Fertilization

PubMed Central

Gracia-Romero, Adrian; Kefauver, Shawn C.; Vergara-Díaz, Omar; Zaman-Allah, Mainassara A.; Prasanna, Boddupalli M.; Cairns, Jill E.; Araus, José L.

2017-01-01

Low soil fertility is one of the factors most limiting agricultural production, with phosphorus deficiency being among the main factors, particularly in developing countries. To deal with such environmental constraints, remote sensing measurements can be used to rapidly assess crop performance and to phenotype a large number of plots in a rapid and cost-effective way. We evaluated the performance of a set of remote sensing indices derived from Red-Green-Blue (RGB) images and multispectral (visible and infrared) data as phenotypic traits and crop monitoring tools for early assessment of maize performance under phosphorus fertilization. Thus, a set of 26 maize hybrids grown under field conditions in Zimbabwe was assayed under contrasting phosphorus fertilization conditions. Remote sensing measurements were conducted in seedlings at two different levels: at the ground and from an aerial platform. Within a particular phosphorus level, some of the RGB indices strongly correlated with grain yield. In general, RGB indices assessed at both ground and aerial levels correlated in a comparable way with grain yield except for indices a* and u*, which correlated better when assessed at the aerial level than at ground level and Greener Area (GGA) which had the opposite correlation. The Normalized Difference Vegetation Index (NDVI) evaluated at ground level with an active sensor also correlated better with grain yield than the NDVI derived from the multispectral camera mounted in the aerial platform. Other multispectral indices like the Soil Adjusted Vegetation Index (SAVI) performed very similarly to NDVI assessed at the aerial level but overall, they correlated in a weaker manner with grain yield than the best RGB indices. This study clearly illustrates the advantage of RGB-derived indices over the more costly and time-consuming multispectral indices. Moreover, the indices best correlated with GY were in general those best correlated with leaf phosphorous content. However

Possibilities for Using LIDAR and Photogrammetric Data Obtained with AN Unmanned Aerial Vehicle for Levee Monitoring

NASA Astrophysics Data System (ADS)

Bakuła, K.; Ostrowski, W.; Szender, M.; Plutecki, W.; Salach, A.; Górski, K.

2016-06-01

This paper presents the possibilities for using an unmanned aerial system for evaluation of the condition of levees. The unmanned aerial system is equipped with two types of sensor. One is an ultra-light laser scanner, integrated with a GNSS receiver and an INS system; the other sensor is a digital camera that acquires data with stereoscopic coverage. Sensors have been mounted on the multirotor, unmanned platform the Hawk Moth, constructed by MSP company. LiDAR data and images of levees the length of several hundred metres were acquired during testing of the platform. Flights were performed in several variants. Control points measured with the use of the GNSS technique were considered as reference data. The obtained results are presented in this paper; the methodology of processing the acquired LiDAR data, which increase in accuracy when low accuracy of the navigation systems occurs as a result of systematic errors, is also discussed. The Iterative Closest Point (ICP) algorithm, as well as measurements of control points, were used to georeference the LiDAR data. Final accuracy in the order of centimetres was obtained for generation of the digital terrain model. The final products of the proposed UAV data processing are digital elevation models, an orthophotomap and colour point clouds. The authors conclude that such a platform offers wide possibilities for low-budget flights to deliver the data, which may compete with typical direct surveying measurements performed during monitoring of such objects. However, the biggest advantage is the density and continuity of data, which allows for detection of changes in objects being monitored.

Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning

NASA Astrophysics Data System (ADS)

Vetrivel, Anand; Gerke, Markus; Kerle, Norman; Nex, Francesco; Vosselman, George

2018-06-01

Oblique aerial images offer views of both building roofs and façades, and thus have been recognized as a potential source to detect severe building damages caused by destructive disaster events such as earthquakes. Therefore, they represent an important source of information for first responders or other stakeholders involved in the post-disaster response process. Several automated methods based on supervised learning have already been demonstrated for damage detection using oblique airborne images. However, they often do not generalize well when data from new unseen sites need to be processed, hampering their practical use. Reasons for this limitation include image and scene characteristics, though the most prominent one relates to the image features being used for training the classifier. Recently features based on deep learning approaches, such as convolutional neural networks (CNNs), have been shown to be more effective than conventional hand-crafted features, and have become the state-of-the-art in many domains, including remote sensing. Moreover, often oblique images are captured with high block overlap, facilitating the generation of dense 3D point clouds - an ideal source to derive geometric characteristics. We hypothesized that the use of CNN features, either independently or in combination with 3D point cloud features, would yield improved performance in damage detection. To this end we used CNN and 3D features, both independently and in combination, using images from manned and unmanned aerial platforms over several geographic locations that vary significantly in terms of image and scene characteristics. A multiple-kernel-learning framework, an effective way for integrating features from different modalities, was used for combining the two sets of features for classification. The results are encouraging: while CNN features produced an average classification accuracy of about 91%, the integration of 3D point cloud features led to an additional

