Science.gov

Sample records for aerial imagery analysis

  1. Analysis of aerial multispectral imagery to assess water quality parameters of Mississippi water bodies

    NASA Astrophysics Data System (ADS)

    Irvin, Shane Adison

    The goal of this study was to demonstrate the application of aerial imagery as a tool in detecting water quality indicators in a three mile segment of Tibbee Creek in, Clay County, Mississippi. Water samples from 10 transects were collected per sampling date over two periods in 2010 and 2011. Temperature and dissolved oxygen (DO) were measured at each point, and water samples were tested for turbidity and total suspended solids (TSS). Relative reflectance was extracted from high resolution (0.5 meter) multispectral aerial images. A regression model was developed for turbidity and TSS as a function of values for specific sampling dates. The best model was used to predict turbidity and TSS using datasets outside the original model date. The development of an appropriate predictive model for water quality assessment based on the relative reflectance of aerial imagery is affected by the quality of imagery and time of sampling.

  2. 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.

  3. 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.

  4. Identification of wild areas in southern lower Michigan. [terrain analysis from aerial photography, and satellite imagery

    NASA Technical Reports Server (NTRS)

    Habowski, S.; Cialek, C.

    1978-01-01

    An inventory methodology was developed to identify potential wild area sites. A list of site criteria were formulated and tested in six selected counties. Potential sites were initially identified from LANDSAT satellite imagery. A detailed study of the soil, vegetation and relief characteristics of each site based on both high-altitude aerial photographs and existing map data was conducted to eliminate unsuitable sites. Ground reconnaissance of the remaining wild areas was made to verify suitability and acquire information on wildlife and general aesthetics. Physical characteristics of the wild areas in each county are presented in tables. Maps show the potential sites to be set aside for natural preservation and regulation by the state under the Wilderness and Natural Areas Act of 1972.

  5. Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery

    USGS Publications Warehouse

    Enwright, Nicholas M.; Jones, William R.; Garber, Adrienne L.; Keller, Matthew J.

    2014-01-01

    Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less). This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m2). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.

  6. Radiometric and geometric analysis of hyperspectral imagery acquired from an unmanned aerial vehicle

    SciTech Connect

    Hruska, Ryan; Mitchell, Jessica; Anderson, Matthew; Glenn, Nancy F.

    2012-09-17

    During the summer of 2010, an Unmanned Aerial Vehicle (UAV) hyperspectral in-flight calibration and characterization experiment of the Resonon PIKA II imaging spectrometer was conducted at the U.S. Department of Energy’s Idaho National Laboratory (INL) UAV Research Park. The purpose of the experiment was to validate the radiometric calibration of the spectrometer and determine the georegistration accuracy achievable from the on-board global positioning system (GPS) and inertial navigation sensors (INS) under operational conditions. In order for low-cost hyperspectral systems to compete with larger systems flown on manned aircraft, they must be able to collect data suitable for quantitative scientific analysis. The results of the in-flight calibration experiment indicate an absolute average agreement of 96.3%, 93.7% and 85.7% for calibration tarps of 56%, 24%, and 2.5% reflectivity, respectively. The achieved planimetric accuracy was 4.6 meters (based on RMSE).

  7. COCOA: tracking in aerial imagery

    NASA Astrophysics Data System (ADS)

    Ali, Saad; Shah, Mubarak

    2006-05-01

    Unmanned Aerial Vehicles (UAVs) are becoming a core intelligence asset for reconnaissance, surveillance and target tracking in urban and battlefield settings. In order to achieve the goal of automated tracking of objects in UAV videos we have developed a system called COCOA. It processes the video stream through number of stages. At first stage platform motion compensation is performed. Moving object detection is performed to detect the regions of interest from which object contours are extracted by performing a level set based segmentation. Finally blob based tracking is performed for each detected object. Global tracks are generated which are used for higher level processing. COCOA is customizable to different sensor resolutions and is capable of tracking targets as small as 100 pixels. It works seamlessly for both visible and thermal imaging modes. The system is implemented in Matlab and works in a batch mode.

  8. Radiometric and geometric analysis of hyperspectral imagery acquired from an unmanned aerial vehicle

    DOE PAGES

    Hruska, Ryan; Mitchell, Jessica; Anderson, Matthew; Glenn, Nancy F.

    2012-09-17

    During the summer of 2010, an Unmanned Aerial Vehicle (UAV) hyperspectral in-flight calibration and characterization experiment of the Resonon PIKA II imaging spectrometer was conducted at the U.S. Department of Energy’s Idaho National Laboratory (INL) UAV Research Park. The purpose of the experiment was to validate the radiometric calibration of the spectrometer and determine the georegistration accuracy achievable from the on-board global positioning system (GPS) and inertial navigation sensors (INS) under operational conditions. In order for low-cost hyperspectral systems to compete with larger systems flown on manned aircraft, they must be able to collect data suitable for quantitative scientific analysis.more » The results of the in-flight calibration experiment indicate an absolute average agreement of 96.3%, 93.7% and 85.7% for calibration tarps of 56%, 24%, and 2.5% reflectivity, respectively. The achieved planimetric accuracy was 4.6 meters (based on RMSE).« less

  9. Detection and spatiotemporal analysis of methane ebullition on thermokarst lake ice using high-resolution optical aerial imagery

    NASA Astrophysics Data System (ADS)

    Lindgren, P. R.; Grosse, G.; Anthony, K. M. Walter; Meyer, F. J.

    2016-01-01

    Thermokarst lakes are important emitters of methane, a potent greenhouse gas. However, accurate estimation of methane flux from thermokarst lakes is difficult due to their remoteness and observational challenges associated with the heterogeneous nature of ebullition. We used high-resolution (9-11 cm) snow-free aerial images of an interior Alaskan thermokarst lake acquired 2 and 4 days following freeze-up in 2011 and 2012, respectively, to detect and characterize methane ebullition seeps and to estimate whole-lake ebullition. Bubbles impeded by the lake ice sheet form distinct white patches as a function of bubbling when lake ice grows downward and around them, trapping the gas in the ice. Our aerial imagery thus captured a snapshot of bubbles trapped in lake ice during the ebullition events that occurred before the image acquisition. Image analysis showed that low-flux A- and B-type seeps are associated with low brightness patches and are statistically distinct from high-flux C-type and hotspot seeps associated with high brightness patches. Mean whole-lake ebullition based on optical image analysis in combination with bubble-trap flux measurements was estimated to be 174 ± 28 and 216 ± 33 mL gas m-2 d-1 for the years 2011 and 2012, respectively. A large number of seeps demonstrated spatiotemporal stability over our 2-year study period. A strong inverse exponential relationship (R2 > = 0.79) was found between the percent of the surface area of lake ice covered with bubble patches and distance from the active thermokarst lake margin. Even though the narrow timing of optical image acquisition is a critical factor, with respect to both atmospheric pressure changes and snow/no-snow conditions during early lake freeze-up, our study shows that optical remote sensing is a powerful tool to map ebullition seeps on lake ice, to identify their relative strength of ebullition, and to assess their spatiotemporal variability.

  10. Inlining 3d Reconstruction, Multi-Source Texture Mapping and Semantic Analysis Using Oblique Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Frommholz, D.; Linkiewicz, M.; Poznanska, A. M.

    2016-06-01

    This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for façade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the façades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM). The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM) of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA) tool running a custom rule set to identify windows on the contained façade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric constraints and

  11. Encoding and analyzing aerial imagery using geospatial semantic graphs

    SciTech Connect

    Watson, Jean-Paul; Strip, David R.; McLendon, William C.; Parekh, Ojas D.; Diegert, Carl F.; Martin, Shawn Bryan; Rintoul, Mark Daniel

    2014-02-01

    While collection capabilities have yielded an ever-increasing volume of aerial imagery, analytic techniques for identifying patterns in and extracting relevant information from this data have seriously lagged. The vast majority of imagery is never examined, due to a combination of the limited bandwidth of human analysts and limitations of existing analysis tools. In this report, we describe an alternative, novel approach to both encoding and analyzing aerial imagery, using the concept of a geospatial semantic graph. The advantages of our approach are twofold. First, intuitive templates can be easily specified in terms of the domain language in which an analyst converses. These templates can be used to automatically and efficiently search large graph databases, for specific patterns of interest. Second, unsupervised machine learning techniques can be applied to automatically identify patterns in the graph databases, exposing recurring motifs in imagery. We illustrate our approach using real-world data for Anne Arundel County, Maryland, and compare the performance of our approach to that of an expert human analyst.

  12. Building and road detection from large aerial imagery

    NASA Astrophysics Data System (ADS)

    Saito, Shunta; Aoki, Yoshimitsu

    2015-02-01

    Building and road detection from aerial imagery has many applications in a wide range of areas including urban design, real-estate management, and disaster relief. The extracting buildings and roads from aerial imagery has been performed by human experts manually, so that it has been very costly and time-consuming process. Our goal is to develop a system for automatically detecting buildings and roads directly from aerial imagery. Many attempts at automatic aerial imagery interpretation have been proposed in remote sensing literature, but much of early works use local features to classify each pixel or segment to an object label, so that these kind of approach needs some prior knowledge on object appearance or class-conditional distribution of pixel values. Furthermore, some works also need a segmentation step as pre-processing. Therefore, we use Convolutional Neural Networks(CNN) to learn mapping from raw pixel values in aerial imagery to three object labels (buildings, roads, and others), in other words, we generate three-channel maps from raw aerial imagery input. We take a patch-based semantic segmentation approach, so we firstly divide large aerial imagery into small patches and then train the CNN with those patches and corresponding three-channel map patches. Finally, we evaluate our system on a large-scale road and building detection datasets that is publicly available.

  13. Building population mapping with aerial imagery and GIS data

    NASA Astrophysics Data System (ADS)

    Ural, Serkan; Hussain, Ejaz; Shan, Jie

    2011-12-01

    Geospatial distribution of population at a scale of individual buildings is needed for analysis of people's interaction with their local socio-economic and physical environments. High resolution aerial images are capable of capturing urban complexities and considered as a potential source for mapping urban features at this fine scale. This paper studies population mapping for individual buildings by using aerial imagery and other geographic data. Building footprints and heights are first determined from aerial images, digital terrain and surface models. City zoning maps allow the classification of the buildings as residential and non-residential. The use of additional ancillary geographic data further filters residential utility buildings out of the residential area and identifies houses and apartments. In the final step, census block population, which is publicly available from the U.S. Census, is disaggregated and mapped to individual residential buildings. This paper proposes a modified building population mapping model that takes into account the effects of different types of residential buildings. Detailed steps are described that lead to the identification of residential buildings from imagery and other GIS data layers. Estimated building populations are evaluated per census block with reference to the known census records. This paper presents and evaluates the results of building population mapping in areas of West Lafayette, Lafayette, and Wea Township, all in the state of Indiana, USA.

  14. Data annotation of aerial reconnaissance imagery and exploitation

    NASA Astrophysics Data System (ADS)

    Wareberg, P. Gunnar; Prunes, V.; Scholes, Richard W.

    1995-09-01

    This paper reviews the use of LED recording head assemblies (RHAs) for film annotation in aerial reconnaissance cameras and discusses code matrix block readers (CMBRs). Annotation of video imagery is also covered.

  15. Texture mapping based on multiple aerial imageries in urban areas

    NASA Astrophysics Data System (ADS)

    Zhou, Guoqing; Ye, Siqi; Wang, Yuefeng; Han, Caiyun; Wang, Chenxi

    2015-12-01

    In the realistic 3D model reconstruction, the requirement of the texture is very high. Texture is one of the key factors that affecting realistic of the model and using texture mapping technology to realize. In this paper we present a practical approach of texture mapping based on photogrammetry theory from multiple aerial imageries in urban areas. By collinearity equation to matching the model and imageries, and in order to improving the quality of texture, we describe an automatic approach for select the optimal texture to realized 3D building from the aerial imageries of many strip. The texture of buildings can be automatically matching by the algorithm. The experimental results show that the platform of texture mapping process has a high degree of automation and improve the efficiency of the 3D modeling reconstruction.

  16. Acquisition and registration of aerial video imagery of urban traffic

    SciTech Connect

    Loveland, Rohan C

    2008-01-01

    The amount of information available about urban traffic from aerial video imagery is extremely high. Here we discuss the collection of such video imagery from a helicopter platform with a low-cost sensor, and the post-processing used to correct radial distortion in the data and register it. The radial distortion correction is accomplished using a Harris model. The registration is implemented in a two-step process, using a globally applied polyprojective correction model followed by a fine scale local displacement field adjustment. The resulting cleaned-up data is sufficiently well-registered to allow subsequent straight-forward vehicle tracking.

  17. An Automated Approach to Agricultural Tile Drain Detection and Extraction Utilizing High Resolution Aerial Imagery and Object-Based Image Analysis

    NASA Astrophysics Data System (ADS)

    Johansen, Richard A.

    Subsurface drainage from agricultural fields in the Maumee River watershed is suspected to adversely impact the water quality and contribute to the formation of harmful algal blooms (HABs) in Lake Erie. In early August of 2014, a HAB developed in the western Lake Erie Basin that resulted in over 400,000 people being unable to drink their tap water due to the presence of a toxin from the bloom. HAB development in Lake Erie is aided by excess nutrients from agricultural fields, which are transported through subsurface tile and enter the watershed. Compounding the issue within the Maumee watershed, the trend within the watershed has been to increase the installation of tile drains in both total extent and density. Due to the immense area of drained fields, there is a need to establish an accurate and effective technique to monitor subsurface farmland tile installations and their associated impacts. This thesis aimed at developing an automated method in order to identify subsurface tile locations from high resolution aerial imagery by applying an object-based image analysis (OBIA) approach utilizing eCognition. This process was accomplished through a set of algorithms and image filters, which segment and classify image objects by their spectral and geometric characteristics. The algorithms utilized were based on the relative location of image objects and pixels, in order to maximize the robustness and transferability of the final rule-set. These algorithms were coupled with convolution and histogram image filters to generate results for a 10km2 study area located within Clay Township in Ottawa County, Ohio. The eCognition results were compared to previously collected tile locations from an associated project that applied heads-up digitizing of aerial photography to map field tile. The heads-up digitized locations were used as a baseline for the accuracy assessment. The accuracy assessment generated a range of agreement values from 67.20% - 71.20%, and an average

  18. Oblique Aerial Imagery for NMA - Some best Practices

    NASA Astrophysics Data System (ADS)

    Remondino, F.; Toschi, I.; Gerke, M.; Nex, F.; Holland, D.; McGill, A.; Talaya Lopez, J.; Magarinos, A.

    2016-06-01

    Oblique airborne photogrammetry is rapidly maturing and being offered by service providers as a good alternative or replacement of the more traditional vertical imagery and for very different applications (Fig.1). EuroSDR, representing European National Mapping Agencies (NMAs) and research organizations of most EU states, is following the development of oblique aerial cameras since 2013, when an ongoing activity was created to continuously update its members on the developments in this technology. Nowadays most European NMAs still rely on the traditional workflow based on vertical photography but changes are slowly taking place also at production level. Some NMAs have already run some tests internally to understand the potential for their needs whereas other agencies are discussing on the future role of this technology and how to possibly adapt their production pipelines. At the same time, some research institutions and academia demonstrated the potentialities of oblique aerial datasets to generate textured 3D city models or large building block models. The paper provides an overview of tests, best practices and considerations coming from the R&D community and from three European NMAs concerning the use of oblique aerial imagery.

  19. Analysis of Biophysical Mechanisms of Gilgai Microrelief Formation in Dryland Swelling Soils Using Ultra-High Resolution Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Krell, N.; DeCarlo, K. F.; Caylor, K. K.

    2015-12-01

    Microrelief formations ("gilgai"), which form due to successive wetting-drying cycles typical of swelling soils, provide ecological hotspots for local fauna and flora, including higher and more robust vegetative growth. The distribution of these gilgai suggests a remarkable degree of regularity. However, it is unclear to what extent the mechanisms that drive gilgai formation are physical, such as desiccation-induced fracturing, or biological in nature, namely antecedent vegetative clustering. We investigated gilgai genesis and pattern formation in a 100 x 100 meter study area with swelling soils in a semiarid grassland at the Mpala Research Center in central Kenya. Our ongoing experiment is composed of three 9m2 treatments: we removed gilgai and limited vegetative growth by herbicide application in one plot, allowed for unrestricted seed dispersal in another, and left gilgai unobstructed in a control plot. To estimate the spatial frequencies of the repeating patterns of gilgai, we obtained ultra-high resolution (0.01-0.03m/pixel) images with an unmanned aerial vehicle (UAV) from which digital elevation models were also generated. Geostatistical analyses using wavelet and fourier methods in 1- and 2-dimensions were employed to characterize gilgai size and distribution. Preliminary results support regular spatial patterning across the gilgaied landscape and heterogeneities may be related to local soil properties and biophysical influences. Local data on gilgai and fracture characteristics suggest that gilgai form at characteristic heights and spacing based on fracture morphology: deep, wide cracks result in large, highly vegetated mounds whereas shallow cracks, induced by animal trails, are less correlated with gilgai size and shape. Our experiments will help elucidate the links between shrink-swell processes and gilgai-vegetation patterning in high activity clay soils and advance our understanding of the mechanisms of gilgai formation in drylands.

  20. High resolution channel geometry from repeat aerial imagery

    NASA Astrophysics Data System (ADS)

    King, T.; Neilson, B. T.; Jensen, A.; Torres-Rua, A. F.; Winkelaar, M.; Rasmussen, M. T.

    2015-12-01

    River channel cross sectional geometry is a key attribute for controlling the river energy balances where surface heat fluxes dominate and discharge varies significantly over short time periods throughout the open water season. These dynamics are seen in higher gradient portions of Arctic rivers where surface heat fluxes can dominates river energy balances and low hillslope storage produce rapidly varying hydrographs. Additionally, arctic river geometry can be highly dynamic in the face of thermal erosion of permafrost landscape. While direct in-situ measurements of channel cross sectional geometry are accurate, they are limited in spatial resolution and coverage, and can be access limited in remote areas. Remote sensing can help gather data at high spatial resolutions and large areas, however techniques for extracting channel geometry is often limited to the banks and flood plains adjacent to river, as the water column inhibits sensing of the river bed itself. Green light LiDAR can be used to map bathymetry, however this is expensive, difficult to obtain at large spatial scales, and dependent on water quality. Alternatively, 3D photogrammetry from aerial imagery can be used to analyze the non-wetted portion of the river channel, but extracting full cross sections requires extrapolation into the wetted portion of the river. To bridge these gaps, an approach for using repeat aerial imagery surveys with visual (RGB) and near infrared (NIR) to extract high resolution channel geometry for the Kuparuk River in the Alaskan Arctic was developed. Aerial imagery surveys were conducted under multiple flow conditions and water surface geometry (elevation and width) were extracted through photogrammetry. Channel geometry was extracted by combining water surface widths and elevations from multiple flights. The accuracy of these results were compared against field surveyed cross sections at many locations throughout the study reach and a digital elevation model created under

  1. 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.

  2. Automatic identification of agricultural terraces through object-oriented analysis of very high resolution DSMs and multispectral imagery obtained from an unmanned aerial vehicle.