An aerial radiological survey of the Evans Area, US Army Communications-Electronics Command, Fort Monmouth, New Jersey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maurer, R.J.

1989-12-01

An aerial radiological survey was conducted over the Evans Area, US Army Communications-Electronics Command, Fort Monmouth, New Jersey, during the period November 14--18, 1988. The purposes of the survey were to document the terrestrial gamma environment of the Evans site and surrounding area and to determine if there had been any radiological impact on the area due to past laboratory operations. The results of the aerial survey are reported as inferred radiation exposure rates at 1 meter above ground level in the form of a contour map. The aerial data were compared to ground-based benchmark'' exposure rate measurements and radionuclidemore » assay of soil samples obtained at sites outside the survey perimeter. Similar ground-based measurements were also made at several locations on the Evans site and at the bank of the Shark River bordering the Evans Area. No evidence for contamination was identified by either radionuclide assay of soil samples or the aerial survey. 6 refs., 5 figs., 2 tabs.« less

Combining LANDSAT MSS, aerial photographs and ground measurements to estimate rangeland productivity

NASA Technical Reports Server (NTRS)

Gialdini, M. J.

1981-01-01

The production of a vegetation map of over 2.2 million acres with detail down to the plant community level, and the production of estimates of rangeland productivity (pounds of usable forage per acre for cattle) for a 500,000 acre subset of area with a design goal for accuracy and precision of + or - 20% at the 80% confidence level, are considered. The data consist of five groups: maps of area, LANDSAT data, digital terrain data, large scale aerial photography, and ground plots. An outline of the data acquisition and data reduction schemes are presented.

Identification of irrigated crop types from ERTS-1 density contour maps and color infrared aerial photography. [Wyoming

NASA Technical Reports Server (NTRS)

Marrs, R. W.; Evans, M. A.

1974-01-01

The author has identified the following significant results. The crop types of a Great Plains study area were mapped from color infrared aerial photography. Each field was positively identified from field checks in the area. Enlarged (50x) density contour maps were constructed from three ERTS-1 images taken in the summer of 1973. The map interpreted from the aerial photography was compared to the density contour maps and the accuracy of the ERTS-1 density contour map interpretations were determined. Changes in the vegetation during the growing season and harvest periods were detectable on the ERTS-1 imagery. Density contouring aids in the detection of such charges.

Automatic mission planning algorithms for aerial collection of imaging-specific tasks

NASA Astrophysics Data System (ADS)

Sponagle, Paul; Salvaggio, Carl

2017-05-01

The rapid advancement and availability of small unmanned aircraft systems (sUAS) has led to many novel exploitation tasks utilizing that utilize this unique aerial imagery data. Collection of this unique data requires novel flight planning to accomplish the task at hand. This work describes novel flight planning to better support structure-from-motion missions to minimize occlusions, autonomous and periodic overflight of reflectance calibration panels to permit more efficient and accurate data collection under varying illumination conditions, and the collection of imagery data to study optical properties such as the bidirectional reflectance distribution function without disturbing the target in sensitive or remote areas of interest. These novel mission planning algorithms will provide scientists with additional tools to meet their future data collection needs.

Millimeter-wave imaging sensor data evaluation

NASA Technical Reports Server (NTRS)

Wilson, William J.; Ibbott, Anthony C.

1987-01-01

A passive 3-mm radiometer system with a mechanically scanned antenna was built for use on a small aircraft or an Unmanned Aerial Vehicle to produce real near-real-time, moderate-resolution (0.5) images of the ground. One of the main advantages of this passive imaging sensor is that it is able to provide surveillance information through dust, smoke, fog and clouds when visual and IR systems are unusable. It can also be used for a variety of remote sensing applications, such as measurements of surface moisture, surface temperature, vegetation extent and snow cover. It is also possible to detect reflective objects under vegetation cover.

Reliable aerial thermography for energy conservation

NASA Technical Reports Server (NTRS)

Jack, J. R.; Bowman, R. L.

1981-01-01

A method for energy conservation, the aerial thermography survey, is discussed. It locates sources of energy losses and wasteful energy management practices. An operational map is presented for clear sky conditions. The map outlines the key environmental conditions conductive to obtaining reliable aerial thermography. The map is developed from defined visual and heat loss discrimination criteria which are quantized based on flat roof heat transfer calculations.

Image Understanding Research and Its Application to Cartography and Computer-Based Analysis of Aerial Imagery

DTIC Science & Technology

1983-09-01

Report Al-TR-346. Artifcial Intelligence Laboratory, Mamachusetts Institute of Tech- niugy. Cambridge, Mmeh mett. June 19 [G.usmn@ A. Gaman-Arenas...Testbed Coordinator, 415/859-4395 Artificial Intelligence Center Computer Science and Technology Division Prepared for: Defense Advanced Research...to support processing of aerial photographs for such military applications as cartography, Intelligence , weapon guidance, and targeting. A key

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

Repeat, Low Altitude Measurements of Vegetation Status and Biomass Using Manned Aerial and UAS Imagery in a Piñon-Juniper Woodland

NASA Astrophysics Data System (ADS)

Krofcheck, D. J.; Lippitt, C.; Loerch, A.; Litvak, M. E.

2015-12-01

Measuring the above ground biomass of vegetation is a critical component of any ecological monitoring campaign. Traditionally, biomass of vegetation was measured with allometric-based approach. However, it is also time-consuming, labor-intensive, and extremely expensive to conduct over large scales and consequently is cost-prohibitive at the landscape scale. Furthermore, in semi-arid ecosystems characterized by vegetation with inconsistent growth morphologies (e.g., piñon-juniper woodlands), even ground-based conventional allometric approaches are often challenging to execute consistently across individuals and through time, increasing the difficulty of the required measurements and consequently the accuracy of the resulting products. To constrain the uncertainty associated with these campaigns, and to expand the extent of our measurement capability, we made repeat measurements of vegetation biomass in a semi-arid piñon-juniper woodland using structure-from-motion (SfM) techniques. We used high-spatial resolution overlapping aerial images and high-accuracy ground control points collected from both manned aircraft and multi-rotor UAS platforms, to generate digital surface model (DSM) for our experimental region. We extracted high-precision canopy volumes from the DSM and compared these to the vegetation allometric data, s to generate high precision canopy volume models. We used these models to predict the drivers of allometric equations for Pinus edulis and Juniperous monosperma (canopy height, diameter at breast height, and root collar diameter). Using this approach, we successfully accounted for the carbon stocks in standing live and standing dead vegetation across a 9 ha region, which contained 12.6 Mg / ha of standing dead biomass, with good agreement to our field plots. Here we present the initial results from an object oriented workflow which aims to automate the biomass estimation process of tree crown delineation and volume calculation, and partition

Monitoring and Estimation of Soil Losses from Ephemeral Gully Erosion in Mediterranean Region Using Low Altitude Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Gündoğan, R.; Alma, V.; Dindaroğlu, T.; Günal, H.; Yakupoğlu, T.; Susam, T.; Saltalı, K.

2017-11-01

Calculation of gullies by remote sensing images obtained from satellite or aerial platforms is often not possible because gullies in agricultural fields, defined as the temporary gullies are filled in a very short time with tillage operations. Therefore, fast and accurate estimation of sediment loss with the temporary gully erosion is of great importance. In this study, it is aimed to monitor and calculate soil losses caused by the gully erosion that occurs in agricultural areas with low altitude unmanned aerial vehicles. According to the calculation with Pix4D, gully volume was estimated to be 10.41 m3 and total loss of soil was estimated to be 14.47 Mg. The RMSE value of estimations was found to be 0.89. The results indicated that unmanned aerial vehicles could be used in predicting temporary gully erosion and losses of soil.