    PubMed

    Diaz-Varela, R A; Zarco-Tejada, P J; Angileri, V; Loudjani, P

    2014-02-15

    Agricultural terraces are features that provide a number of ecosystem services. As a result, their maintenance is supported by measures established by the European Common Agricultural Policy (CAP). In the framework of CAP implementation and monitoring, there is a current and future need for the development of robust, repeatable and cost-effective methodologies for the automatic identification and monitoring of these features at farm scale. This is a complex task, particularly when terraces are associated to complex vegetation cover patterns, as happens with permanent crops (e.g. olive trees). In this study we present a novel methodology for automatic and cost-efficient identification of terraces using only imagery from commercial off-the-shelf (COTS) cameras on board unmanned aerial vehicles (UAVs). Using state-of-the-art computer vision techniques, we generated orthoimagery and digital surface models (DSMs) at 11 cm spatial resolution with low user intervention. In a second stage, these data were used to identify terraces using a multi-scale object-oriented classification method. Results show the potential of this method even in highly complex agricultural areas, both regarding DSM reconstruction and image classification. The UAV-derived DSM had a root mean square error (RMSE) lower than 0.5 m when the height of the terraces was assessed against field GPS data. The subsequent automated terrace classification yielded an overall accuracy of 90% based exclusively on spectral and elevation data derived from the UAV imagery.

  3. Automatic identification of agricultural terraces through object-oriented analysis of very high resolution DSMs and multispectral imagery obtained from an unmanned aerial vehicle.

    PubMed

    Diaz-Varela, R A; Zarco-Tejada, P J; Angileri, V; Loudjani, P

    2014-02-15

    Agricultural terraces are features that provide a number of ecosystem services. As a result, their maintenance is supported by measures established by the European Common Agricultural Policy (CAP). In the framework of CAP implementation and monitoring, there is a current and future need for the development of robust, repeatable and cost-effective methodologies for the automatic identification and monitoring of these features at farm scale. This is a complex task, particularly when terraces are associated to complex vegetation cover patterns, as happens with permanent crops (e.g. olive trees). In this study we present a novel methodology for automatic and cost-efficient identification of terraces using only imagery from commercial off-the-shelf (COTS) cameras on board unmanned aerial vehicles (UAVs). Using state-of-the-art computer vision techniques, we generated orthoimagery and digital surface models (DSMs) at 11 cm spatial resolution with low user intervention. In a second stage, these data were used to identify terraces using a multi-scale object-oriented classification method. Results show the potential of this method even in highly complex agricultural areas, both regarding DSM reconstruction and image classification. The UAV-derived DSM had a root mean square error (RMSE) lower than 0.5 m when the height of the terraces was assessed against field GPS data. The subsequent automated terrace classification yielded an overall accuracy of 90% based exclusively on spectral and elevation data derived from the UAV imagery. PMID:24473345

  4. Challenges in collecting hyperspectral imagery of coastal waters using Unmanned Aerial Vehicles (UAVs)

    NASA Astrophysics Data System (ADS)

    English, D. C.; Herwitz, S.; Hu, C.; Carlson, P. R., Jr.; Muller-Karger, F. E.; Yates, K. K.; Ramsewak, D.

    2013-12-01

    Airborne multi-band remote sensing is an important tool for many aquatic applications; and the increased spectral information from hyperspectral sensors may increase the utility of coastal surveys. Recent technological advances allow Unmanned Aerial Vehicles (UAVs) to be used as alternatives or complements to manned aircraft or in situ observing platforms, and promise significant advantages for field studies. These include the ability to conduct programmed flight plans, prolonged and coordinated surveys, and agile flight operations under difficult conditions such as measurements made at low altitudes. Hyperspectral imagery collected from UAVs should allow the increased differentiation of water column or shallow benthic communities at relatively small spatial scales. However, the analysis of hyperspectral imagery from airborne platforms over shallow coastal waters differs from that used for terrestrial or oligotrophic ocean color imagery, and the operational constraints and considerations for the collection of such imagery from autonomous platforms also differ from terrestrial surveys using manned aircraft. Multispectral and hyperspectral imagery of shallow seagrass and coral environments in the Florida Keys were collected with various sensor systems mounted on manned and unmanned aircrafts in May 2012, October 2012, and May 2013. The imaging systems deployed on UAVs included NovaSol's Selectable Hyperspectral Airborne Remote-sensing Kit (SHARK), a Tetracam multispectral imaging system, and the Sunflower hyperspectal imager from Galileo Group, Inc. The UAVs carrying these systems were Xtreme Aerial Concepts' Vision-II Rotorcraft UAV, MLB Company's Bat-4 UAV, and NASA's SIERRA UAV, respectively. Additionally, the Galileo Group's manned aircraft also surveyed the areas with their AISA Eagle hyperspectral imaging system. For both manned and autonomous flights, cloud cover and sun glint (solar and viewing angles) were dominant constraints on retrieval of quantitatively

  5. Applicability Evaluation of Object Detection Method to Satellite and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Kamiya, K.; Fuse, T.; Takahashi, M.

    2016-06-01

    Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ object detection before object recognition can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING) method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

  6. First results for an image processing workflow for hyperspatial imagery acquired with a low-cost unmanned aerial vehicle (UAV).

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Very high-resolution images from unmanned aerial vehicles (UAVs) have great potential for use in rangeland monitoring and assessment, because the imagery fills the gap between ground-based observations and remotely sensed imagery from aerial or satellite sensors. However, because UAV imagery is ofte...

  7. A Semi-Automated Single Day Image Differencing Technique to Identify Animals in Aerial Imagery

    PubMed Central

    Terletzky, Pat; Ramsey, Robert Douglas

    2014-01-01

    Our research presents a proof-of-concept that explores a new and innovative method to identify large animals in aerial imagery with single day image differencing. We acquired two aerial images of eight fenced pastures and conducted a principal component analysis of each image. We then subtracted the first principal component of the two pasture images followed by heuristic thresholding to generate polygons. The number of polygons represented the number of potential cattle (Bos taurus) and horses (Equus caballus) in the pasture. The process was considered semi-automated because we were not able to automate the identification of spatial or spectral thresholding values. Imagery was acquired concurrently with ground counts of animal numbers. Across the eight pastures, 82% of the animals were correctly identified, mean percent commission was 53%, and mean percent omission was 18%. The high commission error was due to small mis-alignments generated from image-to-image registration, misidentified shadows, and grouping behavior of animals. The high probability of correctly identifying animals suggests short time interval image differencing could provide a new technique to enumerate wild ungulates occupying grassland ecosystems, especially in isolated or difficult to access areas. To our knowledge, this was the first attempt to use standard change detection techniques to identify and enumerate large ungulates. PMID:24454827

  8. 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.

  9. Multi-Scale Validation of Forest Insect Mortality Using QuickBird and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Meddens, A. J.; Hicke, J. A.; Vierling, L. A.

    2008-12-01

    Insects are major disturbances in forested ecosystems, affecting forest succession, carbon cycling, and fuel loads. Insect-caused tree mortality causes significant change in forest structure as dead trees lose their needles and eventually fall to the ground. To manage forests and establish natural resource policy, accurate estimates of the extent of insect disturbance are needed. Mountain pine beetles (Dendroctonus ponderosae Hopkins), one of the most damaging insect species, have affected large forested areas in the United States and Canada. Our goal is to map landscape-level tree mortality caused by insect outbreaks across the western United States using satellite remote sensing. Here we report on the methods we are developing and applying to an outbreak of mountain pine beetle in Colorado as well as the means of evaluating the classification using field measurements and finer spatial resolution aerial imagery. In August 2008, 36 forest inventory plots were established in an area affected by mountain pine beetle in the Arapaho National Forest in the Rocky Mountains of Colorado, USA. A digital aerial multispectral image with a spatial resolution of 30 cm and a QuickBird image with a spatial resolution of 2.4 m were acquired in the same area. We are employing a nested validation approach using the aerial imagery and QuickBird imagery to ultimately validate a Landsat-based insect disturbance detection product. Tree-level field measurements are used to evaluate classified the aerial imagery. The classified aerial imagery is subsequently used to evaluate classified QuickBird imagery, which in turn is used to evaluate the Landsat product. The outcomes of finer spatial level classification can be used to increase understanding of the coarser spatial image classification and provide means to investigate disturbance level thresholds for the detection of insect outbreaks using the coarser resolution imagery.

  10. Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

    USGS Publications Warehouse

    Gillan, Jeffrey K.; Karl, Jason W.; Barger, Nichole N.; Elaksher, Ahmed; Duniway, Michael C.

    2016-01-01

    Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to

  11. Unsupervised building detection from irregularly spaced LiDAR and aerial imagery

    NASA Astrophysics Data System (ADS)

    Shorter, Nicholas Sven

    As more data sources containing 3-D information are becoming available, an increased interest in 3-D imaging has emerged. Among these is the 3-D reconstruction of buildings and other man-made structures. A necessary preprocessing step is the detection and isolation of individual buildings that subsequently can be reconstructed in 3-D using various methodologies. Applications for both building detection and reconstruction have commercial use for urban planning, network planning for mobile communication (cell phone tower placement), spatial analysis of air pollution and noise nuisances, microclimate investigations, geographical information systems, security services and change detection from areas affected by natural disasters. Building detection and reconstruction are also used in the military for automatic target recognition and in entertainment for virtual tourism. Previously proposed building detection and reconstruction algorithms solely utilized aerial imagery. With the advent of Light Detection and Ranging (LiDAR) systems providing elevation data, current algorithms explore using captured LiDAR data as an additional feasible source of information. Additional sources of information can lead to automating techniques (alleviating their need for manual user intervention) as well as increasing their capabilities and accuracy. Several building detection approaches surveyed in the open literature have fundamental weaknesses that hinder their use; such as requiring multiple data sets from different sensors, mandating certain operations to be carried out manually, and limited functionality to only being able to detect certain types of buildings. In this work, a building detection system is proposed and implemented which strives to overcome the limitations seen in existing techniques. The developed framework is flexible in that it can perform building detection from just LiDAR data (first or last return), or just nadir, color aerial imagery. If data from both LiDAR and

  12. Wildlife Multispecies Remote Sensing Using Visible and Thermal Infrared Imagery Acquired from AN Unmanned Aerial Vehicle (uav)

    NASA Astrophysics Data System (ADS)

    Chrétien, L.-P.; Théau, J.; Ménard, P.

    2015-08-01

    Wildlife aerial surveys require time and significant resources. Multispecies detection could reduce costs to a single census for species that coexist spatially. Traditional methods are demanding for observers in terms of concentration and are not adapted to multispecies censuses. The processing of multispectral aerial imagery acquired from an unmanned aerial vehicle (UAV) represents a potential solution for multispecies detection. The method used in this study is based on a multicriteria object-based image analysis applied on visible and thermal infrared imagery acquired from a UAV. This project aimed to detect American bison, fallow deer, gray wolves, and elks located in separate enclosures with a known number of individuals. Results showed that all bison and elks were detected without errors, while for deer and wolves, 0-2 individuals per flight line were mistaken with ground elements or undetected. This approach also detected simultaneously and separately the four targeted species even in the presence of other untargeted ones. These results confirm the potential of multispectral imagery acquired from UAV for wildlife census. Its operational application remains limited to small areas related to the current regulations and available technology. Standardization of the workflow will help to reduce time and expertise requirements for such technology.

  13. Acquisition, orthorectification, and object-based classification of unmanned aerial vehicle (UAV) imagery for rangeland monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this paper, we examine the potential of using a small unmanned aerial vehicle (UAV) for rangeland inventory, assessment and monitoring. Imagery with 8-cm resolution was acquired over 290 ha in southwestern Idaho. We developed a semi-automated orthorectification procedure suitable for handling lar...

  14. 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.

  15. Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery.

    PubMed

    Casado, Monica Rivas; Gonzalez, Rocio Ballesteros; Kriechbaumer, Thomas; Veal, Amanda

    2015-01-01

    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. PMID:26556355

  16. Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery

    PubMed Central

    Rivas Casado, Monica; Ballesteros Gonzalez, Rocio; Kriechbaumer, Thomas; Veal, Amanda

    2015-01-01

    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. PMID:26556355

  17. Automatic Extraction of Building Outline from High Resolution Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Wang, Yandong

    2016-06-01

    In this paper, a new approach for automated extraction of building boundary from high resolution imagery is proposed. The proposed approach uses both geometric and spectral properties of a building to detect and locate buildings accurately. It consists of automatic generation of high quality point cloud from the imagery, building detection from point cloud, classification of building roof and generation of building outline. Point cloud is generated from the imagery automatically using semi-global image matching technology. Buildings are detected from the differential surface generated from the point cloud. Further classification of building roof is performed in order to generate accurate building outline. Finally classified building roof is converted into vector format. Numerous tests have been done on images in different locations and results are presented in the paper.

  18. Preliminary assessment of aerial photography techniques for canvasback population analysis

    USGS Publications Warehouse

    Munro, R.E.; Trauger, D.L.

    1976-01-01

    Recent intensive research on the canvasback has focused attention on the need for more precise estimates of population parameters. During the 1972-75 period, various types of aerial photographing equipment were evaluated to determine the problems and potentials for employing these techniques in appraisals of canvasback populations. The equipment and procedures available for automated analysis of aerial photographic imagery were also investigated. Serious technical problems remain to be resolved, but some promising results were obtained. Final conclusions about the feasibility of operational implementation await a more rigorous analysis of the data collected.

  19. Exploration towards the modeling of gable-roofed buildings using a combination of aerial and street-level imagery

    NASA Astrophysics Data System (ADS)

    Creusen, Ivo; Hazelhoff, Lykele; de With, Peter H. N.

    2015-03-01

    Extraction of residential building properties is helpful for numerous applications, such as computer-guided feasibility analysis for solar panel placement, determination of real-estate taxes and assessment of real-estate insurance policies. Therefore, this work explores the automated modeling of buildings with a gable roof (the most common roof type within Western Europe), based on a combination of aerial imagery and street-level panoramic images. This is a challenging task, since buildings show large variations in shape, dimensions and building extensions, and may additionally be captured under non-ideal lighting conditions. The aerial images feature a coarse overview of the building due to the large capturing distance. The building footprint and an initial estimate of the building height is extracted based on the analysis of stereo aerial images. The estimated model is then refined using street-level images, which feature higher resolution and enable more accurate measurements, however, displaying a single building side only. Initial experiments indicate that the footprint dimensions of the main building can be accurately extracted from aerial images, while the building height is extracted with slightly less accuracy. By combining aerial and street-level images, we have found that the accuracies of these height measurements are significantly increased, thereby improving the overall quality of the extracted building model, and resulting in an average inaccuracy of the estimated volume below 10%.

  20. Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.; Hayden, David; Thompson, David R.; Castano, Rebecca

    2013-01-01

    Many current and future NASA missions are capable of collecting enormous amounts of data, of which only a small portion can be transmitted to Earth. Communications are limited due to distance, visibility constraints, and competing mission downlinks. Long missions and high-resolution, multispectral imaging devices easily produce data exceeding the available bandwidth. To address this situation computationally efficient algorithms were developed for analyzing science imagery onboard the spacecraft. These algorithms autonomously cluster the data into classes of similar imagery, enabling selective downlink of representatives of each class, and a map classifying the terrain imaged rather than the full dataset, reducing the volume of the downlinked data. A range of approaches was examined, including k-means clustering using image features based on color, texture, temporal, and spatial arrangement

  1. The Photo-Mosaic Assistant: Incorporating Historic Aerial Imagery into Modern Research Projects

    NASA Astrophysics Data System (ADS)

    Flathers, E.

    2013-12-01

    One challenge that researchers face as data organization and analysis shift into the digital realm is the incorporation of 'dirty' data from analog back-catalogs into current projects. Geospatial data collections in university libraries, government data repositories, and private industry contain historic data such as aerial photographs that may be stored as negatives, prints, and as scanned digital image files. A typical aerial imagery series is created by taking photos of the ground from an aircraft along a series of parallel flight lines. The raw photos can be assembled into a mosaic that represents the full geographic area of the collection, but each photo suffers from individual distortion according to the attitude and altitude of the collecting aircraft at the moment of acquisition, so there is a process of orthorectification needed in order to produce a planimetric composite image that can be used to accurately refer to locations on the ground. Historic aerial photo collections often need significant preparation for consumption by a GIS: they may need to be digitized, often lack any explicit spatial coordinates, and may not include information about flight line patterns. Many collections lack even such basic information as index numbers for the photos, so it may be unclear in what order the photos were acquired. When collections contain large areas of, for example, forest or agricultural land, any given photo may have few visual cues to assist in relating it to the other photos or to an area on the ground. The Photo-Mosaic Assistant (PMA) is a collection of tools designed to assist in the organization of historic aerial photo collections and the preparation of collections for orthorectification and use in modern research applications. The first tool is a light table application that allows a user to take advantage of visual cues within photos to organize and explore the collection, potentially building a rough image mosaic by hand. The second tool is a set of

  2. Evaluation of unmanned aerial vehicle (UAV) imagery to model vegetation heights in Hulun Buir grassland ecosystem

    NASA Astrophysics Data System (ADS)

    Wang, D.; Xin, X.; Li, Z.

    2015-12-01

    Vertical vegetation structure in grassland ecosystem is needed to assess grassland health and monitor available forage for livestock and wildlife habitat. Traditional ground-based field methods for measuring vegetation heights are time consuming. Most emerging airborne remote sensing techniques capable of measuring surface and vegetation height (e.g., LIDAR) are too expensive to apply at broad scales. Aerial or spaceborne stereo imagery has the cost advantage for mapping height of tall vegetation, such as forest. However, the accuracy and uncertainty of using stereo imagery for modeling heights of short vegetation, such as grass (generally lower than 50cm) needs to be investigated. In this study, 2.5-cm resolution UAV stereo imagery are used to model vegetation heights in Hulun Buir grassland ecosystem. Strong correlations were observed (r > 0.9) between vegetation heights derived from UAV stereo imagery and those field-measured ones at individual and plot level. However, vegetation heights tended to be underestimated in the imagery especially for those areas with high vegetation coverage. The strong correlations between field-collected vegetation heights and metrics derived from UAV stereo imagery suggest that UAV stereo imagery can be used to estimate short vegetation heights such as those in grassland ecosystem. Future work will be needed to verify the extensibility of the methods to other sites and vegetation types.

  3. Exterior Orientation Estimation of Oblique Aerial Imagery Using Vanishing Points

    NASA Astrophysics Data System (ADS)

    Verykokou, Styliani; Ioannidis, Charalabos

    2016-06-01

    In this paper, a methodology for the calculation of rough exterior orientation (EO) parameters of multiple large-scale overlapping oblique aerial images, in the case that GPS/INS information is not available (e.g., for old datasets), is presented. It consists of five main steps; (a) the determination of the overlapping image pairs and the single image in which four ground control points have to be measured; (b) the computation of the transformation parameters from every image to the coordinate reference system; (c) the rough estimation of the camera interior orientation parameters; (d) the estimation of the true horizon line and the nadir point of each image; (e) the calculation of the rough EO parameters of each image. A developed software suite implementing the proposed methodology is tested using a set of UAV multi-perspective oblique aerial images. Several tests are performed for the assessment of the errors and show that the estimated EO parameters can be used either as initial approximations for a bundle adjustment procedure or as rough georeferencing information for several applications, like 3D modelling, even by non-photogrammetrists, because of the minimal user intervention needed. Finally, comparisons with a commercial software are made, in terms of automation and correctness of the computed EO parameters.