USGS Releases New Digital Aerial Products

USGS Publications Warehouse

,

2005-01-01

The U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) has initiated distribution of digital aerial photographic products produced by scanning or digitizing film from its historical aerial photography film archive. This archive, located in Sioux Falls, South Dakota, contains thousands of rolls of film that contain more than 8 million frames of historic aerial photographs. The largest portion of this archive consists of original film acquired by Federal agencies from the 1930s through the 1970s to produce 1:24,000-scale USGS topographic quadrangle maps. Most of this photography is reasonably large scale (USGS photography ranges from 1:8,000 to 1:80,000) to support the production of the maps. Two digital products are currently available for ordering: high-resolution scanned products and medium-resolution digitized products.

Measurements of the Temperature Structure-Function Parameters with a Small Unmanned Aerial System Compared with a Sodar

NASA Astrophysics Data System (ADS)

Bonin, Timothy A.; Goines, David C.; Scott, Aaron K.; Wainwright, Charlotte E.; Gibbs, Jeremy A.; Chilson, Phillip B.

2015-06-01

The structure function is often used to quantify the intensity of spatial inhomogeneities within turbulent flows. Here, the Small Multifunction Research and Teaching Sonde (SMARTSonde), an unmanned aerial system, is used to measure horizontal variations in temperature and to calculate the structure function of temperature at various heights for a range of separation distances. A method for correcting for the advection of turbulence in the calculation of the structure function is discussed. This advection correction improves the data quality, particularly when wind speeds are high. The temperature structure-function parameter can be calculated from the structure function of temperature. Two case studies from which the SMARTSonde was able to take measurements used to derive at several heights during multiple consecutive flights are discussed and compared with sodar measurements, from which is directly related to return power. Profiles of from both the sodar and SMARTSonde from an afternoon case exhibited generally good agreement. However, the profiles agreed poorly for a morning case. The discrepancies are partially attributed to different averaging times for the two instruments in a rapidly evolving environment, and the measurement errors associated with the SMARTSonde sampling within the stable boundary layer.

Infrared Surveys of Hawaiian Volcanoes: Aerial surveys with infrared imaging radiometer depict volcanic thermal patterns and structural features.

PubMed

Fisher, W A; Moxham, R M; Polcyn, F; Landis, G H

1964-11-06

Aerial infrared-sensor surveys of Kilauea volcano have depicted the areal extent and the relative intensity of abnormal thermal features in the caldera area of the volcano and along its associated rift zones. Many of these anomalies show correlation with visible steaming and reflect convective transfer of heat to the surface from subterranean sources. Structural details of the volcano, some not evident from surface observation, are also delineated by their thermal abnormalities. Several changes were observed in the patterns of infrared emission during the period of study; two such changes show correlation in location with subsequent eruptions, but the cause-and-effect relationship is uncertain. Thermal anomalies were also observed on the southwest flank of Mauna Loa; images of other volcanoes on the island of Hawaii, and of Haleakala on the island of Maui, revealed no thermal abnormalities. Approximately 25 large springs issuing into the ocean around the periphery of Hawaii have been detected. Infrared emission varies widely with surface texture and composition, suggesting that similar observations may have value for estimating surface conditions on the moon or planets.

Phase measurements of EUV mask defects

DOE PAGES

Claus, Rene A.; Wang, Yow-Gwo; Wojdyla, Antoine; ...

2015-02-22

Extreme Ultraviolet (EUV) Lithography mask defects were examined on the actinic mask imaging system, SHARP, at Lawrence Berkeley National Laboratory. Also, a quantitative phase retrieval algorithm based on the Weak Object Transfer Function was applied to the measured through-focus aerial images to examine the amplitude and phase of the defects. The accuracy of the algorithm was demonstrated by comparing the results of measurements using a phase contrast zone plate and a standard zone plate. Using partially coherent illumination to measure frequencies that would otherwise fall outside the numerical aperture (NA), it was shown that some defects are smaller than themore » conventional resolution of the microscope. We found that the programmed defects of various sizes were measured and shown to have both an amplitude and a phase component that the algorithm is able to recover.« less

Computer 3D site model generation based on aerial images

NASA Astrophysics Data System (ADS)

Zheltov, Sergey Y.; Blokhinov, Yuri B.; Stepanov, Alexander A.; Skryabin, Sergei V.; Sibiriakov, Alexandre V.