  4. Rigorous LiDAR Strip Adjustment with Triangulated Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Y. J.; Xiong, X. D.; Hu, X. Y.

    2013-10-01

    This paper proposes a POS aided LiDAR strip adjustment method. Firstly, aero-triangulation of the simultaneously obtained aerial images is conducted with a few photogrammetry-specific ground control points. Secondly, LiDAR intensity images are generated from the reflectance signals of laser foot points, and conjugate points are automatically matched between the LiDAR intensity image and the aero-triangulated aerial image. Control points used in LiDAR strip adjustment are derived from these conjugate points. Finally, LiDAR strip adjustment of real data is conducted with the POS aided LiDAR strip adjustment method proposed in this paper, and comparison experiment using three-dimensional similarity transformation method is also performed. The results indicate that the POS aided LiDAR strip adjustment method can significantly correct the planimetric and vertical errors of LiDAR strips. The planimetric correction accuracy is higher than average point distance while the vertical correction accuracy is comparable to that of the result of aero-triangulation. Moreover, the proposed method is obliviously superior to the traditional three-dimensional similarity transformation method.

  5. New interpretations of the Fort Clark State Historic Site based on aerial color and thermal infrared imagery

    NASA Astrophysics Data System (ADS)

    Heller, Andrew Roland

    The Fort Clark State Historic Site (32ME2) is a well known site on the upper Missouri River, North Dakota. The site was the location of two Euroamerican trading posts and a large Mandan-Arikara earthlodge village. In 2004, Dr. Kenneth L. Kvamme and Dr. Tommy Hailey surveyed the site using aerial color and thermal infrared imagery collected from a powered parachute. Individual images were stitched together into large image mosaics and registered to Wood's 1993 interpretive map of the site using Adobe Photoshop. The analysis of those image mosaics resulted in the identification of more than 1,500 archaeological features, including as many as 124 earthlodges.

  6. Canopy Density Mapping on Ultracam-D Aerial Imagery in Zagros Woodlands, Iran

    NASA Astrophysics Data System (ADS)

    Erfanifard, Y.; Khodaee, Z.

    2013-09-01

    Canopy density maps express different characteristics of forest stands, especially in woodlands. Obtaining such maps by field measurements is so expensive and time-consuming. It seems necessary to find suitable techniques to produce these maps to be used in sustainable management of woodland ecosystems. In this research, a robust procedure was suggested to obtain these maps by very high spatial resolution aerial imagery. It was aimed to produce canopy density maps by UltraCam-D aerial imagery, newly taken in Zagros woodlands by Iran National Geographic Organization (NGO), in this study. A 30 ha plot of Persian oak (Quercus persica) coppice trees was selected in Zagros woodlands, Iran. The very high spatial resolution aerial imagery of the plot purchased from NGO, was classified by kNN technique and the tree crowns were extracted precisely. The canopy density was determined in each cell of different meshes with different sizes overlaid on the study area map. The accuracy of the final maps was investigated by the ground truth obtained by complete field measurements. The results showed that the proposed method of obtaining canopy density maps was efficient enough in the study area. The final canopy density map obtained by a mesh with 30 Ar (3000 m2) cell size had 80% overall accuracy and 0.61 KHAT coefficient of agreement which shows a great agreement with the observed samples. This method can also be tested in other case studies to reveal its capability in canopy density map production in woodlands.

  7. A procedure for orthorectification of sub-decimeter resolution imagery obtained with an unmanned aerial vehicle (UAV)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Digital aerial photography acquired with unmanned aerial vehicles (UAVs) has great value for resource management due to the flexibility and relatively low cost for image acquisition, and very high resolution imagery (5 cm) which allows for mapping bare soil and vegetation types, structure and patter...

  8. 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.

  9. Mapping of riparian invasive species with supervised classification of Unmanned Aerial System (UAS) imagery

    NASA Astrophysics Data System (ADS)

    Michez, Adrien; Piégay, Hervé; Jonathan, Lisein; Claessens, Hugues; Lejeune, Philippe

    2016-02-01

    Riparian zones are key landscape features, representing the interface between terrestrial and aquatic ecosystems. Although they have been influenced by human activities for centuries, their degradation has increased during the 20th century. Concomitant with (or as consequences of) these disturbances, the invasion of exotic species has increased throughout the world's riparian zones. In our study, we propose a easily reproducible methodological framework to map three riparian invasive taxa using Unmanned Aerial Systems (UAS) imagery: Impatiens glandulifera Royle, Heracleum mantegazzianum Sommier and Levier, and Japanese knotweed (Fallopia sachalinensis (F. Schmidt Petrop.), Fallopia japonica (Houtt.) and hybrids). Based on visible and near-infrared UAS orthophoto, we derived simple spectral and texture image metrics computed at various scales of image segmentation (10, 30, 45, 60 using eCognition software). Supervised classification based on the random forests algorithm was used to identify the most relevant variable (or combination of variables) derived from UAS imagery for mapping riparian invasive plant species. The models were built using 20% of the dataset, the rest of the dataset being used as a test set (80%). Except for H. mantegazzianum, the best results in terms of global accuracy were achieved with the finest scale of analysis (segmentation scale parameter = 10). The best values of overall accuracies reached 72%, 68%, and 97% for I. glandulifera, Japanese knotweed, and H. mantegazzianum respectively. In terms of selected metrics, simple spectral metrics (layer mean/camera brightness) were the most used. Our results also confirm the added value of texture metrics (GLCM derivatives) for mapping riparian invasive species. The results obtained for I. glandulifera and Japanese knotweed do not reach sufficient accuracies for operational applications. However, the results achieved for H. mantegazzianum are encouraging. The high accuracies values combined to

  10. Imagery analysis and the need for standards

    NASA Astrophysics Data System (ADS)

    Grant, Barbara G.

    2014-09-01

    While efforts within the optics community focus on the development of high-quality systems and data products, comparatively little attention is paid to their use. Our standards for verification and validation are high; but in some user domains, standards are either lax or do not exist at all. In forensic imagery analysis, for example, standards exist to judge image quality, but do not exist to judge the quality of an analysis. In litigation, a high quality analysis is by default the one performed by the victorious attorney's expert. This paper argues for the need to extend quality standards into the domain of imagery analysis, which is expected to increase in national visibility and significance with the increasing deployment of unmanned aerial vehicle—UAV, or "drone"—sensors in the continental U. S.. It argues that like a good radiometric calibration, made as independent of the calibrated instrument as possible, a good analysis should be subject to standards the most basic of which is the separation of issues of scientific fact from analysis results.

  11. Vectorization of Road Data Extracted from Aerial and Uav Imagery

    NASA Astrophysics Data System (ADS)

    Bulatov, Dimitri; Häufel, Gisela; Pohl, Melanie

    2016-06-01

    Road databases are essential instances of urban infrastructure. Therefore, automatic road detection from sensor data has been an important research activity during many decades. Given aerial images in a sufficient resolution, dense 3D reconstruction can be performed. Starting at a classification result of road pixels from combined elevation and optical data, we present in this paper a fivestep procedure for creating vectorized road networks. These main steps of the algorithm are: preprocessing, thinning, polygonization, filtering, and generalization. In particular, for the generalization step, which represents the principal area of innovation, two strategies are presented. The first strategy corresponds to a modification of the Douglas-Peucker-algorithm in order to reduce the number of vertices while the second strategy allows a smoother representation of street windings by Bezir curves, which results in reduction - to a decimal power - of the total curvature defined for the dataset. We tested our approach on three datasets with different complexity. The quantitative assessment of the results was performed by means of shapefiles from OpenStreetMap data. For a threshold of 6 m, completeness and correctness values of up to 85% were achieved.

  12. Forest fuel treatment detection using multi-temporal airborne Lidar data and high resolution aerial imagery ---- A case study at Sierra Nevada, California

    NASA Astrophysics Data System (ADS)

    Su, Y.; Guo, Q.; Collins, B.; Fry, D.; Kelly, M.

    2014-12-01

    Forest fuel treatments (FFT) are often employed in Sierra Nevada forest (located in California, US) to enhance forest health, regulate stand density, and reduce wildfire risk. However, there have been concerns that FFTs may have negative impacts on certain protected wildlife species. Due to the constraints and protection of resources (e.g., perennial streams, cultural resources, wildlife habitat, etc.), the actual FFT extents are usually different from planned extents. Identifying the actual extent of treated areas is of primary importance to understand the environmental influence of FFTs. Light detection and ranging (Lidar) is a powerful remote sensing technique that can provide accurate forest structure measurements, which provides great potential to monitor forest changes. This study used canopy height model (CHM) and canopy cover (CC) products derived from multi-temporal airborne Lidar data to detect FFTs by an approach combining a pixel-wise thresholding method and a object-of-interest segmentation method. We also investigated forest change following the implementation of landscape-scale FFT projects through the use of normalized difference vegetation index (NDVI) and standardized principle component analysis (PCA) from multi-temporal high resolution aerial imagery. The same FFT detection routine was applied on the Lidar data and aerial imagery for the purpose of comparing the capability of Lidar data and aerial imagery on FFT detection. Our results demonstrated that the FFT detection using Lidar derived CC products produced both the highest total accuracy and kappa coefficient, and was more robust at identifying areas with light FFTs. The accuracy using Lidar derived CHM products was significantly lower than that of the result using Lidar derived CC, but was still slightly higher than using aerial imagery. FFT detection results using NDVI and standardized PCA using multi-temporal aerial imagery produced almost identical total accuracy and kappa coefficient

  13. Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping.

    PubMed

    Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

    2015-08-12

    Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.

  14. Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping.

    PubMed

    Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

    2015-01-01

    Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights. PMID:26274960

  15. Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping

    PubMed Central

    Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

    2015-01-01

    Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights. PMID:26274960

  16. 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.

  17. Bridging Estimates of Greenness in an Arid Grassland Using Field Observations, Phenocams, and Time Series Unmanned Aerial System (UAS) Imagery

    NASA Astrophysics Data System (ADS)

    Browning, D. M.; Tweedie, C. E.; Rango, A.

    2013-12-01

    Spatially extensive grasslands and savannas in arid and semi-arid ecosystems (i.e., rangelands) require cost-effective, accurate, and consistent approaches for monitoring plant phenology. Remotely sensed imagery offers these capabilities; however contributions of exposed soil due to modest vegetation cover, susceptibility of vegetation to drought, and lack of robust scaling relationships challenge biophysical retrievals using moderate- and coarse-resolution satellite imagery. To evaluate methods for characterizing plant phenology of common rangeland species and to link field measurements to remotely sensed metrics of land surface phenology, we devised a hierarchical study spanning multiple spatial scales. We collect data using weekly standardized field observations on focal plants, daily phenocam estimates of vegetation greenness, and very high spatial resolution imagery from an Unmanned Aerial System (UAS) throughout the growing season. Field observations of phenological condition and vegetation cover serve to verify phenocam greenness indices along with indices derived from time series UAS imagery. UAS imagery is classified using object-oriented image analysis to identify species-specific image objects for which greenness indices are derived. Species-specific image objects facilitate comparisons with phenocam greenness indices and scaling spectral responses to footprints of Landsat and MODIS pixels. Phenocam greenness curves indicated rapid canopy development for the widespread deciduous shrub Prosopis glandulosa over 14 (in April 2012) to 16 (in May 2013) days. The modest peak in greenness for the dominant perennial grass Bouteloua eriopoda occurred in October 2012 following peak summer rainfall. Weekly field estimates of canopy development closely coincided with daily patterns in initial growth and senescence for both species. Field observations improve the precision of the timing of phenophase transitions relative to inflection points calculated from phenocam

  18. Environmental waste site characterization utilizing aerial photographs and satellite imagery: Three sites in New Mexico, USA

    SciTech Connect

    Van Eeckhout, E.; Pope, P.; Becker, N.; Wells, B.; Lewis, A.; David, N.

    1996-04-01

    The proper handling and characterization of past hazardous waste sites is becoming more and more important as world population extends into areas previously deemed undesirable. Historical photographs, past records, current aerial satellite imagery can play an important role in characterizing these sites. These data provide clear insight into defining problem areas which can be surface samples for further detail. Three such areas are discussed in this paper: (1) nuclear wastes buried in trenches at Los Alamos National Laboratory, (2) surface dumping at one site at Los Alamos National Laboratory, and (3) the historical development of a municipal landfill near Las Cruces, New Mexico.

  19. 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.

  20. Estimation of walrus populations on sea ice with infrared imagery and aerial photography

    USGS Publications Warehouse

    Udevitz, M.S.; Burn, D.M.; Webber, M.A.

    2008-01-01

    Population sizes of ice-associated pinnipeds have often been estimated with visual or photographic aerial surveys, but these methods require relatively slow speeds and low altitudes, limiting the area they can cover. Recent developments in infrared imagery and its integration with digital photography could allow substantially larger areas to be surveyed and more accurate enumeration of individuals, thereby solving major problems with previous survey methods. We conducted a trial survey in April 2003 to estimate the number of Pacific walruses (Odobenus rosmarus divergens) hauled out on sea ice around St. Lawrence Island, Alaska. The survey used high altitude infrared imagery to detect groups of walruses on strip transects. Low altitude digital photography was used to determine the number of walruses in a sample of detected groups and calibrate the infrared imagery for estimating the total number of walruses. We propose a survey design incorporating this approach with satellite radio telemetry to estimate the proportion of the population in the water and additional low-level flights to estimate the proportion of the hauled-out population in groups too small to be detected in the infrared imagery. We believe that this approach offers the potential for obtaining reliable population estimates for walruses and other ice-associated pinnipeds. ?? 2007 by the Society for Marine Mammalogy.

  1. Monitoring the invasion of Spartina alterniflora using very high resolution unmanned aerial vehicle imagery in Beihai, Guangxi (China).

    PubMed

    Wan, Huawei; Wang, Qiao; Jiang, Dong; Fu, Jingying; Yang, Yipeng; Liu, Xiaoman

    2014-01-01

    Spartina alterniflora was introduced to Beihai, Guangxi (China), for ecological engineering purposes in 1979. However, the exceptional adaptability and reproductive ability of this species have led to its extensive dispersal into other habitats, where it has had a negative impact on native species and threatens the local mangrove and mudflat ecosystems. To obtain the distribution and spread of Spartina alterniflora, we collected HJ-1 CCD imagery from 2009 and 2011 and very high resolution (VHR) imagery from the unmanned aerial vehicle (UAV). The invasion area of Spartina alterniflora was 357.2 ha in 2011, which increased by 19.07% compared with the area in 2009. A field survey was conducted for verification and the total accuracy was 94.0%. The results of this paper show that VHR imagery can provide details on distribution, progress, and early detection of Spartina alterniflora invasion. OBIA, object based image analysis for remote sensing (RS) detection method, can enable control measures to be more effective, accurate, and less expensive than a field survey of the invasive population.

  2. Monitoring the invasion of Spartina alterniflora using very high resolution unmanned aerial vehicle imagery in Beihai, Guangxi (China).

    PubMed

    Wan, Huawei; Wang, Qiao; Jiang, Dong; Fu, Jingying; Yang, Yipeng; Liu, Xiaoman

    2014-01-01

    Spartina alterniflora was introduced to Beihai, Guangxi (China), for ecological engineering purposes in 1979. However, the exceptional adaptability and reproductive ability of this species have led to its extensive dispersal into other habitats, where it has had a negative impact on native species and threatens the local mangrove and mudflat ecosystems. To obtain the distribution and spread of Spartina alterniflora, we collected HJ-1 CCD imagery from 2009 and 2011 and very high resolution (VHR) imagery from the unmanned aerial vehicle (UAV). The invasion area of Spartina alterniflora was 357.2 ha in 2011, which increased by 19.07% compared with the area in 2009. A field survey was conducted for verification and the total accuracy was 94.0%. The results of this paper show that VHR imagery can provide details on distribution, progress, and early detection of Spartina alterniflora invasion. OBIA, object based image analysis for remote sensing (RS) detection method, can enable control measures to be more effective, accurate, and less expensive than a field survey of the invasive population. PMID:24892066

  3. Monitoring the Invasion of Spartina alterniflora Using Very High Resolution Unmanned Aerial Vehicle Imagery in Beihai, Guangxi (China)

    PubMed Central

    Wan, Huawei; Wang, Qiao; Jiang, Dong; Yang, Yipeng; Liu, Xiaoman

    2014-01-01

    Spartina alterniflora was introduced to Beihai, Guangxi (China), for ecological engineering purposes in 1979. However, the exceptional adaptability and reproductive ability of this species have led to its extensive dispersal into other habitats, where it has had a negative impact on native species and threatens the local mangrove and mudflat ecosystems. To obtain the distribution and spread of Spartina alterniflora, we collected HJ-1 CCD imagery from 2009 and 2011 and very high resolution (VHR) imagery from the unmanned aerial vehicle (UAV). The invasion area of Spartina alterniflora was 357.2 ha in 2011, which increased by 19.07% compared with the area in 2009. A field survey was conducted for verification and the total accuracy was 94.0%. The results of this paper show that VHR imagery can provide details on distribution, progress, and early detection of Spartina alterniflora invasion. OBIA, object based image analysis for remote sensing (RS) detection method, can enable control measures to be more effective, accurate, and less expensive than a field survey of the invasive population. PMID:24892066

  4. Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery

    PubMed Central

    Ma, Yalong; Wu, Xinkai; Yu, Guizhen; Xu, Yongzheng; Wang, Yunpeng

    2016-01-01

    Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM) with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG) and Discrete Cosine Transform (DCT) features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness. PMID:27023564

  5. Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery.

    PubMed

    Ma, Yalong; Wu, Xinkai; Yu, Guizhen; Xu, Yongzheng; Wang, Yunpeng

    2016-01-01

    Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM) with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG) and Discrete Cosine Transform (DCT) features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness. PMID:27023564

  6. Influence of Gsd for 3d City Modeling and Visualization from Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Alrajhi, Muhamad; Alam, Zafare; Afroz Khan, Mohammad; Alobeid, Abdalla

    2016-06-01

    Ministry of Municipal and Rural Affairs (MOMRA), aims to establish solid infrastructure required for 3D city modelling, for decision making to set a mark in urban development. MOMRA is responsible for the large scale mapping 1:1,000; 1:2,500; 1:10,000 and 1:20,000 scales for 10cm, 20cm and 40 GSD with Aerial Triangulation data. As 3D city models are increasingly used for the presentation exploration, and evaluation of urban and architectural designs. Visualization capabilities and animations support of upcoming 3D geo-information technologies empower architects, urban planners, and authorities to visualize and analyze urban and architectural designs in the context of the existing situation. To make use of this possibility, first of all 3D city model has to be created for which MOMRA uses the Aerial Triangulation data and aerial imagery. The main concise for 3D city modelling in the Kingdom of Saudi Arabia exists due to uneven surface and undulations. Thus real time 3D visualization and interactive exploration support planning processes by providing multiple stakeholders such as decision maker, architects, urban planners, authorities, citizens or investors with a three - dimensional model. Apart from advanced visualization, these 3D city models can be helpful for dealing with natural hazards and provide various possibilities to deal with exotic conditions by better and advanced viewing technological infrastructure. Riyadh on one side is 5700m above sea level and on the other hand Abha city is 2300m, this uneven terrain represents a drastic change of surface in the Kingdom, for which 3D city models provide valuable solutions with all possible opportunities. In this research paper: influence of different GSD (Ground Sample Distance) aerial imagery with Aerial Triangulation is used for 3D visualization in different region of the Kingdom, to check which scale is more sophisticated for obtaining better results and is cost manageable, with GSD (7.5cm, 10cm, 20cm and 40cm

  7. Assessment of the Quality of Digital Terrain Model Produced from Unmanned Aerial System Imagery

    NASA Astrophysics Data System (ADS)

    Kosmatin Fras, M.; Kerin, A.; Mesarič, M.; Peterman, V.; Grigillo, D.