1997-07-01

The technology for 3D model design of real world scenes and its photorealistic rendering are current topics of investigation. Development of such technology is very attractive to implement in vast varieties of applications: military mission planning, crew training, civil engineering, architecture, virtual reality entertainments--just a few were mentioned. 3D photorealistic models of urban areas are often discussed now as upgrade from existing 2D geographic information systems. Possibility of site model generation with small details depends on two main factors: available source dataset and computer power resources. In this paper PC based technology is presented, so the scenes of middle resolution (scale of 1:1000) be constructed. Types of datasets are the gray level aerial stereo pairs of photographs (scale of 1:14000) and true color on ground photographs of buildings (scale ca.1:1000). True color terrestrial photographs are also necessary for photorealistic rendering, that in high extent improves human perception of the scene.

Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery.

PubMed

Casado, Monica Rivas; Gonzalez, Rocio Ballesteros; Kriechbaumer, Thomas; Veal, Amanda

2015-11-04

European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management.

Drogue tracking using 3D flash lidar for autonomous aerial refueling

NASA Astrophysics Data System (ADS)

Chen, Chao-I.; Stettner, Roger

2011-06-01

Autonomous aerial refueling (AAR) is an important capability for an unmanned aerial vehicle (UAV) to increase its flying range and endurance without increasing its size. This paper presents a novel tracking method that utilizes both 2D intensity and 3D point-cloud data acquired with a 3D Flash LIDAR sensor to establish relative position and orientation between the receiver vehicle and drogue during an aerial refueling process. Unlike classic, vision-based sensors, a 3D Flash LIDAR sensor can provide 3D point-cloud data in real time without motion blur, in the day or night, and is capable of imaging through fog and clouds. The proposed method segments out the drogue through 2D analysis and estimates the center of the drogue from 3D point-cloud data for flight trajectory determination. A level-set front propagation routine is first employed to identify the target of interest and establish its silhouette information. Sufficient domain knowledge, such as the size of the drogue and the expected operable distance, is integrated into our approach to quickly eliminate unlikely target candidates. A statistical analysis along with a random sample consensus (RANSAC) is performed on the target to reduce noise and estimate the center of the drogue after all 3D points on the drogue are identified. The estimated center and drogue silhouette serve as the seed points to efficiently locate the target in the next frame.

Method of orthogonally splitting imaging pose measurement

NASA Astrophysics Data System (ADS)

Zhao, Na; Sun, Changku; Wang, Peng; Yang, Qian; Liu, Xintong

2018-01-01

In order to meet the aviation's and machinery manufacturing's pose measurement need of high precision, fast speed and wide measurement range, and to resolve the contradiction between measurement range and resolution of vision sensor, this paper proposes an orthogonally splitting imaging pose measurement method. This paper designs and realizes an orthogonally splitting imaging vision sensor and establishes a pose measurement system. The vision sensor consists of one imaging lens, a beam splitter prism, cylindrical lenses and dual linear CCD. Dual linear CCD respectively acquire one dimensional image coordinate data of the target point, and two data can restore the two dimensional image coordinates of the target point. According to the characteristics of imaging system, this paper establishes the nonlinear distortion model to correct distortion. Based on cross ratio invariability, polynomial equation is established and solved by the least square fitting method. After completing distortion correction, this paper establishes the measurement mathematical model of vision sensor, and determines intrinsic parameters to calibrate. An array of feature points for calibration is built by placing a planar target in any different positions for a few times. An terative optimization method is presented to solve the parameters of model. The experimental results show that the field angle is 52 °, the focus distance is 27.40 mm, image resolution is 5185×5117 pixels, displacement measurement error is less than 0.1mm, and rotation angle measurement error is less than 0.15°. The method of orthogonally splitting imaging pose measurement can satisfy the pose measurement requirement of high precision, fast speed and wide measurement range.

Influence of Mechanical Properties of Aerial Shells made from Biodegradable Plastics on Smaller Fragmentation

NASA Astrophysics Data System (ADS)

Kudo, Makoto; Murata, Kenji; Kamata, Satoru; Hamada, Fumio

In this paper, a new aerial shell made of biodegradable plastics was developed and explosion tests were carried out using 2.5-10 gou-size firework aerial shells at a ground test site in order to observe the fragmentation. The dispersed fragments were then collected and their size and distribution measured. In order to monitor the fragmentation visually, a high-speed camera was used to film the ignition of the bursting charge and the scattering of the shell fragments. The shell fragments became much smaller, because mechanical properties of biodegradable plastics that were added improved polyvinyl alcohol (PVA) and chaff powder (CP). Fibrillation was seen in PBS/PVA/CP, and it seemed effective for mechanical properties. As a result, safer aerial shells which disperse into smaller fragments on explosion were successfully developed.