    2016-06-01

    Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy.

  8. Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system.

    PubMed

    Michez, Adrien; Piégay, Hervé; Lisein, Jonathan; Claessens, Hugues; Lejeune, Philippe

    2016-03-01

    Riparian forests are critically endangered many anthropogenic pressures and natural hazards. The importance of riparian zones has been acknowledged by European Directives, involving multi-scale monitoring. The use of this very-high-resolution and hyperspatial imagery in a multi-temporal approach is an emerging topic. The trend is reinforced by the recent and rapid growth of the use of the unmanned aerial system (UAS), which has prompted the development of innovative methodology. Our study proposes a methodological framework to explore how a set of multi-temporal images acquired during a vegetative period can differentiate some of the deciduous riparian forest species and their health conditions. More specifically, the developed approach intends to identify, through a process of variable selection, which variables derived from UAS imagery and which scale of image analysis are the most relevant to our objectives.The methodological framework is applied to two study sites to describe the riparian forest through two fundamental characteristics: the species composition and the health condition. These characteristics were selected not only because of their use as proxies for the riparian zone ecological integrity but also because of their use for river management.The comparison of various scales of image analysis identified the smallest object-based image analysis (OBIA) objects (ca. 1 m(2)) as the most relevant scale. Variables derived from spectral information (bands ratios) were identified as the most appropriate, followed by variables related to the vertical structure of the forest. Classification results show good overall accuracies for the species composition of the riparian forest (five classes, 79.5 and 84.1% for site 1 and site 2). The classification scenario regarding the health condition of the black alders of the site 1 performed the best (90.6%).The quality of the classification models developed with a UAS-based, cost-effective, and semi-automatic approach

  9. Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system.

    PubMed

    Michez, Adrien; Piégay, Hervé; Lisein, Jonathan; Claessens, Hugues; Lejeune, Philippe

    2016-03-01

    Riparian forests are critically endangered many anthropogenic pressures and natural hazards. The importance of riparian zones has been acknowledged by European Directives, involving multi-scale monitoring. The use of this very-high-resolution and hyperspatial imagery in a multi-temporal approach is an emerging topic. The trend is reinforced by the recent and rapid growth of the use of the unmanned aerial system (UAS), which has prompted the development of innovative methodology. Our study proposes a methodological framework to explore how a set of multi-temporal images acquired during a vegetative period can differentiate some of the deciduous riparian forest species and their health conditions. More specifically, the developed approach intends to identify, through a process of variable selection, which variables derived from UAS imagery and which scale of image analysis are the most relevant to our objectives.The methodological framework is applied to two study sites to describe the riparian forest through two fundamental characteristics: the species composition and the health condition. These characteristics were selected not only because of their use as proxies for the riparian zone ecological integrity but also because of their use for river management.The comparison of various scales of image analysis identified the smallest object-based image analysis (OBIA) objects (ca. 1 m(2)) as the most relevant scale. Variables derived from spectral information (bands ratios) were identified as the most appropriate, followed by variables related to the vertical structure of the forest. Classification results show good overall accuracies for the species composition of the riparian forest (five classes, 79.5 and 84.1% for site 1 and site 2). The classification scenario regarding the health condition of the black alders of the site 1 performed the best (90.6%).The quality of the classification models developed with a UAS-based, cost-effective, and semi-automatic approach

  10. Parameter optimization of image classification techniques to delineate crowns of coppice trees on UltraCam-D aerial imagery in woodlands

    NASA Astrophysics Data System (ADS)

    Erfanifard, Yousef; Stereńczak, Krzysztof; Behnia, Negin

    2014-01-01

    Estimating the optimal parameters of some classification techniques becomes their negative aspect as it affects their performance for a given dataset and reduces classification accuracy. It was aimed to optimize the combination of effective parameters of support vector machine (SVM), artificial neural network (ANN), and object-based image analysis (OBIA) classification techniques by the Taguchi method. The optimized techniques were applied to delineate crowns of Persian oak coppice trees on UltraCam-D very high spatial resolution aerial imagery in Zagros semiarid woodlands, Iran. The imagery was classified and the maps were assessed by receiver operating characteristic curve and other performance metrics. The results showed that Taguchi is a robust approach to optimize the combination of effective parameters in these image classification techniques. The area under curve (AUC) showed that the optimized OBIA could well discriminate tree crowns on the imagery (AUC=0.897), while SVM and ANN yielded slightly less AUC performances of 0.819 and 0.850, respectively. The indices of accuracy (0.999) and precision (0.999) and performance metrics of specificity (0.999) and sensitivity (0.999) in the optimized OBIA were higher than with other techniques. The optimization of effective parameters of image classification techniques by the Taguchi method, thus, provided encouraging results to discriminate the crowns of Persian oak coppice trees on UltraCam-D aerial imagery in Zagros semiarid woodlands.

  11. Extracting Semantically Annotated 3d Building Models with Textures from Oblique Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Frommholz, D.; Linkiewicz, M.; Meissner, H.; Dahlke, D.; Poznanska, A.

    2015-03-01

    This paper proposes a method for the reconstruction of city buildings with automatically derived textures that can be directly used for façade element classification. Oblique and nadir aerial imagery recorded by a multi-head camera system is transformed into dense 3D point clouds and evaluated statistically in order to extract the hull of the structures. For the resulting wall, roof and ground surfaces high-resolution polygonal texture patches are calculated and compactly arranged in a texture atlas without resampling. The façade textures subsequently get analyzed by a commercial software package to detect possible windows whose contours are projected into the original oriented source images and sparsely ray-casted to obtain their 3D world coordinates. With the windows being reintegrated into the previously extracted hull the final building models are stored as semantically annotated CityGML "LOD-2.5" objects.

  12. Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object-based classification approaches.

    PubMed

    Meneguzzo, Dacia M; Liknes, Greg C; Nelson, Mark D

    2013-08-01

    Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis-[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA. Three types of accuracy assessments were used to evaluate how each method performed in terms of: (1) producing a county-level estimate of total tree-covered area, (2) correctly locating tree cover on the ground, and (3) how tree cover patch metrics computed from the classified outputs compared to those delineated by a human photo interpreter. Both approaches were found to be viable for mapping tree cover over a broad spatial extent and could serve to supplement ground-based inventory data. The ICA approach produced an estimate of total tree cover more similar to the photo-interpreted result, but the output from the OBIA method was more realistic in terms of describing the actual observed spatial pattern of tree cover.

  13. Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object-based classification approaches.

    PubMed

    Meneguzzo, Dacia M; Liknes, Greg C; Nelson, Mark D

    2013-08-01

    Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis-[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA. Three types of accuracy assessments were used to evaluate how each method performed in terms of: (1) producing a county-level estimate of total tree-covered area, (2) correctly locating tree cover on the ground, and (3) how tree cover patch metrics computed from the classified outputs compared to those delineated by a human photo interpreter. Both approaches were found to be viable for mapping tree cover over a broad spatial extent and could serve to supplement ground-based inventory data. The ICA approach produced an estimate of total tree cover more similar to the photo-interpreted result, but the output from the OBIA method was more realistic in terms of describing the actual observed spatial pattern of tree cover. PMID:23255169

  14. Wavelet-based detection of bush encroachment in a savanna using multi-temporal aerial photographs and satellite imagery

    NASA Astrophysics Data System (ADS)

    Shekede, Munyaradzi D.; Murwira, Amon; Masocha, Mhosisi

    2015-03-01

    Although increased woody plant abundance has been reported in tropical savannas worldwide, techniques for detecting the direction and magnitude of change are mostly based on visual interpretation of historical aerial photography or textural analysis of multi-temporal satellite images. These techniques are prone to human error and do not permit integration of remotely sensed data from diverse sources. Here, we integrate aerial photographs with high spatial resolution satellite imagery and use a discrete wavelet transform to objectively detect the dynamics in bush encroachment at two protected Zimbabwean savanna sites. Based on the recently introduced intensity-dominant scale approach, we test the hypotheses that: (1) the encroachment of woody patches into the surrounding grassland matrix causes a shift in the dominant scale. This shift in the dominant scale can be detected using a discrete wavelet transform regardless of whether aerial photography and satellite data are used; and (2) as the woody patch size stabilises, woody cover tends to increase thereby triggering changes in intensity. The results show that at the first site where tree patches were already established (Lake Chivero Game Reserve), between 1972 and 1984 the dominant scale of woody patches initially increased from 8 m before stabilising at 16 m and 32 m between 1984 and 2012 while the intensity fluctuated during the same period. In contrast, at the second site, which was formely grass-dominated site (Kyle Game Reserve), we observed an unclear dominant scale (1972) which later becomes distinct in 1985, 1996 and 2012. Over the same period, the intensity increased. Our results imply that using our approach we can detect and quantify woody/bush patch dynamics in savanna landscapes.

  15. Automatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models

    NASA Astrophysics Data System (ADS)

    Abayowa, Bernard O.; Yilmaz, Alper; Hardie, Russell C.

    2015-08-01

    This paper presents a framework for automatic registration of both the optical and 3D structural information extracted from oblique aerial imagery to a Light Detection and Ranging (LiDAR) point cloud without prior knowledge of an initial alignment. The framework employs a coarse to fine strategy in the estimation of the registration parameters. First, a dense 3D point cloud and the associated relative camera parameters are extracted from the optical aerial imagery using a state-of-the-art 3D reconstruction algorithm. Next, a digital surface model (DSM) is generated from both the LiDAR and the optical imagery-derived point clouds. Coarse registration parameters are then computed from salient features extracted from the LiDAR and optical imagery-derived DSMs. The registration parameters are further refined using the iterative closest point (ICP) algorithm to minimize global error between the registered point clouds. The novelty of the proposed approach is in the computation of salient features from the DSMs, and the selection of matching salient features using geometric invariants coupled with Normalized Cross Correlation (NCC) match validation. The feature extraction and matching process enables the automatic estimation of the coarse registration parameters required for initializing the fine registration process. The registration framework is tested on a simulated scene and aerial datasets acquired in real urban environments. Results demonstrates the robustness of the framework for registering optical and 3D structural information extracted from aerial imagery to a LiDAR point cloud, when co-existing initial registration parameters are unavailable.

  16. Forest and land inventory using ERTS imagery and aerial photography in the boreal forest region of Alberta, Canada

    NASA Technical Reports Server (NTRS)

    Kirby, C. L.

    1974-01-01

    Satellite imagery and small-scale (1:120,000) infrared ektachrome aerial photography for the development of improved forest and land inventory techniques in the boreal forest region are presented to demonstrate spectral signatures and their application. The forest is predominately mixed, stands of white spruce and poplar, with some pure stands of black spruce, pine and large areas of poorly drained land with peat and sedge type muskegs. This work is part of coordinated program to evaluate ERTS imagery by the Canadian Forestry Service.

  17. Geomorphological relationships through the use of 2-D seismic reflection data, Lidar, and aerial imagery

    NASA Astrophysics Data System (ADS)

    Alesce, Meghan Elizabeth

    Barrier Islands are crucial in protecting coastal environments. This study focuses on Dauphin Island, Alabama, located within the Northern Gulf of Mexico (NGOM) Barrier Island complex. It is one of many islands serving as natural protection for NGOM ecosystems and coastal cities. The NGOM barrier islands formed at 4 kya in response to a decrease in rate of sea level rise. The morphology of these islands changes with hurricanes, anthropogenic activity, and tidal and wave action. This study focuses on ancient incised valleys and and the impact on island morphology on hurricane breaches. Using high frequency 2-D seismic reflection data four horizons, including the present seafloor, were interpreted. Subaerial portions of Dauphin Island were imaged using Lidar data and aerial imagery over a ten-year time span, as well as historical maps. Historical shorelines of Dauphin Island were extracted from aerial imagery and historical maps, and were compared to the location of incised valleys seen within the 2-D seismic reflection data. Erosion and deposition volumes of Dauphin Island from 1998 to 2010 (the time span covering hurricanes Ivan and Katrina) in the vicinity of Katrina Cut and Pelican Island were quantified using Lidar data. For the time period prior to Hurricane Ivan an erosional volume of 46,382,552 m3 and depositional volume of 16,113.6 m3 were quantified from Lidar data. The effects of Hurricane Ivan produced a total erosion volume of 4,076,041.5 m3. The erosional and depositional volumes of Katrina Cut being were 7,562,068.5 m3 and 510,936.7 m3, respectively. More volume change was found within Pelican Pass. For the period between hurricanes Ivan and Katrina the erosion volume was 595,713.8 m3. This was mostly located within Katrina Cut. Total deposition for the same period, including in Pelican Pass, was 15,353,961 m3. Hurricane breaches were compared to ancient incised valleys seen within the 2-D seismic reflection results. Breaches from hurricanes from 1849

  18. Outlier and target detection in aerial hyperspectral imagery: a comparison of traditional and percentage occupancy hit or miss transform techniques

    NASA Astrophysics Data System (ADS)

    Young, Andrew; Marshall, Stephen; Gray, Alison

    2016-05-01

    The use of aerial hyperspectral imagery for the purpose of remote sensing is a rapidly growing research area. Currently, targets are generally detected by looking for distinct spectral features of the objects under surveillance. For example, a camouflaged vehicle, deliberately designed to blend into background trees and grass in the visible spectrum, can be revealed using spectral features in the near-infrared spectrum. This work aims to develop improved target detection methods, using a two-stage approach, firstly by development of a physics-based atmospheric correction algorithm to convert radiance into re ectance hyperspectral image data and secondly by use of improved outlier detection techniques. In this paper the use of the Percentage Occupancy Hit or Miss Transform is explored to provide an automated method for target detection in aerial hyperspectral imagery.

  19. Integrating Terrestrial LIDAR with Point Clouds Created from Unmanned Aerial Vehicle Imagery

    NASA Astrophysics Data System (ADS)

    Leslar, M.

    2015-08-01

    Using unmanned aerial vehicles (UAV) for the purposes of conducting high-accuracy aerial surveying has become a hot topic over the last year. One of the most promising means of conducting such a survey involves integrating a high-resolution non-metric digital camera with the UAV and using the principals of digital photogrammetry to produce high-density colorized point clouds. Through the use of stereo imagery, precise and accurate horizontal positioning information can be produced without the need for integration with any type of inertial navigation system (INS). Of course, some form of ground control is needed to achieve this result. Terrestrial LiDAR, either static or mobile, provides the solution. Points extracted from Terrestrial LiDAR can be used as control in the digital photogrammetry solution required by the UAV. In return, the UAV is an affordable solution for filling in the shadows and occlusions typically experienced by Terrestrial LiDAR. In this paper, the accuracies of points derived from a commercially available UAV solution will be examined and compared to the accuracies achievable by a commercially available LIDAR solution. It was found that the LiDAR system produced a point cloud that was twice as accurate as the point cloud produced by the UAV's photogrammetric solution. Both solutions gave results within a few centimetres of the control field. In addition the about of planar dispersion on the vertical wall surfaces in the UAV point cloud was found to be multiple times greater than that from the horizontal ground based UAV points or the LiDAR data.

  20. Fusing Unmanned Aerial Vehicle Imagery with High Resolution Hydrologic Modeling (Invited)

    NASA Astrophysics Data System (ADS)

    Vivoni, E. R.; Pierini, N.; Schreiner-McGraw, A.; Anderson, C.; Saripalli, S.; Rango, A.

    2013-12-01

    After decades of development and applications, high resolution hydrologic models are now common tools in research and increasingly used in practice. More recently, high resolution imagery from unmanned aerial vehicles (UAVs) that provide information on land surface properties have become available for civilian applications. Fusing the two approaches promises to significantly advance the state-of-the-art in terms of hydrologic modeling capabilities. This combination will also challenge assumptions on model processes, parameterizations and scale as land surface characteristics (~0.1 to 1 m) may now surpass traditional model resolutions (~10 to 100 m). Ultimately, predictions from high resolution hydrologic models need to be consistent with the observational data that can be collected from UAVs. This talk will describe our efforts to develop, utilize and test the impact of UAV-derived topographic and vegetation fields on the simulation of two small watersheds in the Sonoran and Chihuahuan Deserts at the Santa Rita Experimental Range (Green Valley, AZ) and the Jornada Experimental Range (Las Cruces, NM). High resolution digital terrain models, image orthomosaics and vegetation species classification were obtained from a fixed wing airplane and a rotary wing helicopter, and compared to coarser analyses and products, including Light Detection and Ranging (LiDAR). We focus the discussion on the relative improvements achieved with UAV-derived fields in terms of terrain-hydrologic-vegetation analyses and summer season simulations using the TIN-based Real-time Integrated Basin Simulator (tRIBS) model. Model simulations are evaluated at each site with respect to a high-resolution sensor network consisting of six rain gauges, forty soil moisture and temperature profiles, four channel runoff flumes, a cosmic-ray soil moisture sensor and an eddy covariance tower over multiple summer periods. We also discuss prospects for the fusion of high resolution models with novel

  1. Fusion of Multi-View and Multi-Scale Aerial Imagery for Real-Time Situation Awareness Applications

    NASA Astrophysics Data System (ADS)

    Zhuo, X.; Kurz, F.; Reinartz, P.

    2015-08-01

    Manned aircraft has long been used for capturing large-scale aerial images, yet the high costs and weather dependence restrict its availability in emergency situations. In recent years, MAV (Micro Aerial Vehicle) emerged as a novel modality for aerial image acquisition. Its maneuverability and flexibility enable a rapid awareness of the scene of interest. Since these two platforms deliver scene information from different scale and different view, it makes sense to fuse these two types of complimentary imagery to achieve a quick, accurate and detailed description of the scene, which is the main concern of real-time situation awareness. This paper proposes a method to fuse multi-view and multi-scale aerial imagery by establishing a common reference frame. In particular, common features among MAV images and geo-referenced airplane images can be extracted by a scale invariant feature detector like SIFT. From the tie point of geo-referenced images we derive the coordinate of corresponding ground points, which are then utilized as ground control points in global bundle adjustment of MAV images. In this way, the MAV block is aligned to the reference frame. Experiment results show that this method can achieve fully automatic geo-referencing of MAV images even if GPS/IMU acquisition has dropouts, and the orientation accuracy is improved compared to the GPS/IMU based georeferencing. The concept for a subsequent 3D classification method is also described in this paper.

  2. Discrimination of Deciduous Tree Species from Time Series of Unmanned Aerial System Imagery.

    PubMed

    Lisein, Jonathan; Michez, Adrien; Claessens, Hugues; Lejeune, Philippe

    2015-01-01

    Technology advances can revolutionize Precision Forestry by providing accurate and fine forest information at tree level. This paper addresses the question of how and particularly when Unmanned Aerial System (UAS) should be used in order to efficiently discriminate deciduous tree species. The goal of this research is to determine when is the best time window to achieve an optimal species discrimination. A time series of high resolution UAS imagery was collected to cover the growing season from leaf flush to leaf fall. Full benefit was taken of the temporal resolution of UAS acquisition, one of the most promising features of small drones. The disparity in forest tree phenology is at the maximum during early spring and late autumn. But the phenology state that optimized the classification result is the one that minimizes the spectral variation within tree species groups and, at the same time, maximizes the phenologic differences between species. Sunlit tree crowns (5 deciduous species groups) were classified using a Random Forest approach for monotemporal, two-date and three-date combinations. The end of leaf flushing was the most efficient single-date time window. Multitemporal datasets definitely improve the overall classification accuracy. But single-date high resolution orthophotomosaics, acquired on optimal time-windows, result in a very good classification accuracy (overall out of bag error of 16%).

  3. Discrimination of Deciduous Tree Species from Time Series of Unmanned Aerial System Imagery.

    PubMed

    Lisein, Jonathan; Michez, Adrien; Claessens, Hugues; Lejeune, Philippe

    2015-01-01

    Technology advances can revolutionize Precision Forestry by providing accurate and fine forest information at tree level. This paper addresses the question of how and particularly when Unmanned Aerial System (UAS) should be used in order to efficiently discriminate deciduous tree species. The goal of this research is to determine when is the best time window to achieve an optimal species discrimination. A time series of high resolution UAS imagery was collected to cover the growing season from leaf flush to leaf fall. Full benefit was taken of the temporal resolution of UAS acquisition, one of the most promising features of small drones. The disparity in forest tree phenology is at the maximum during early spring and late autumn. But the phenology state that optimized the classification result is the one that minimizes the spectral variation within tree species groups and, at the same time, maximizes the phenologic differences between species. Sunlit tree crowns (5 deciduous species groups) were classified using a Random Forest approach for monotemporal, two-date and three-date combinations. The end of leaf flushing was the most efficient single-date time window. Multitemporal datasets definitely improve the overall classification accuracy. But single-date high resolution orthophotomosaics, acquired on optimal time-windows, result in a very good classification accuracy (overall out of bag error of 16%). PMID:26600422

  4. Random Forest and Objected-Based Classification for Forest Pest Extraction from Uav Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Yuan, Yi; Hu, Xiangyun

    2016-06-01

    Forest pest is one of the most important factors affecting the health of forest. However, since it is difficult to figure out the pest areas and to predict the spreading ways just to partially control and exterminate it has not effective enough so far now. The infected areas by it have continuously spreaded out at present. Thus the introduction of spatial information technology is highly demanded. It is very effective to examine the spatial distribution characteristics that can establish timely proper strategies for control against pests by periodically figuring out the infected situations as soon as possible and by predicting the spreading ways of the infection. Now, with the UAV photography being more and more popular, it has become much cheaper and faster to get UAV images which are very suitable to be used to monitor the health of forest and detect the pest. This paper proposals a new method to effective detect forest pest in UAV aerial imagery. For an image, we segment it to many superpixels at first and then we calculate a 12-dimension statistical texture information for each superpixel which are used to train and classify the data. At last, we refine the classification results by some simple rules. The experiments show that the method is effective for the extraction of forest pest areas in UAV images.

  5. Discrimination of Deciduous Tree Species from Time Series of Unmanned Aerial System Imagery

    PubMed Central

    Lisein, Jonathan; Michez, Adrien; Claessens, Hugues; Lejeune, Philippe

    2015-01-01

    Technology advances can revolutionize Precision Forestry by providing accurate and fine forest information at tree level. This paper addresses the question of how and particularly when Unmanned Aerial System (UAS) should be used in order to efficiently discriminate deciduous tree species. The goal of this research is to determine when is the best time window to achieve an optimal species discrimination. A time series of high resolution UAS imagery was collected to cover the growing season from leaf flush to leaf fall. Full benefit was taken of the temporal resolution of UAS acquisition, one of the most promising features of small drones. The disparity in forest tree phenology is at the maximum during early spring and late autumn. But the phenology state that optimized the classification result is the one that minimizes the spectral variation within tree species groups and, at the same time, maximizes the phenologic differences between species. Sunlit tree crowns (5 deciduous species groups) were classified using a Random Forest approach for monotemporal, two-date and three-date combinations. The end of leaf flushing was the most efficient single-date time window. Multitemporal datasets definitely improve the overall classification accuracy. But single-date high resolution orthophotomosaics, acquired on optimal time-windows, result in a very good classification accuracy (overall out of bag error of 16%). PMID:26600422

  6. 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

  7. Low-Level Tie Feature Extraction of Mobile Mapping Data (mls/images) and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Jende, P.; Hussnain, Z.; Peter, M.; Oude Elberink, S.; Gerke, M.; Vosselman, G.

    2016-03-01

    Mobile Mapping (MM) is a technique to obtain geo-information using sensors mounted on a mobile platform or vehicle. The mobile platform's position is provided by the integration of Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). However, especially in urban areas, building structures can obstruct a direct line-of-sight between the GNSS receiver and navigation satellites resulting in an erroneous position estimation. Therefore, derived MM data products, such as laser point clouds or images, lack the expected positioning reliability and accuracy. This issue has been addressed by many researchers, whose aim to mitigate these effects mainly concentrates on utilising tertiary reference data. However, current approaches do not consider errors in height, cannot achieve sub-decimetre accuracy and are often not designed to work in a fully automatic fashion. We propose an automatic pipeline to rectify MM data products by employing high resolution aerial nadir and oblique imagery as horizontal and vertical reference, respectively. By exploiting the MM platform's defective, and therefore imprecise but approximate orientation parameters, accurate feature matching techniques can be realised as a pre-processing step to minimise the MM platform's three-dimensional positioning error. Subsequently, identified correspondences serve as constraints for an orientation update, which is conducted by an estimation or adjustment technique. Since not all MM systems employ laser scanners and imaging sensors simultaneously, and each system and data demands different approaches, two independent workflows are developed in parallel. Still under development, both workflows will be presented and preliminary results will be shown. The workflows comprise of three steps; feature extraction, feature matching and the orientation update. In this paper, initial results of low-level image and point cloud feature extraction methods will be discussed as well as an outline of

  8. A temporal and ecological analysis of the Huntington Beach Wetlands through an unmanned aerial system remote sensing perspective

    NASA Astrophysics Data System (ADS)

    Rafiq, Talha

    Wetland monitoring and preservation efforts have the potential to be enhanced with advanced remote sensing acquisition and digital image analysis approaches. Progress in the development and utilization of Unmanned Aerial Systems (UAS) and Unmanned Aerial Vehicles (UAV) as remote sensing platforms has offered significant spatial and temporal advantages over traditional aerial and orbital remote sensing platforms. Photogrammetric approaches to generate high spatial resolution orthophotos of UAV acquired imagery along with the UAV's low-cost and temporally flexible characteristics are explored. A comparative analysis of different spectral based land cover maps derived from imagery captured using UAV, satellite, and airplane platforms provide an assessment of the Huntington Beach Wetlands. This research presents a UAS remote sensing methodology encompassing data collection, image processing, and analysis in constructing spectral based land cover maps to augment the efforts of the Huntington Beach Wetlands Conservancy by assessing ecological and temporal changes at the Huntington Beach Wetlands.

  9. Intergration of LiDAR Data with Aerial Imagery for Estimating Rooftop Solar Photovoltaic Potentials in City of Cape Town

    NASA Astrophysics Data System (ADS)

    Adeleke, A. K.; Smit, J. L.

    2016-06-01

    Apart from the drive to reduce carbon dioxide emissions by carbon-intensive economies like South Africa, the recent spate of electricity load shedding across most part of the country, including Cape Town has left electricity consumers scampering for alternatives, so as to rely less on the national grid. Solar energy, which is adequately available in most part of Africa and regarded as a clean and renewable source of energy, makes it possible to generate electricity by using photovoltaics technology. However, before time and financial resources are invested into rooftop solar photovoltaic systems in urban areas, it is important to evaluate the potential of the building rooftop, intended to be used in harvesting the solar energy. This paper presents methodologies making use of LiDAR data and other ancillary data, such as high-resolution aerial imagery, to automatically extract building rooftops in City of Cape Town and evaluate their potentials for solar photovoltaics systems. Two main processes were involved: (1) automatic extraction of building roofs using the integration of LiDAR data and aerial imagery in order to derive its' outline and areal coverage; and (2) estimating the global solar radiation incidence on each roof surface using an elevation model derived from the LiDAR data, in order to evaluate its solar photovoltaic potential. This resulted in a geodatabase, which can be queried to retrieve salient information about the viability of a particular building roof for solar photovoltaic installation.

  10. Decision Level Fusion of LIDAR Data and Aerial Color Imagery Based on Bayesian Theory for Urban Area Classification

    NASA Astrophysics Data System (ADS)

    Rastiveis, H.

    2015-12-01

    Airborne Light Detection and Ranging (LiDAR) generates high-density 3D point clouds to provide a comprehensive information from object surfaces. Combining this data with aerial/satellite imagery is quite promising for improving land cover classification. In this study, fusion of LiDAR data and aerial imagery based on Bayesian theory in a three-level fusion algorithm is presented. In the first level, pixel-level fusion, the proper descriptors for both LiDAR and image data are extracted. In the next level of fusion, feature-level, using extracted features the area are classified into six classes of "Buildings", "Trees", "Asphalt Roads", "Concrete roads", "Grass" and "Cars" using Naïve Bayes classification algorithm. This classification is performed in three different strategies: (1) using merely LiDAR data, (2) using merely image data, and (3) using all extracted features from LiDAR and image. The results of three classifiers are integrated in the last phase, decision level fusion, based on Naïve Bayes algorithm. To evaluate the proposed algorithm, a high resolution color orthophoto and LiDAR data over the urban areas of Zeebruges, Belgium were applied. Obtained results from the decision level fusion phase revealed an improvement in overall accuracy and kappa coefficient.

  11. Detection of two intermixed invasive woody species using color infrared aerial imagery and the support vector machine classifier

    NASA Astrophysics Data System (ADS)

    Mirik, Mustafa; Chaudhuri, Sriroop; Surber, Brady; Ale, Srinivasulu; James Ansley, R.

    2013-01-01

    Both the evergreen redberry juniper (Juniperus pinchotii Sudw.) and deciduous honey mesquite (Prosopis glandulosa Torr.) are destructive and aggressive invaders that affect rangelands and grasslands of the southern Great Plains of the United States. However, their current spatial extent and future expansion trends are unknown. This study was aimed at: (1) exploring the utility of aerial imagery for detecting and mapping intermixed redberry juniper and honey mesquite while both are in full foliage using the support vector machine classifier at two sites in north central Texas and, (2) assessing and comparing the mapping accuracies between sites. Accuracy assessments revealed that the overall accuracies were 90% with the associated kappa coefficient of 0.86% and 89% with the associated kappa coefficient of 0.85 for sites 1 and 2, respectively. Z-statistics (0.102<1.96) used to compare the classification results for both sites indicated an insignificant difference between classifications at 95% probability level. In most instances, juniper and mesquite were identified correctly with <7% being mistaken for the other woody species. These results indicated that assessment of the current infestation extent and severity of these two woody species in a spatial context is possible using aerial remote sensing imagery.

  12. Using high-resolution digital aerial imagery to map land cover

    USGS Publications Warehouse

    Dieck, J.J.; Robinson, Larry

    2014-01-01

    The Upper Midwest Environmental Sciences Center (UMESC) has used aerial photography to map land cover/land use on federally owned and managed lands for over 20 years. Until recently, that process used 23- by 23-centimeter (9- by 9-inch) analog aerial photos to classify vegetation along the Upper Mississippi River System, on National Wildlife Refuges, and in National Parks. With digital aerial cameras becoming more common and offering distinct advantages over analog film, UMESC transitioned to an entirely digital mapping process in 2009. Though not without challenges, this method has proven to be much more accurate and efficient when compared to the analog process.

  13. Preliminary statistical studies concerning the Campos RJ sugar cane area, using LANDSAT imagery and aerial photographs

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Costa, S. R. X.; Paiao, L. B. F.; Mendonca, F. J.; Shimabukuro, Y. E.; Duarte, V.

    1983-01-01

    The two phase sampling technique was applied to estimate the area cultivated with sugar cane in an approximately 984 sq km pilot region of Campos. Correlation between existing aerial photography and LANDSAT data was used. The two phase sampling technique corresponded to 99.6% of the results obtained by aerial photography, taken as ground truth. This estimate has a standard deviation of 225 ha, which constitutes a coefficient of variation of 0.6%.

  14. Automatic Road Extraction Based on Integration of High Resolution LIDAR and Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Rahimi, S.; Arefi, H.; Bahmanyar, R.

    2015-12-01

    In recent years, the rapid increase in the demand for road information together with the availability of large volumes of high resolution Earth Observation (EO) images, have drawn remarkable interest to the use of EO images for road extraction. Among the proposed methods, the unsupervised fully-automatic ones are more efficient since they do not require human effort. Considering the proposed methods, the focus is usually to improve the road network detection, while the roads' precise delineation has been less attended to. In this paper, we propose a new unsupervised fully-automatic road extraction method, based on the integration of the high resolution LiDAR and aerial images of a scene using Principal Component Analysis (PCA). This method discriminates the existing roads in a scene; and then precisely delineates them. Hough transform is then applied to the integrated information to extract straight lines; which are further used to segment the scene and discriminate the existing roads. The roads' edges are then precisely localized using a projection-based technique, and the round corners are further refined. Experimental results demonstrate that our proposed method extracts and delineates the roads with a high accuracy.

  15. Using Unmanned Aerial Vehicle (UAV) Imagery to Investigate Surface Displacements and Surface Features of the Super-Sauze Earthflow (France)

    NASA Astrophysics Data System (ADS)

    James, M. R.; Tizzard, S.; Niethammer, U.

    2014-12-01

    We present the result of using imagery collected with a small rotary wing UAV (unmanned aerial vehicle) to investigate surface displacements and fissures on the Super-Sauze earthflow (France); a slow moving earthflow with the potential to develop into rapid and highly destructive mud flows. UAV imagery acquired in October 2009 was processed using a structure-from-motion and multi-view stereo (SfM-MVS) approach in PhotoScan software. Identification of ~200 ground control points throughout the image set was facilitated by automated image matching in SfM_georef software[1] and the data incorporated into PhotoScan for network optimisation and georeferencing. The completed 2009 model enabled an ~5 cm spatial resolution orthoimage to be generated with an expected accuracy (based on residuals on control) of ~0.3 m. This was supported by comparison to a previously created 2008 model, which gave standard deviations on tie points (located on stationary terrain) of 0.27 m and 0.43 m in Easting and Northing respectively. The high resolution of the orthoimage allowed an investigation into surface displacements and geomorphology of surface features (compared to the 2008 model). The results have produced a comprehensive surface displacement map of the Super-Sauze earthflow, as well as highlighting interesting variations in fissure geomorphology and density between the 2008 and 2009 models. This study underscored the capability for UAV imagery and SfM-MVS to generate highly detailed orthographic imagery and DEMs with a low cost approach that offers significant potential for landslide hazard assessments. [1] http://www.lancaster.ac.uk/staff/jamesm/software/sfm_georef.htm

  16. Automated identification of rivers and shorelines in aerial imagery using image texture

    NASA Astrophysics Data System (ADS)

    McKay, Paul; Blain, Cheryl Ann; Linzell, Robert

    2011-06-01

    A method has been developed which automatically extracts river and river bank locations from arbitrarily sourced high resolution (~1m) visual spectrum imagery without recourse to multi-spectral or even color information. This method relies on quantifying the difference in image texture between the relatively smooth surface of the river water and the rougher surface of the vegetated land or built environment bordering it and then segmenting the image into high and low roughness regions. The edges of the low roughness regions then define the river banks. The method can be coded in any language without recourse to proprietary tools and requires minimal operator intervention. As this sort of imagery is increasingly being made freely available through such services as Google Earth or Worldwind this technique can be used to extract river features when more specialized imagery or software is not available.

  17. Characterizing Sediment Flux Using Reconstructed Topography and Bathymetry from Historical Aerial Imagery on the Willamette River, OR.

    NASA Astrophysics Data System (ADS)

    Langston, T.; Fonstad, M. A.

    2014-12-01

    The Willamette is a gravel-bed river that drains ~28,800 km^2 between the Coast Range and Cascade Range in northwestern Oregon before entering the Columbia River near Portland. In the last 150 years, natural and anthropogenic drivers have altered the sediment transport regime, drastically reducing the geomorphic complexity of the river. Previously dynamic multi-threaded reaches have transformed into stable single channels to the detriment of ecosystem diversity and productivity. Flow regulation by flood-control dams, bank revetments, and conversion of riparian forests to agriculture have been key drivers of channel change. To date, little has been done to quantitatively describe temporal and spatial trends of sediment transport in the Willamette. This knowledge is critical for understanding how modern processes shape landforms and habitats. The goal of this study is to describe large-scale temporal and spatial trends in the sediment budget by reconstructing historical topography and bathymetry from aerial imagery. The area of interest for this project is a reach of the Willamette stretching from the confluence of the McKenzie River to the town of Peoria. While this reach remains one of the most dynamic sections of the river, it has exhibited a great loss in geomorphic complexity. Aerial imagery for this section of the river is available from USDA and USACE projects dating back to the 1930's. Above water surface elevations are extracted using the Imagine Photogrammetry package in ERDAS. Bathymetry is estimated using a method known as Hydraulic Assisted Bathymetry in which hydraulic parameters are used to develop a regression between water depth and pixel values. From this, pixel values are converted to depth below the water surface. Merged together, topography and bathymetry produce a spatially continuous digital elevation model of the geomorphic floodplain. Volumetric changes in sediment stored along the study reach are then estimated for different historic periods

  18. 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.

  19. [Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

    PubMed

    Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

    2015-05-01

    This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

  20. [Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

    PubMed

    Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

    2015-05-01

    This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest. PMID:26571671

  1. Monitoring a BLM level 5 watershed with very-large aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A fifth order BLM watershed in central Wyoming was flown using a Sport-airplane to acquire high-resolution aerial images from 2 cameras at 2 altitudes. Project phases 1 and 2 obtained images for measuring ground cover, species composition and canopy cover of Wyoming big sagebrush by ecological site....

  2. Surface Temperature Mapping of the University of Northern Iowa Campus Using High Resolution Thermal Infrared Aerial Imageries

    PubMed Central

    Savelyev, Alexander; Sugumaran, Ramanathan

    2008-01-01

    The goal of this project was to map the surface temperature of the University of Northern Iowa campus using high-resolution thermal infrared aerial imageries. A thermal camera with a spectral bandwidth of 3.0-5.0 μm was flown at the average altitude of 600 m, achieving ground resolution of 29 cm. Ground control data was used to construct the pixel- to-temperature conversion model, which was later used to produce temperature maps of the entire campus and also for validation of the model. The temperature map then was used to assess the building rooftop conditions and steam line faults in the study area. Assessment of the temperature map revealed a number of building structures that may be subject to insulation improvement due to their high surface temperatures leaks. Several hot spots were also identified on the campus for steam pipelines faults. High-resolution thermal infrared imagery proved highly effective tool for precise heat anomaly detection on the campus, and it can be used by university facility services for effective future maintenance of buildings and grounds.