BOREAS Level-0 ER-2 Aerial Photography

NASA Technical Reports Server (NTRS)

Newcomer, Jeffrey A.; Dominquez, Roseanne; Hall, Forrest G. (Editor)

2000-01-01

For BOReal Ecosystem-Atmosphere Study (BOREAS), the ER-2 and other aerial photography was collected to provide finely detailed and spatially extensive documentation of the condition of the primary study sites. The ER-2 aerial photography consists of color-IR transparencies collected during flights in 1994 and 1996 over the study areas.

7 CFR 1755.703 - Nonmetallic reinforced (NMR) aerial service wire.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Nonmetallic reinforced (NMR) aerial service wire... MATERIALS, AND STANDARD CONTRACT FORMS § 1755.703 Nonmetallic reinforced (NMR) aerial service wire. (a... resistance of each conductor in a completed NMR aerial service wire shall comply with the requirement...

7 CFR 1755.703 - Nonmetallic reinforced (NMR) aerial service wire.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Nonmetallic reinforced (NMR) aerial service wire... MATERIALS, AND STANDARD CONTRACT FORMS § 1755.703 Nonmetallic reinforced (NMR) aerial service wire. (a... resistance of each conductor in a completed NMR aerial service wire shall comply with the requirement...

7 CFR 1755.703 - Nonmetallic reinforced (NMR) aerial service wire.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Nonmetallic reinforced (NMR) aerial service wire... MATERIALS, AND STANDARD CONTRACT FORMS § 1755.703 Nonmetallic reinforced (NMR) aerial service wire. (a... resistance of each conductor in a completed NMR aerial service wire shall comply with the requirement...

Multiple vehicle tracking in aerial video sequence using driver behavior analysis and improved deterministic data association

NASA Astrophysics Data System (ADS)

Zhang, Xunxun; Xu, Hongke; Fang, Jianwu

2018-01-01

Along with the rapid development of the unmanned aerial vehicle technology, multiple vehicle tracking (MVT) in aerial video sequence has received widespread interest for providing the required traffic information. Due to the camera motion and complex background, MVT in aerial video sequence poses unique challenges. We propose an efficient MVT algorithm via driver behavior-based Kalman filter (DBKF) and an improved deterministic data association (IDDA) method. First, a hierarchical image registration method is put forward to compensate the camera motion. Afterward, to improve the accuracy of the state estimation, we propose the DBKF module by incorporating the driver behavior into the Kalman filter, where artificial potential field is introduced to reflect the driver behavior. Then, to implement the data association, a local optimization method is designed instead of global optimization. By introducing the adaptive operating strategy, the proposed IDDA method can also deal with the situation in which the vehicles suddenly appear or disappear. Finally, comprehensive experiments on the DARPA VIVID data set and KIT AIS data set demonstrate that the proposed algorithm can generate satisfactory and superior results.

Off-the-Wall Project Brings Aerial Mapping down to Earth

ERIC Educational Resources Information Center

Davidhazy, Andrew

2008-01-01

The technology of aerial photography, photogrametry, has widespread applications in mapping and aerial surveying. A multi-billion-dollar industry, aerial surveying and mapping is "big business" in both civilian and military sectors. While the industry has grown increasingly automated, employment opportunities still exist for people with a basic…

Knowledge-based understanding of aerial surveillance video

NASA Astrophysics Data System (ADS)

Cheng, Hui; Butler, Darren

2006-05-01

Aerial surveillance has long been used by the military to locate, monitor and track the enemy. Recently, its scope has expanded to include law enforcement activities, disaster management and commercial applications. With the ever-growing amount of aerial surveillance video acquired daily, there is an urgent need for extracting actionable intelligence in a timely manner. Furthermore, to support high-level video understanding, this analysis needs to go beyond current approaches and consider the relationships, motivations and intentions of the objects in the scene. In this paper we propose a system for interpreting aerial surveillance videos that automatically generates a succinct but meaningful description of the observed regions, objects and events. For a given video, the semantics of important regions and objects, and the relationships between them, are summarised into a semantic concept graph. From this, a textual description is derived that provides new search and indexing options for aerial video and enables the fusion of aerial video with other information modalities, such as human intelligence, reports and signal intelligence. Using a Mixture-of-Experts video segmentation algorithm an aerial video is first decomposed into regions and objects with predefined semantic meanings. The objects are then tracked and coerced into a semantic concept graph and the graph is summarized spatially, temporally and semantically using ontology guided sub-graph matching and re-writing. The system exploits domain specific knowledge and uses a reasoning engine to verify and correct the classes, identities and semantic relationships between the objects. This approach is advantageous because misclassifications lead to knowledge contradictions and hence they can be easily detected and intelligently corrected. In addition, the graph representation highlights events and anomalies that a low-level analysis would overlook.