  3. Analysis by gender and Visual Imagery Reactivity of conventional and imagery Rorschach.

    PubMed

    Yanovski, A; Menduke, H; Albertson, M G

    1995-06-01

    Examined here are the effects of gender and Visual Imagery Reactivity in 80 consecutively selected psychiatric outpatients. The participants were grouped by gender and by the amounts of responsiveness to preceding therapy work using imagery (Imagery Nonreactors and Reactors). In the group of Imagery Nonreactors were 13 men and 22 women, and in the Reactor group were 17 men and 28 women. Compared were the responses to standard Rorschach (Conventional condition) with visual associations to memory images of Rorschach inkblots (Imagery condition). Responses were scored using the Visual Imagery Reactivity (VIR) scoring system, a general, test-nonspecific scoring method. Nonparametric statistical analysis showed that critical indicators of Imagery Reactivity encoded as High Affect/Conflict score and its derivatives associated with sexual or bizarre content were not significantly associated with gender; neither was Neutral Content score which categorizes "non-Reactivity." These results support the notion that system's criteria of Visual Imagery Reactivity can be applied equally to both men and women for the classification of Imagery Reactors and Nonreactors. Discussed are also the speculative consequences of extending the tolerance range of significance levels for the interaction between Reactivity and sex above the customary limit of p < .05 in borderline cases. The results of such an analysis may imply a trend towards more rigid defensiveness under Imagery and toward lesser verbal productivity in response to either the Conventional or the Imagery task among women who are Nonreactors. In Reactors, men produced significantly more Sexual Reference scores (in the subcategory not associated with High Affect/Conflict) than women, but this could be attributed to the effect of tester's and subjects' gender combined.

  4. 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.

  5. 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

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

    PubMed

    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.

  7. 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.

  8. 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.

  9. 3D Building Modeling and Reconstruction using Photometric Satellite and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Izadi, Mohammad

    In this thesis, the problem of three dimensional (3D) reconstruction of building models using photometric satellite and aerial images is investigated. Here, two systems are pre-sented: 1) 3D building reconstruction using a nadir single-view image, and 2) 3D building reconstruction using slant multiple-view aerial images. The first system detects building rooftops in orthogonal aerial/satellite images using a hierarchical segmentation algorithm and a shadow verification approach. The heights of detected buildings are then estimated using a fuzzy rule-based method, which measures the height of a building by comparing its predicted shadow region with the actual shadow evidence in the image. This system finally generated a KML (Keyhole Markup Language) file as the output, that contains 3D models of detected buildings. The second system uses the geolocation information of a scene containing a building of interest and uploads all slant-view images that contain this scene from an input image dataset. These images are then searched automatically to choose image pairs with different views of the scene (north, east, south and west) based on the geolocation and auxiliary data accompanying the input data (metadata that describes the acquisition parameters at the capture time). The camera parameters corresponding to these images are refined using a novel point matching algorithm. Next, the system independently reconstructs 3D flat surfaces that are visible in each view using an iterative algorithm. 3D surfaces generated for all views are combined, and redundant surfaces are removed to create a complete set of 3D surfaces. Finally, the combined 3D surfaces are connected together to generate a more complete 3D model. For the experimental results, both presented systems are evaluated quantitatively and qualitatively and different aspects of the two systems including accuracy, stability, and execution time are discussed.

  10. Mapping Urban Tree Canopy Coverage and Structure using Data Fusion of High Resolution Satellite Imagery and Aerial Lidar

    NASA Astrophysics Data System (ADS)

    Elmes, A.; Rogan, J.; Williams, C. A.; Martin, D. G.; Ratick, S.; Nowak, D.

    2015-12-01

    Urban tree canopy (UTC) coverage is a critical component of sustainable urban areas. Trees provide a number of important ecosystem services, including air pollution mitigation, water runoff control, and aesthetic and cultural values. Critically, urban trees also act to mitigate the urban heat island (UHI) effect by shading impervious surfaces and via evaporative cooling. The cooling effect of urban trees can be seen locally, with individual trees reducing home HVAC costs, and at a citywide scale, reducing the extent and magnitude of an urban areas UHI. In order to accurately model the ecosystem services of a given urban forest, it is essential to map in detail the condition and composition of these trees at a fine scale, capturing individual tree crowns and their vertical structure. This paper presents methods for delineating UTC and measuring canopy structure at fine spatial resolution (<1m). These metrics are essential for modeling the HVAC benefits from UTC for individual homes, and for assessing the ecosystem services for entire urban areas. Such maps have previously been made using a variety of methods, typically relying on high resolution aerial or satellite imagery. This paper seeks to contribute to this growing body of methods, relying on a data fusion method to combine the information contained in high resolution WorldView-3 satellite imagery and aerial lidar data using an object-based image classification approach. The study area, Worcester, MA, has recently undergone a large-scale tree removal and reforestation program, following a pest eradication effort. Therefore, the urban canopy in this location provides a wide mix of tree age class and functional type, ideal for illustrating the effectiveness of the proposed methods. Early results show that the object-based classifier is indeed capable of identifying individual tree crowns, while continued research will focus on extracting crown structural characteristics using lidar-derived metrics. Ultimately

  11. Assessing the accuracy and repeatability of automated photogrammetrically generated digital surface models from unmanned aerial system imagery

    NASA Astrophysics Data System (ADS)

    Chavis, Christopher

    Using commercial digital cameras in conjunction with Unmanned Aerial Systems (UAS) to generate 3-D Digital Surface Models (DSMs) and orthomosaics is emerging as a cost-effective alternative to Light Detection and Ranging (LiDAR). Powerful software applications such as Pix4D and APS can automate the generation of DSM and orthomosaic products from a handful of inputs. However, the accuracy of these models is relatively untested. The objectives of this study were to generate multiple DSM and orthomosaic pairs of the same area using Pix4D and APS from flights of imagery collected with a lightweight UAS. The accuracy of each individual DSM was assessed in addition to the consistency of the method to model one location over a period of time. Finally, this study determined if the DSMs automatically generated using lightweight UAS and commercial digital cameras could be used for detecting changes in elevation and at what scale. Accuracy was determined by comparing DSMs to a series of reference points collected with survey grade GPS. Other GPS points were also used as control points to georeference the products within Pix4D and APS. The effectiveness of the products for change detection was assessed through image differencing and observance of artificially induced, known elevation changes. The vertical accuracy with the optimal data and model is ≈ 25 cm and the highest consistency over repeat flights is a standard deviation of ≈ 5 cm. Elevation change detection based on such UAS imagery and DSM models should be viable for detecting infrastructure change in urban or suburban environments with little dense canopy vegetation.

  12. Mapping potential Blanding's turtle habitat using aerial orthophotographic imagery and object based classification

    NASA Astrophysics Data System (ADS)

    Barker, Rebecca

    Blanding's turtle (Emydoidea blandingii) is a threatened species in southern Quebec that is being inventoried to determine abundance and potential habitat by the Quebec Ministry of Natural Resources and Wildlife. In collaboration with that program and using spring leaf-off aerial orthophotos of Gatineau Park, attributes associated with known habitat criteria were analyzed: wetlands with open water, vegetation mounds for camouflage and thermoregulation, and logs for spring sun-basking. Pixel-based classification to separate wetlands from other land cover types was followed by object-based segmentation and rule-based classification of within--wetland vegetation and logs. Classifications integrated several image characteristics including texture, context, shape, area and spectral attributes. Field data and visual interpretation showed the accuracies of wetland and within wetland habitat feature classifications to be over 82.5%. The wetland classification results were used to develop a ranked potential habitat suitability map for Blanding's turtle that can be employed in conservation planning and management.

  13. Supervised classification of aerial imagery and multi-source data fusion for flood assessment

    NASA Astrophysics Data System (ADS)

    Sava, E.; Harding, L.; Cervone, G.

    2015-12-01

    Floods are among the most devastating natural hazards and the ability to produce an accurate and timely flood assessment before, during, and after an event is critical for their mitigation and response. Remote sensing technologies have become the de-facto approach for observing the Earth and its environment. However, satellite remote sensing data are not always available. For these reasons, it is crucial to develop new techniques in order to produce flood assessments during and after an event. Recent advancements in data fusion techniques of remote sensing with near real time heterogeneous datasets have allowed emergency responders to more efficiently extract increasingly precise and relevant knowledge from the available information. This research presents a fusion technique using satellite remote sensing imagery coupled with non-authoritative data such as Civil Air Patrol (CAP) and tweets. A new computational methodology is proposed based on machine learning algorithms to automatically identify water pixels in CAP imagery. Specifically, wavelet transformations are paired with multiple classifiers, run in parallel, to build models discriminating water and non-water regions. The learned classification models are first tested against a set of control cases, and then used to automatically classify each image separately. A measure of uncertainty is computed for each pixel in an image proportional to the number of models classifying the pixel as water. Geo-tagged tweets are continuously harvested and stored on a MongoDB and queried in real time. They are fused with CAP classified data, and with satellite remote sensing derived flood extent results to produce comprehensive flood assessment maps. The final maps are then compared with FEMA generated flood extents to assess their accuracy. The proposed methodology is applied on two test cases, relative to the 2013 floods in Boulder CO, and the 2015 floods in Texas.

  14. Characterization of Shrubland-Atmosphere Interactions through Use of the Eddy Covariance Method, Distributed Footprint Sampling, and Imagery from Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Anderson, C.; Vivoni, E. R.; Pierini, N.; Robles-Morua, A.; Rango, A.; Laliberte, A.; Saripalli, S.

    2012-12-01

    Ecohydrological dynamics can be evaluated from field observations of land-atmosphere states and fluxes, including water, carbon, and energy exchanges measured through the eddy covariance method. In heterogeneous landscapes, the representativeness of these measurements is not well understood due to the variable nature of the sampling footprint and the mixture of underlying herbaceous, shrub, and soil patches. In this study, we integrate new field techniques to understand how ecosystem surface states are related to turbulent fluxes in two different semiarid shrubland settings in the Jornada (New Mexico) and Santa Rita (Arizona) Experimental Ranges. The two sites are characteristic of Chihuahuan (NM) and Sonoran (AZ) Desert mixed-shrub communities resulting from woody plant encroachment into grassland areas. In each study site, we deployed continuous soil moisture and soil temperature profile observations at twenty sites around an eddy covariance tower after local footprint estimation revealed the optimal sensor network design. We then characterized the tower footprint through terrain and vegetation analyses derived at high resolution (<1 m) from imagery obtained from a fixed-wing and rotary-wing Unmanned Aerial Vehicles (UAV). Our analysis focuses on the summertime land-atmosphere states and fluxes during which each ecosystem responded differentially to the North American monsoon. We found that vegetation heterogeneity induces spatial differences in soil moisture and temperature that are important to capture when relating these states to the eddy covariance flux measurements. Spatial distributions of surface states at different depths reveal intricate patterns linked to vegetation cover that vary between the two sites. Furthermore, single site measurements at the tower are insufficient to capture the footprint conditions and their influence on turbulent fluxes. We also discuss techniques for aggregating the surface states based upon the vegetation and soil

  15. Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots

    PubMed Central

    Lelong, Camille C. D.; Burger, Philippe; Jubelin, Guillaume; Roux, Bruno; Labbé, Sylvain; Baret, Frédéric

    2008-01-01

    This paper outlines how light Unmanned Aerial Vehicles (UAV) can be used in remote sensing for precision farming. It focuses on the combination of simple digital photographic cameras with spectral filters, designed to provide multispectral images in the visible and near-infrared domains. In 2005, these instruments were fitted to powered glider and parachute, and flown at six dates staggered over the crop season. We monitored ten varieties of wheat, grown in trial micro-plots in the South-West of France. For each date, we acquired multiple views in four spectral bands corresponding to blue, green, red, and near-infrared. We then performed accurate corrections of image vignetting, geometric distortions, and radiometric bidirectional effects. Afterwards, we derived for each experimental micro-plot several vegetation indexes relevant for vegetation analyses. Finally, we sought relationships between these indexes and field-measured biophysical parameters, both generic and date-specific. Therefore, we established a robust and stable generic relationship between, in one hand, leaf area index and NDVI and, in the other hand, nitrogen uptake and GNDVI. Due to a high amount of noise in the data, it was not possible to obtain a more accurate model for each date independently. A validation protocol showed that we could expect a precision level of 15% in the biophysical parameters estimation while using these relationships.

  16. Cultivated land information extraction from high-resolution unmanned aerial vehicle imagery data

    NASA Astrophysics Data System (ADS)

    Ma, Lei; Cheng, Liang; Han, Wenquan; Zhong, Lishan; Li, Manchun

    2014-01-01

    The development of precision agriculture demands high accuracy and efficiency of cultivated land information extraction. Simultaneously, unmanned aerial vehicles (UAVs) have been increasingly used for natural resource applications in recent years as a result of their greater availability, the miniaturization of sensors, and the ability to deploy UAVs relatively quickly and repeatedly at low altitudes. We examine the potential of utilizing a small UAV for the characterization, assessment, and monitoring of cultivated land. Because most UAV images lack spectral information, we propose a novel cultivated land information extraction method based on a triangulation for cultivated land information extraction (TCLE) method. Thus, the information on more spatial properties of a region is incorporated into the classification process. The TCLE comprises three main steps: image segmentation, triangulation construction, and triangulation clustering using AUTOCLUST. Experiments were conducted on three UAV images in Deyang, China, using TCLE and eCognition for cultivated land information extraction (ECLE). Experimental results show that TCLE, which does not require training samples and has a much higher level of automation, can obtain accuracies equivalent to ECLE. Comparing with ECLE, TCLE also extracts coherent cultivated land with much less noise. As such, cultivated land information extraction based on high-resolution UAV images can be effectively and efficiently conducted using the proposed method.

  17. Improvement of erosion risk modelling using soil information derived from aerial Vis-NIR imagery

    NASA Astrophysics Data System (ADS)

    Ciampalini, Rossano; Raclot, Damien; Le Bissonnais, Yves

    2016-04-01

    The aim of this research is to test the benefit of the hyperspectral imagery in soil surface properties characterisation for soil erosion modelling purposes. The research area is the Lebna catchment located in the in the north of Tunisia (Cap Bon Region). Soil erosion is evaluated with the use of two different soil erosion models: PESERA (Pan-European Soil Erosion Risk Assessment already used for the soil erosion risk mapping for the European Union, Kirkby et al., 2008) and Mesales (Regional Modelling of Soil Erosion Risk developed by Le Bissonnais et al., 1998, 2002); for that, different sources for soil properties and derived parameters such as soil erodibility map and soil crusting map have been evaluated with use of four different supports: 1) IAO soil map (IAO, 2000), 2) Carte Agricole - CA - (Ministry of Agriculture, Tunisia), 3) Hyperspectral VIS-NIR map - HY - (Gomez et al., 2012; Ciampalini t al., 2012), and, 3) a here developed Hybrid map - CY - integrating information from Hyperspectral VIS-NIR and pedological maps. Results show that the data source has a high influence on the estimation of the parameters for both the models with a more evident sensitivity for Pesera. With regard to the classical pedological data, the VIS-NIR data clearly ameliorates the spatialization of the texture, then, the spatial detail of the results. Differences in the output using different maps are more important in Pesera model than in Mesales showing no-change ranges of about 15 to 41% and 53 to 67%, respectively.

  18. Incorporation of texture, intensity, hue, and saturation for rangeland monitoring with unmanned aircraft imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aerial photography acquired with unmanned aerial vehicles (UAVs) has great potential for incorporation into rangeland health monitoring protocols, and object-based image analysis is well suited for this hyperspatial imagery. A major drawback, however, is the low spectral resolution of the imagery, b...

  19. Knowledge Based 3d Building Model Recognition Using Convolutional Neural Networks from LIDAR and Aerial Imageries

    NASA Astrophysics Data System (ADS)

    Alidoost, F.; Arefi, H.

    2016-06-01

    In recent years, with the development of the high resolution data acquisition technologies, many different approaches and algorithms have been presented to extract the accurate and timely updated 3D models of buildings as a key element of city structures for numerous applications in urban mapping. In this paper, a novel and model-based approach is proposed for automatic recognition of buildings' roof models such as flat, gable, hip, and pyramid hip roof models based on deep structures for hierarchical learning of features that are extracted from both LiDAR and aerial ortho-photos. The main steps of this approach include building segmentation, feature extraction and learning, and finally building roof labeling in a supervised pre-trained Convolutional Neural Network (CNN) framework to have an automatic recognition system for various types of buildings over an urban area. In this framework, the height information provides invariant geometric features for convolutional neural network to localize the boundary of each individual roofs. CNN is a kind of feed-forward neural network with the multilayer perceptron concept which consists of a number of convolutional and subsampling layers in an adaptable structure and it is widely used in pattern recognition and object detection application. Since the training dataset is a small library of labeled models for different shapes of roofs, the computation time of learning can be decreased significantly using the pre-trained models. The experimental results highlight the effectiveness of the deep learning approach to detect and extract the pattern of buildings' roofs automatically considering the complementary nature of height and RGB information.

  20. Orthorectification, mosaicking, and analysis of sub-decimeter resolution UAV imagery for rangeland monitoring

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Unmanned aerial vehicles (UAVs) offer an attractive platform for acquiring imagery for rangeland monitoring. UAVs can be deployed quickly and repeatedly, and they can obtain sub-decimeter resolution imagery at lower image acquisition costs than with piloted aircraft. Low flying heights result in ima...

  1. Aerial Imagery and Other Non-invasive Approaches to Detect Nitrogen and Water Stress in a Potato Crop

    NASA Astrophysics Data System (ADS)

    Nigon, Tyler John

    commercial potato field using aerial imagery. Reference areas were found to be necessary in order to make accurate recommendations because of differences in sensors, potato variety, growth stage, and other local conditions. The results from this study suggest that diagnostic criteria based on both biomass and plant nutrient concentration (e.g., canopy-level spectral reflectance data) were best suited to determine overall crop N status for determination of in-season N fertilizer recommendations.

  2. Error Detection, Factorization and Correction for Multi-View Scene Reconstruction from Aerial Imagery

    SciTech Connect

    Hess-Flores, Mauricio

    2011-11-10

    reconstruction pre-processing, where an algorithm detects and discards frames that would lead to inaccurate feature matching, camera pose estimation degeneracies or mathematical instability in structure computation based on a residual error comparison between two different match motion models. The presented algorithms were designed for aerial video but have been proven to work across different scene types and camera motions, and for both real and synthetic scenes.

  3. Terrestrial and unmanned aerial system imagery for deriving photogrammetric three-dimensional point clouds and volume models of mass wasting sites

    NASA Astrophysics Data System (ADS)

    Hämmerle, Martin; Schütt, Fabian; Höfle, Bernhard

    2016-04-01

    Three-dimensional (3-D) geodata of mass wasting sites are important to model surfaces, volumes, and their changes over time. With a photogrammetric approach commonly known as structure from motion, 3-D point clouds can be derived from image collections in a straightforward way. The quality of point clouds covering a quarry dump derived from terrestrial and aerial imagery is compared and assessed. A comprehensive set of quality indicators is calculated and compared to surveyed reference data and to a terrestrial LiDAR point cloud. The examined indicators are completeness of coverage, point density, vertical accuracy, multiscale point cloud distance, scaling accuracy, and dump volume. It is found that the photogrammetric datasets generally represent the examined dump well with, for example, an area coverage of up to 90% and 100% in case of terrestrial and aerial imagery, respectively, a maximum scaling difference of 0.62%, and volume estimations reaching up to 100% of the LiDAR reference. Combining the advantages of 3-D geodata derived from terrestrial (high detail, accurate volume calculation even with a small number of input images) and aerial images (high coverage) can be a promising method to further improve the quality of 3-D geodata derived with low-cost approaches.

  4. Tree Crown Delineation on Vhr Aerial Imagery with Svm Classification Technique Optimized by Taguchi Method: a Case Study in Zagros Woodlands

    NASA Astrophysics Data System (ADS)

    Erfanifard, Y.; Behnia, N.; Moosavi, V.

    2013-09-01

    The Support Vector Machine (SVM) is a theoretically superior machine learning methodology with great results in classification of remotely sensed datasets. Determination of optimal parameters applied in SVM is still vague to some scientists. In this research, it is suggested to use the Taguchi method to optimize these parameters. The objective of this study was to detect tree crowns on very high resolution (VHR) aerial imagery in Zagros woodlands by SVM optimized by Taguchi method. A 30 ha plot of Persian oak (Quercus persica) coppice trees was selected in Zagros woodlands, Iran. The VHR aerial imagery of the plot with 0.06 m spatial resolution was obtained from National Geographic Organization (NGO), Iran, to extract the crowns of Persian oak trees in this study. The SVM parameters were optimized by Taguchi method and thereafter, the imagery was classified by the SVM with optimal parameters. The results showed that the Taguchi method is a very useful approach to optimize the combination of parameters of SVM. It was also concluded that the SVM method could detect the tree crowns with a KHAT coefficient of 0.961 which showed a great agreement with the observed samples and overall accuracy of 97.7% that showed the accuracy of the final map. Finally, the authors suggest applying this method to optimize the parameters of classification techniques like SVM.

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

    SciTech Connect

    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 by 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.

  6. Regional tsunami vulnerability analysis through ASTER imagery

    NASA Astrophysics Data System (ADS)

    Dall'Osso, Filippo; Cavalletti, Alessandra; Immordino, Francesco; Gonella, Marco

    2010-05-01

    Analysis of vulnerability to natural hazards is a key issue of prevention measures within ICZM. Knowledge of susceptibility to damage and how this is distributed along the coast allows to optimize possible prevention and mitigation actions. The present study focuses on tsunami vulnerability of a large extension of coastline: the entire westerly Thailand's coast. The work is a follow up of the CRATER project (Coastal Risk Analysis for Tsunamis and Environmental Remediation) carried out on the aftermath of the 26th December 2004 Tsunami event. Vulnerability is analyzed considering an inundation scenario given by a tsunami of seismic origin, causing a maximum run-up of 25m.. An innovative methodology have been here developed and applied, based on the combined use of ASTER (Advanced Spaceborn Thermal Emission and Reflection Radiometer) satellite imagery, SRTM v-3 (Shuttle Radar Topography Mission - version #3) DEMs and GIS. Vulnerability level has been calculated combining information on coastal geomorphology, land use, topography and distance from the shoreline. Land use has been extrapolated from ASTER images through a multi-spectral analysis (a pixel-based and supervised classification process) of ASTER bands 1 to 9, plus one band for the NDVI index (Normalized Difference Vegetation Index). Coastal geomorphology has been obtained through a photo-interpretation process. Results have been organized in a set of vectorial vulnerability maps with horizontal resolution of 90m. The proposed methodology has the great advantage of being repeatable for any case of vulnerability analysis at small-medium scale (i.e. at Regional/National level) with a moderate investment in term of costs and human resources.

  7. 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.

  8. An analysis of simulated stereo radar imagery

    NASA Technical Reports Server (NTRS)

    Pisaruck, M. A.; Kaupp, V. H.; Macdonald, H. C.; Waite, W. P.

    1983-01-01

    Simulated stereo radar imagery is used to investigate parameters for a spaceborne imaging radar. Incidence angles ranging from small to intermediate to large are used with three digital terrain model areas which are representative of relatively flat, moderately rough, and mountainous terrain. The simulated radar imagery was evaluated by interpreters for ease of stereo perception and information content, and rank order within each class of terrain. The interpreter's results are analyzed for trends between the height of a feature and either parallax or vertical exaggeration for a stereo pair. A model is developed which predicts the amount of parallax (or vertical exaggeration) an interpreter would desire for best stereo perception of a feature of a specific height. Results indicate the selection of angle of incidence and stereo intersection angle depend upon the relative relief of the terrain. Examples of the simulated stereo imagery are presented for a candidate spaceborne imaging radar having four selectable angles of incidence.

  9. A Vegetation Analysis on Horn Island Mississippi, ca. 1940 using Habitat Characteristic Dimensions Derived from Historical Aerial Photography

    NASA Astrophysics Data System (ADS)

    Jeter, G. W.; Carter, G. A.

    2013-12-01

    Guy (Will) Wilburn Jeter Jr., Gregory A. Carter University of Southern Mississippi Geography and Geology Gulf Coast Geospatial Center The over-arching goal of this research is to assess habitat change over a seventy year period to better understand the combined effects of global sea level rise and storm impacts on the stability of Horn Island, MS habitats. Historical aerial photography is often overlooked as a resource for use in determining habitat change. However, the spatial information provided even by black and white imagery can give insight into past habitat composition via textural analysis. This research will evaluate characteristic dimensions; most notably patch size of habitat types using simple geo-statistics and textures of brightness values of historical aerial imagery. It is assumed that each cover type has an identifiable patch size that can be used as a unique classifier of each habitat type. Analytical methods applied to the 1940 imagery were developed using 2010 field data and USDA aerial imagery. Textural moving window methods and basic geo-statistics were used to estimate characteristic dimensions of each cover type in 1940 aerial photography. The moving window texture analysis was configured with multiple window sizes to capture the characteristic dimensions of six habitat types; water, bare sand , dune herb land, estuarine shrub land, marsh land and slash pine woodland. Coefficient of variation (CV), contrast, and entropy texture filters were used to analyze the spatial variability of the 1940 and 2010 imagery. (CV) was used to depict the horizontal variability of each habitat characteristic dimension. Contrast was used to represent the variability of bright versus dark pixel values; entropy was used to show the variation in the slash pine woodland habitat type. Results indicate a substantial increase in marshland habitat relative to other habitat types since 1940. Results also reveal each habitat-type, such as dune herb-land, marsh

  10. A color prediction model for imagery analysis

    NASA Technical Reports Server (NTRS)

    Skaley, J. E.; Fisher, J. R.; Hardy, E. E.

    1977-01-01

    A simple model has been devised to selectively construct several points within a scene using multispectral imagery. The model correlates black-and-white density values to color components of diazo film so as to maximize the color contrast of two or three points per composite. The CIE (Commission Internationale de l'Eclairage) color coordinate system is used as a quantitative reference to locate these points in color space. Superimposed on this quantitative reference is a perceptional framework which functionally contrasts color values in a psychophysical sense. This methodology permits a more quantitative approach to the manual interpretation of multispectral imagery while resulting in improved accuracy and lower costs.

  11. Stream network analysis from orbital and suborbital imagery, Colorado River Basin, Texas

    NASA Technical Reports Server (NTRS)

    Baker, V. R. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. Orbital SL-2 imagery (earth terrain camera S-190B), received September 5, 1973, was subjected to quantitative network analysis and compared to 7.5 minute topographic mapping (scale: 1/24,000) and U.S.D.A. conventional black and white aerial photography (scale: 1/22,200). Results can only be considered suggestive because detail on the SL-2 imagery was badly obscured by heavy cloud cover. The upper Bee Creek basin was chosen for analysis because it appeared in a relatively cloud-free portion of the orbital imagery. Drainage maps were drawn from the three sources digitized into a computer-compatible format, and analyzed by the WATER system computer program. Even at its small scale (1/172,000) and with bad haze the orbital photo showed much drainage detail. The contour-like character of the Glen Rose Formation's resistant limestone units allowed channel definition. The errors in pattern recognition can be attributed to local areas of dense vegetation and to other areas of very high albedo caused by surficial exposure of caliche. The latter effect caused particular difficulty in the determination of drainage divides.

  12. Aberration analysis in aerial images formed by lithographic lenses

    NASA Astrophysics Data System (ADS)

    Freitag, Wolfgang; Grossmann, Wilfried; Grunewald, Uwe

    1992-05-01

    A test procedure for the final assembly of lenses that does not need exposed photographic plates is introduced. It is based on the metrological simulation of optical ray tracing. A measuring example illustrates its suitabilty for ultraviolet optical systems in particular. The measuring apparatus displays the distortion vectors directly in the aerial image, gives a wave-front analysis, and performs an analogous distortion analysis.

  13. Dubai 3d Textuerd Mesh Using High Quality Resolution Vertical/oblique Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Tayeb Madani, Adib; Ziad Ahmad, Abdullateef; Christoph, Lueken; Hammadi, Zamzam; Manal Abdullah Sabeal, Manal Abdullah x.

    2016-06-01

    Providing high quality 3D data with reasonable quality and cost were always essential, affording the core data and foundation for developing an information-based decision-making tool of urban environments with the capability of providing decision makers, stakeholders, professionals, and public users with 3D views and 3D analysis tools of spatial information that enables real-world views. Helps and assist in improving users' orientation and also increase their efficiency in performing their tasks related to city planning, Inspection, infrastructures, roads, and cadastre management. In this paper, the capability of multi-view Vexcel UltraCam Osprey camera images is examined to provide a 3D model of building façades using an efficient image-based modeling workflow adopted by commercial software's. The main steps of this work include: Specification, point cloud generation, and 3D modeling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM) is applied on the images to generate point cloud. Then, a mesh model of points is calculated using and refined to obtain an accurate model of buildings. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough LoD2 details of the building based on visual assessment. The objective of this paper is neither comparing nor promoting a specific technique over the other and does not mean to promote a sensor-based system over another systems or mechanism presented in existing or previous paper. The idea is to share experience.

  14. Use of Aerial high resolution visible imagery to produce large river bathymetry: a multi temporal and spatial study over the by-passed Upper Rhine

    NASA Astrophysics Data System (ADS)

    Béal, D.; Piégay, H.; Arnaud, F.; Rollet, A.; Schmitt, L.

    2011-12-01

    Aerial high resolution visible imagery allows producing large river bathymetry assuming that water depth is related to water colour (Beer-Bouguer-Lambert law). In this paper we aim at monitoring Rhine River geometry changes for a diachronic study as well as sediment transport after an artificial injection (25.000 m3 restoration operation). For that a consequent data base of ground measurements of river depth is used, built on 3 different sources: (i) differential GPS acquisitions, (ii) sounder data and (iii) lateral profiles realized by experts. Water depth is estimated using a multi linear regression over neo channels built on a principal component analysis over red, green and blue bands and previously cited depth data. The study site is a 12 km long reach of the by-passed section of the Rhine River that draws French and German border. This section has been heavily impacted by engineering works during the last two centuries: channelization since 1842 for navigation purposes and the construction of a 45 km long lateral canal and 4 consecutive hydroelectric power plants of since 1932. Several bathymetric models are produced based on 3 different spatial resolutions (6, 13 and 20 cm) and 5 acquisitions (January, March, April, August and October) since 2008. Objectives are to find the optimal spatial resolution and to characterize seasonal effects. Best performances according to the 13 cm resolution show a 18 cm accuracy when suspended matters impacted less water transparency. Discussions are oriented to the monitoring of the artificial reload after 2 flood events during winter 2010-2011. Bathymetric models produced are also useful to build 2D hydraulic model's mesh.

  15. Detecting new Buffel grass infestations in Australian arid lands: evaluation of methods using high-resolution multispectral imagery and aerial photography.

    PubMed

    Marshall, V M; Lewis, M M; Ostendorf, B

    2014-03-01

    We assess the feasibility of using airborne imagery for Buffel grass detection in Australian arid lands and evaluate four commonly used image classification techniques (visual estimate, manual digitisation, unsupervised classification and normalised difference vegetation index (NDVI) thresholding) for their suitability to this purpose. Colour digital aerial photography captured at approximately 5 cm of ground sample distance (GSD) and four-band (visible–near-infrared) multispectral imagery (25 cm GSD) were acquired (14 February 2012) across overlapping subsets of our study site. In the field, Buffel grass projected cover estimates were collected for quadrates (10 m diameter), which were subsequently used to evaluate the four image classification techniques. Buffel grass was found to be widespread throughout our study site; it was particularly prevalent in riparian land systems and alluvial plains. On hill slopes, Buffel grass was often present in depressions, valleys and crevices of rock outcrops, but the spread appeared to be dependent on soil type and vegetation communities. Visual cover estimates performed best (r 2 0.39), and pixel-based classifiers (unsupervised classification and NDVI thresholding) performed worst (r 2 0.21). Manual digitising consistently underrepresented Buffel grass cover compared with field- and image-based visual cover estimates; we did not find the labours of digitising rewarding. Our recommendation for regional documentation of new infestation of Buffel grass is to acquire ultra-high-resolution aerial photography and have a trained observer score cover against visual standards and use the scored sites to interpolate density across the region.

  16. 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.

  17. Landslide detection and susceptibility analysis using aerial photographs and weight of evidence

    NASA Astrophysics Data System (ADS)

    Saro, Lee; Hyun-Joo, Oh

    2010-05-01

    susceptibility using GIS. Using landslide location and a spatial database containing information such as topography, soil, forest, geology, lineament and land cover, the weights-of-evidence model was applied to calculate each relevant factor's rating for the Jinbu-myeon area in Korea, which had suffered substantial landslide damage following heavy rain in 2006. In the topographic database, the factors were slope, aspect, curvature, Topographic Wetness Index (TWI) and Stream Power Index (SPI); in the soil database, they were soil texture, soil material, soil drainage, soil effective thickness and topographic type; in the forest map, they were forest type, timber diameter, timber age and forest density; lithology was derived from the geological database; land cover information came from SPOT satellite imagery; and lineament data from hillshade map. For the analysis of mapping landslide susceptibility, W+ and W-, of each factor's rating were overlaid spatially. The result of the analysis was validated using the known landslide locations (30% of total landslide occurrence), which were not used during the training of the weight-of-evidence model. The demonstrated prediction accuracy was 82.82%. Tests of conditional independence were performed for the selection of factors, allowing 17 combinations of factors to be analysed. The combination of slope, aspect, curvature, SPI, lineament, land cover, timber density, soil drainage and topography showed the best results. The results can be used for hazard prevention and land-use planning. The photograph was a time and cost effective to identify landslide prone area in the study area, and the landslide locations were equal to the locations where were checked in the field. In addition, it can help to assess a better understanding of the landslide processes. Keyword: Landslide susceptibility, Digital aerial photograph, GIS, Korea, Weight of evidence.

  18. Aerial videotape mapping of coastal geomorphic changes

    USGS Publications Warehouse

    Debusschere, Karolien; Penland, Shea; Westphal, Karen A.; Reimer, P. Douglas; McBride, Randolph A.

    1991-01-01

    An aerial geomorphic mapping system was developed to examine the spatial and temporal variability in the coastal geomorphology of Louisiana. Between 1984 and 1990 eleven sequential annual and post-hurricane aerial videotape surveys were flown covering periods of prolonged fair weather, hurricane impacts and subsequent post-storm recoveries. A coastal geomorphic classification system was developed to map the spatial and temporal geomorphic changes between these surveys. The classification system is based on 10 years of shoreline monitoring, analysis of aerial photography for 1940-1989, and numerous field surveys. The classification system divides shorelines into two broad classes: natural and altered. Each class consists of several genetically linked categories of shorelines. Each category is further subdivided into morphologic types on the basis of landform relief, elevation, habitat type, vegetation density and type, and sediment characteristics. The classification is used with imagery from the low-altitude, high-resolution aerial videotape surveys to describe and quantify the longshore and cross-shore geomorphic, sedimentologic, and vegetative character of Louisiana's shoreline systems. The mapping system makes it possible to delineate and map detailed geomorphic habitat changes at a resolution higher than that of conventional vertical aerial photography. Morphologic units are mapped parallel to the regional shoreline from the aerial videotape imagery onto the base maps at a scale of 1:24,000. The base maps were constructed from vertical aerial photography concurrent with the data of the video imagery.

  19. Estimating chlorophyll with thermal and broadband multispectral high resolution imagery from an unmanned aerial system using relevance vector machines for precision agriculture

    NASA Astrophysics Data System (ADS)

    Elarab, Manal; Ticlavilca, Andres M.; Torres-Rua, Alfonso F.; Maslova, Inga; McKee, Mac

    2015-12-01

    Precision agriculture requires high-resolution information to enable greater precision in the management of inputs to production. Actionable information about crop and field status must be acquired at high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high spatial resolution imagery was obtained through the use of a small, unmanned aerial system called AggieAirTM. Simultaneously with the AggieAir flights, intensive ground sampling for plant chlorophyll was conducted at precisely determined locations. This study reports the application of a relevance vector machine coupled with cross validation and backward elimination to a dataset composed of reflectance from high-resolution multi-spectral imagery (VIS-NIR), thermal infrared imagery, and vegetative indices, in conjunction with in situ SPAD measurements from which chlorophyll concentrations were derived, to estimate chlorophyll concentration from remotely sensed data at 15-cm resolution. The results indicate that a relevance vector machine with a thin plate spline kernel type and kernel width of 5.4, having LAI, NDVI, thermal and red bands as the selected set of inputs, can be used to spatially estimate chlorophyll concentration with a root-mean-squared-error of 5.31 μg cm-2, efficiency of 0.76, and 9 relevance vectors.

  20. Classifying Multiple Stages of Mountain Pine Beetle Disturbance Using Multispectral Aerial Imagery in North-Central Colorado

    NASA Astrophysics Data System (ADS)

    Meddens, A. J.; Hicke, J. A.; Vierling, L. A.

    2010-12-01

    Insect outbreaks are major forest disturbances, killing trees across millions of ha in the United States. These dead trees affect the condition of the ecosystems, leading to alterations of forest functioning and fuel arrangement, among other impacts. In this study, we evaluated methods for classifying 30-cm multispectral imagery including insect-caused tree mortality (both red and gray attack) classes and non-forest classes. We acquired 4-band imagery in lodgepole pine stands of central Colorado that were recently attacked by mountain pine beetle. The 30-cm resolution image facilitated delineation of field-observed trees, which were used for image classification. We employed the maximum likelihood classifier with the Normalized Difference Vegetation Index (NDVI), the Red-Green Index (RGI), and Green band (GREEN). Our initial classification used original spatial resolution imagery to identify green trees, red-attack, gray-attack, herbaceous, bare soil, and shadow classes. Although classification accuracies were good (overall accuracy of 85.95%, kappa = 0.826), we noted confusion between sunlit crowns of live (green) trees and herbaceous classes at this very fine spatial resolution, and confusion between sunlit crowns of gray- and red-attack trees and bare soil, and thus explored additional methods to reduce omission and commission errors. Classification confusion was overcome by aggregating the 30-cm multispectral imagery into a 2.4-m resolution image (matching very high resolution satellite imagery). Pixels in the 2.4-m resolution image included more shadow in the forested regions than the 30-cm resolution, thereby reducing forest canopy reflectance and improving the separability between the forest and non-forest classes that had caused previous errors. We conclude that operational mapping of insect-caused tree mortality with multispectral imagery has great potential for forest disturbance mapping, and that imagery with a spatial resolution about the crown width of

  1. Parameter-Based Performance Analysis of Object-Based Image Analysis Using Aerial and Quikbird-2 Images

    NASA Astrophysics Data System (ADS)

    Kavzoglu, T.; Yildiz, M.