DoD Comprehensive Military Unmanned Aerial Vehicle Smart Device Ground Control Station Threat Model

DTIC Science & Technology

2015-04-01

design , imple- mentation, and test evaluation were interviewed to evaluate the existing gaps in the DoD processes for cybersecurity. This group exposed...such as antenna design and signal reception have made satellite communication networks a viable solution for smart devices on the battlefield...DoD Comprehensive Military Unmanned AERIAL VEHICLE SMART DEVICE GROUND CONTROL STATION THREAT MODEL  Image designed by Diane Fleischer Report

Experimental and rendering-based investigation of laser radar cross sections of small unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Laurenzis, Martin; Bacher, Emmanuel; Christnacher, Frank

2017-12-01

Laser imaging systems are prominent candidates for detection and tracking of small unmanned aerial vehicles (UAVs) in current and future security scenarios. Laser reflection characteristics for laser imaging (e.g., laser gated viewing) of small UAVs are investigated to determine their laser radar cross section (LRCS) by analyzing the intensity distribution of laser reflection in high resolution images. For the first time, LRCSs are determined in a combined experimental and computational approaches by high resolution laser gated viewing and three-dimensional rendering. An optimized simple surface model is calculated taking into account diffuse and specular reflectance properties based on the Oren-Nayar and the Cook-Torrance reflectance models, respectively.

Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

NASA Astrophysics Data System (ADS)

Osipov, Gennady

2013-04-01

includes noncontact registration of eye motion, reconstruction of "attention landscape" fixed by the expert, recording the comments of the expert who is a specialist in the field of images` interpretation, and transfer this information into knowledge base.Creation of base of ophthalmologic images (OI) includes making semantic contacts from great number of OI based on analysis of OI and expert's comments.Processing of OI and making generalized OI (GOI) is realized by inductive logic algorithms and consists in synthesis of structural invariants of OI. The mode of recognition and interpretation of unknown images consists of several stages, which include: comparison of unknown image with the base of structural invariants of OI; revealing of structural invariants in unknown images; ynthesis of interpretive message of the structural invariants base and OI base (the experts` comments stored in it). We want to emphasize that the training mode does not assume special involvement of experts to teach the system - it is realized in the process of regular experts` work on image interpretation and it becomes possible after installation of a special apparatus for non contact registration of experts` attention. Consequently, the technology, which principles is described there, provides fundamentally new effective solution to the problem of exploration of mineral resource deposits based on computer analysis of aerial and satellite image data.

7 CFR 1755.703 - Nonmetallic reinforced (NMR) aerial service wire.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Nonmetallic reinforced (NMR) aerial service wire... MATERIALS, AND STANDARD CONTRACT FORMS § 1755.703 Nonmetallic reinforced (NMR) aerial service wire. (a..., paragraphs 2.2 and 2.2.1. The ANSI/ICEA S-89-648-1993 Standard For Telecommunications Aerial Service Wire...

7 CFR 1755.703 - Nonmetallic reinforced (NMR) aerial service wire.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Nonmetallic reinforced (NMR) aerial service wire... MATERIALS, AND STANDARD CONTRACT FORMS § 1755.703 Nonmetallic reinforced (NMR) aerial service wire. (a..., paragraphs 2.2 and 2.2.1. The ANSI/ICEA S-89-648-1993 Standard For Telecommunications Aerial Service Wire...

7 CFR 1755.700 - RUS specification for aerial service wires.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false RUS specification for aerial service wires. 1755.700..., AND STANDARD CONTRACT FORMS § 1755.700 RUS specification for aerial service wires. §§ 1755.701 through 1755.704 cover the requirements for aerial service wires. [61 FR 26074, May 24, 1996] ...

7 CFR 1755.700 - RUS specification for aerial service wires.