    2014-09-01

    Opening new possibilities for research, very high resolution (VHR) imagery acquired by recent commercial satellites and aerial systems requires advanced approaches and techniques that can handle large volume of data with high local variance. Delineation of land use/cover information from VHR images is a hot research topic in remote sensing. In recent years, object-based image analysis (OBIA) has become a popular solution for image analysis tasks as it considers shape, texture and content information associated with the image objects. The most important stage of OBIA is the image segmentation process applied prior to classification. Determination of optimal segmentation parameters is of crucial importance for the performance of the selected classifier. In this study, effectiveness and applicability of the segmentation method in relation to its parameters was analysed using two VHR images, an aerial photo and a Quickbird-2 image. Multi-resolution segmentation technique was employed with its optimal parameters of scale, shape and compactness that were defined after an extensive trail process on the data sets. Nearest neighbour classifier was applied on the segmented images, and then the accuracy assessment was applied. Results show that segmentation parameters have a direct effect on the classification accuracy, and low values of scale-shape combinations produce the highest classification accuracies. Also, compactness parameter was found to be having minimal effect on the construction of image objects, hence it can be set to a constant value in image classification.

  2. Low-cost Tools for Aerial Video Geolocation and Air Traffic Analysis for Delay Reduction Using Google Earth

    NASA Astrophysics Data System (ADS)

    Zetterlind, V.; Pledgie, S.

    2009-12-01

    Low-cost, low-latency, robust geolocation and display of aerial video is a common need for a wide range of earth observing as well as emergency response and security applications. While hardware costs for aerial video collection systems, GPS, and inertial sensors have been decreasing, software costs for geolocation algorithms and reference imagery/DTED remain expensive and highly proprietary. As part of a Federal Small Business Innovative Research project, MosaicATM and EarthNC, Inc have developed a simple geolocation system based on the Google Earth API and Google's 'built-in' DTED and reference imagery libraries. This system geolocates aerial video based on platform and camera position, attitude, and field-of-view metadata using geometric photogrammetric principles of ray-intersection with DTED. Geolocated video can be directly rectified and viewed in the Google Earth API during processing. Work is underway to extend our geolocation code to NASA World Wind for additional flexibility and a fully open-source platform. In addition to our airborne remote sensing work, MosaicATM has developed the Surface Operations Data Analysis and Adaptation (SODAA) tool, funded by NASA Ames, which supports analysis of airport surface operations to optimize aircraft movements and reduce fuel burn and delays. As part of SODAA, MosaicATM and EarthNC, Inc have developed powerful tools to display national airspace data and time-animated 3D flight tracks in Google Earth for 4D analysis. The SODAA tool can convert raw format flight track data, FAA National Flight Data (NFD), and FAA 'Adaptation' airport surface data to a spatial database representation and then to Google Earth KML. The SODAA client provides users with a simple graphical interface through which to generate queries with a wide range of predefined and custom filters, plot results, and export for playback in Google Earth in conjunction with NFD and Adaptation overlays.

  3. Object-based spatiotemporal analysis of vine canopy vigor using an inexpensive unmanned aerial vehicle remote sensing system

    NASA Astrophysics Data System (ADS)

    Mathews, Adam J.

    2014-01-01

    Remotely sensed imagery provides a rapid assessment of spatial variability in grapevine canopy vigor that correlates with crop performance. Unmanned aerial vehicles (UAVs) provide a low-cost image acquisition platform with high spatial and temporal resolutions. Using a UAV and digital cameras, aerial images of a Texas vineyard were captured at postflowering, veraison, and harvest. Imagery was processed to generate orthophotos in units of reflectance, which were then segmented to extract per-vine estimates of canopy area (planimetric extent) and normalized difference vegetation index (NDVI)-based canopy density. Derived canopy area and density values were compared to the harvest variables of number of clusters, cluster size, and yield to explore correlations. Planimetrically derived canopy area yielded significant, positive relationships, whereas NDVI-based canopy density exhibited no significant relationships due to sensor-related radiometric inaccuracy. A vine performance index was calculated to map spatial variation in canopy vigor for the entire growing season. Future management zones were delineated using spatial grouping analysis.

  4. Environmental Remote Sensing Analysis Using Open Source Virtual Earths and Public Domain Imagery

    NASA Astrophysics Data System (ADS)

    Pilant, A. N.; Worthy, L. D.

    2008-12-01

    Human activities increasingly impact natural environments. Globally, many ecosystems are stressed to unhealthy limits, leading to loss of valuable ecosystem services- economic, ecologic and intrinsic. Virtual earths (virtual globes) (e.g., NASA World Wind, ossimPlanet, ArcGIS Explorer, Google Earth, Microsoft Virtual Earth) are geospatial data integration tools that can aid our efforts to understand and protect the environment. Virtual earths provide unprecedented desktop views of our planet, not only to professional scientists, but also to citizen scientists, students, environmental stewards, decision makers, urban developers and planners. Anyone with a broadband internet connection can explore the planet virtually, due in large part to freely available open source software and public domain imagery. This has at least two important potential benefits. One, individuals can study the planet from the visually intuitive perspective of the synoptic aerial view, promoting environmental awareness and stewardship. Two, it opens up the possibility of harnessing the in situ knowledge and observations of citizen scientists familiar with landscape conditions in their locales. Could this collective knowledge be harnessed (crowd sourcing) to validate and quality assure land cover and other maps? In this presentation we present examples using public domain imagery and two open source virtual earths to highlight some of the functionalities currently available. OssimPlanet is used to view aerial data from the USDA Geospatial Data Gateway. NASA World Wind is used to extract georeferenced high resolution USGS urban area orthoimagery. ArcGIS Explorer is used to demonstrate an example of image analysis using web processing services. The research presented here was conducted under the Environmental Feature Finder project of the Environmental Protection Agency's Advanced Monitoring Initiative. Although this work was reviewed by EPA and approved for publication, it may not necessarily

  5. Analysis of optical imagery for Seyfert's Sextet and VV 172

    NASA Technical Reports Server (NTRS)

    Sulentic, J. W.; Lorre, J. J.

    1983-01-01

    Seyfert's Sextet and VV 172, 5-m photographs have been subjected to image processing to yield field-galaxy density analysis, redshift-scaled imagery, interaction morphology display and enhancement, color difference imagery,modeling of the VV 172 halo, and image texture analysis of the spiral galaxy components of Seyfert's Sextet. An effort is made to evaluate the evidence for physical association of the discordant redshift components of these groups. An especially noteworthy characteristic of the groups is their extended luminous halos. The halo of VV 172 cannot be explained by the overlapping envelopes of galaxies with normal luminosity profiles, and the high redshift spiral galaxy in the Sextet is found to have an asymmetric internal structure and associated filament which suggest gravitational perturbation by the other members of the group.

  6. Radiometric and Geometric Accuracy Analysis of Rasat Pan Imagery

    NASA Astrophysics Data System (ADS)

    Kocaman, S.; Yalcin, I.; Guler, M.

    2016-06-01

    RASAT is the second Turkish Earth Observation satellite which was launched in 2011. It operates with pushbroom principle and acquires panchromatic and MS images with 7.5 m and 15 m resolutions, respectively. The swath width of the sensor is 30 km. The main aim of this study is to analyse the radiometric and geometric quality of RASAT images. A systematic validation approach for the RASAT imagery and its products is being applied. RASAT image pair acquired over Kesan city in Edirne province of Turkey are used for the investigations. The raw RASAT data (L0) are processed by Turkish Space Agency (TUBITAK-UZAY) to produce higher level image products. The image products include radiometrically processed (L1), georeferenced (L2) and orthorectified (L3) data, as well as pansharpened images. The image quality assessments include visual inspections, noise, MTF and histogram analyses. The geometric accuracy assessment results are only preliminary and the assessment is performed using the raw images. The geometric accuracy potential is investigated using 3D ground control points extracted from road intersections, which were measured manually in stereo from aerial images with 20 cm resolution and accuracy. The initial results of the study, which were performed using one RASAT panchromatic image pair, are presented in this paper.

  7. The Pacific Northwest story. [imagery analysis facilities

    NASA Technical Reports Server (NTRS)

    Johnson, K. A.; Schrumpf, B. J.; Krebs, L.

    1981-01-01

    The establishment of image analysis facilities for the operational utilization of LANDSAT data in Idaho, Oregon, and Washington is discussed. The hardware and software resources are described for each facility along with the range of services.

  8. Waste site characterization through digital analysis of historical aerial photographs at Los Alamos National Laboratory and Eglin Air Force Base

    SciTech Connect

    Van Eeckhout, E.; Pope, P.; Wells, B.; Rofer, C.; Martin, B.

    1995-05-01

    Historical aerial photographs are used to provide a physical history and preliminary mapping information for characterizing hazardous waste sites at Los Alamos National Laboratory and Eglin Air Force Base. The examples cited show how imagery was used to accurately locate and identify previous activities at a site, monitor changes that occurred over time, and document the observable of such activities today. The methodology demonstrates how historical imagery (along with any other pertinent data) can be used in the characterization of past environmental damage.

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

    SciTech Connect

    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. Several 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.

  10. Preliminary analysis of aerial hyperspectral data on shallow lacustrine waters

    NASA Astrophysics Data System (ADS)

    Bianchi, Remo; Castagnoli, A.; Cavalli, Rosa M.; Marino, Carlo M.; Pignatti, Stefano; Zilioli, Eugenio

    1995-11-01

    The availability of MIVIS hyperspectral data, deriving from an aerial survey recently performed over a test-site in Lake Garda, Italy, gave the possibility of a preliminary new insight in the field of specific applications of remote sensing to shallow water analysis. The spectroradiometers in the visible and in the thermal infrared were explored in particular, accessing to helpful information for the detection of bio-physical indicators of water quality, either related to the surface/sub-surface of waters or to the bottom of the lake, since the study area presents very shallow waters, never exceeding a 6-meter depth in any case. Primary interest was the detection of man-induced activities along the margins, like sewage effect and sedimentary structure in the bottom or algal bloom. Secondly, a correlation between absorbivity coefficients in the visible bands and bathimetric contour lines in the proximity of the marginal zone of the lake was accomplished, by means of two indicative spectroradiometric transects.

  11. Semi-Automated Approach for Mapping Urban Trees from Integrated Aerial LiDAR Point Cloud and Digital Imagery Datasets

    NASA Astrophysics Data System (ADS)

    Dogon-Yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

    2016-09-01

    Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.

  12. Integration of radar and Landsat imagery for structural analysis

    SciTech Connect

    Dodge, R.L.

    1986-05-01

    Radar imagery contains information on texture, structural orientation, and topography that augments data interpretable from Landsat Multispectral Scanner and Thematic Mapper data. Integrating data available from these two remote-sensing systems results in a more complete interpretation of surface features related to subsurface structures. Examples of improved interpretation emphasize the importance of radar's variable illumination azimuth for recognizing structural trends in addition to those seen on Landsat data. Also, textural detail and increased resolution from radar imagery improve the interpretability of fracture patterns and fracture density, and high resolution and variable illumination angle enhance topographic detail and recognition of structurally controlled topography. Tonal variations in the visible-near infrared, seen on Landsat data, can be related to fracture density, structurally controlled soil moisture conditions, and structurally controlled topography. Integrating the surface expression of structural features on the two types of data results in better maps of the surface expression of subsurface structures. Examples presented illustrate applications of such integrated analysis. Data from Landsat and radar sensors can be integrated visually, during the interpretation process, or digitally. Both approaches have advantages; visual integration is more practical for regional analysis, and digital integration can be applied in high-graded areas.

  13. Hierarchical target model analysis of tactical thermal imagery

    NASA Astrophysics Data System (ADS)

    Lee, Harry C.; Olson, Teresa L. P.; Sefcik, Jason A.

    2002-07-01

    Hierarchical Target Model Analysis (HTMA) is an automatic pattern matching process for categorizing tactical targets. Stored target model information is re-projected into the image space using the sensor camera model state vector. The analysis is carried out in image gradient angle space for greater flexibility and reduced processing. Re-sampling the gradient angle space allows the classification process to work at a wider variety of target ranges. The target model database is built from an assortment of both target operating and background environmental conditions. Incremental classification is possible by applying the matching strategy at increasing target resolution levels that are either self or range closure induced. The first application of this process has been on thermal imagery. It can easily be extended to other image domains.

  14. Supervised nonparametric sparse discriminant analysis for hyperspectral imagery classification

    NASA Astrophysics Data System (ADS)

    Wu, Longfei; Sun, Hao; Ji, Kefeng

    2016-03-01

    Owing to the high spectral sampling, the spectral information in hyperspectral imagery (HSI) is often highly correlated and contains redundancy. Motivated by the recent success of sparsity preserving based dimensionality reduction (DR) techniques in both computer vision and remote sensing image analysis community, a novel supervised nonparametric sparse discriminant analysis (NSDA) algorithm is presented for HSI classification. The objective function of NSDA aims at preserving the within-class sparse reconstructive relationship for within-class compactness characterization and maximizing the nonparametric between-class scatter simultaneously to enhance discriminative ability of the features in the projected space. Essentially, it seeks for the optimal projection matrix to identify the underlying discriminative manifold structure of a multiclass dataset. Experimental results on one visualization dataset and three recorded HSI dataset demonstrate NSDA outperforms several state-of-the-art feature extraction methods for HSI classification.

  15. 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.

  16. A new technique for the detection of large scale landslides in glacio-lacustrine deposits using image correlation based upon aerial imagery: A case study from the French Alps

    NASA Astrophysics Data System (ADS)

    Fernandez, Paz; Whitworth, Malcolm

    2016-10-01

    Landslide monitoring has benefited from recent advances in the use of image correlation of high resolution optical imagery. However, this approach has typically involved satellite imagery that may not be available for all landslides depending on their time of movement and location. This study has investigated the application of image correlation techniques applied to a sequence of aerial imagery to an active landslide in the French Alps. We apply an indirect landslide monitoring technique (COSI-Corr) based upon the cross-correlation between aerial photographs, to obtain horizontal displacement rates. Results for the 2001-2003 time interval are presented, providing a spatial model of landslide activity and motion across the landslide, which is consistent with previous studies. The study has identified areas of new landslide activity in addition to known areas and through image decorrelation has identified and mapped two new lateral landslides within the main landslide complex. This new approach for landslide monitoring is likely to be of wide applicability to other areas characterised by complex ground displacements.

  17. Risk and safety analysis for Florida commercial aerial application operations

    NASA Astrophysics Data System (ADS)

    Robbins, John Michael

    The purpose of this study was to determine self-reported perceptions in the areas of agroterrorism, bioterrorism, chemical exposure and Federal Aviation Administration (FAA) oversight. The aerial application industry has been in existence since the 1920's with a gamut of issues ranging from pesticide drift to counterterrorism. The attacks of September 11th, 2001, caused a paradigm shift in the way the United States views security and, more importantly, the prevention of malicious activity. Through the proper implementation and dissemination of educational materials dealing with industry specific concerns, it is imperative that everyone has the proper level of resources and training to effectively manage terrorist threats. This research study was designed to interpret how aerial applicators view these topics of concern and how they perceive the current threat level of terrorism in the industry. Research results were consistent, indicating that a high number of aerial applicators in the state of Florida are concerned with these topics. As a result, modifications need to be made with respect to certain variables. The aerial application industry works day in and day out to provide a professional service that helps maintain the integrity of the food and commodities that we need to survive. They are a small percentage of the aviation community that we all owe a great deal for the vital and necessary services they provide.

  18. Spatial statistical analysis of tree deaths using airborne digital imagery

    NASA Astrophysics Data System (ADS)

    Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael

    2013-04-01

    High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).

  19. Design, fabrication & performance analysis of an unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Khan, M. I.; Salam, M. A.; Afsar, M. R.; Huda, M. N.; Mahmud, T.

    2016-07-01

    An Unmanned Aerial Vehicle was designed, analyzed and fabricated to meet design requirements and perform the entire mission for an international aircraft design competition. The goal was to have a balanced design possessing, good demonstrated flight handling qualities, practical and affordable manufacturing requirements while providing a high vehicle performance. The UAV had to complete total three missions named ferry flight (1st mission), maximum load mission (2nd mission) and emergency medical mission (3rd mission). The requirement of ferry flight mission was to fly as many as laps as possible within 4 minutes. The maximum load mission consists of flying 3 laps while carrying two wooden blocks which simulate cargo. The requirement of emergency medical mission was complete 3 laps as soon as possible while carrying two attendances and two patients. A careful analysis revealed lowest rated aircraft cost (RAC) as the primary design objective. So, the challenge was to build an aircraft with minimum RAC that can fly fast, fly with maximum payload, and fly fast with all the possible configurations. The aircraft design was reached by first generating numerous design concepts capable of completing the mission requirements. In conceptual design phase, Figure of Merit (FOM) analysis was carried out to select initial aircraft configuration, propulsion, empennage and landing gear. After completion of the conceptual design, preliminary design was carried out. The preliminary design iterations had a low wing loading, high lift coefficient, and a high thrust to weight ratio. To make the aircraft capable of Rough Field Taxi; springs were added in the landing gears for absorbing shock. An airfoil shaped fuselage was designed to allowed sufficient space for payload and generate less drag to make the aircraft fly fast. The final design was a high wing monoplane with conventional tail, single tractor propulsion system and a tail dragger landing gear. Payload was stored in

  20. Aberration measurement based on principal component analysis of aerial images of optimized marks

    NASA Astrophysics Data System (ADS)

    Yan, Guanyong; Wang, Xiangzhao; Li, Sikun; Yang, Jishuo; Xu, Dongbo

    2014-10-01

    We propose an aberration measurement technique based on principal component analysis of aerial images of optimized marks (AMAI-OM). Zernike aberrations are retrieved using a linear relationship between the aerial image and Zernike coefficients. The linear relationship is composed of the principal components (PCs) and regression matrix. A centering process is introduced to compensate position offsets of the measured aerial image. A new test mark is designed in order to improve the centering accuracy and theoretical accuracy of aberration measurement together. The new test marks are composed of three spaces with different widths, and their parameters are optimized by using an accuracy evaluation function. The offsets of the measured aerial image are compensated in the centering process and the adjusted PC coefficients are obtained. Then the Zernike coefficients are calculated according to these PC coefficients using a least square method. The simulations using the lithography simulators PROLITH and Dr.LiTHO validate the accuracy of our method. Compared with the previous aberration measurement technique based on principal component analysis of aerial image (AMAI-PCA), the measurement accuracy of Zernike aberrations under the real measurement condition of the aerial image is improved by about 50%.

  1. Wavelet-based multifractal analysis of laser biopsy imagery

    NASA Astrophysics Data System (ADS)

    Jagtap, Jaidip; Ghosh, Sayantan; Panigrahi, Prasanta K.; Pradhan, Asima

    2012-03-01

    In this work, we report a wavelet based multi-fractal study of images of dysplastic and neoplastic HE- stained human cervical tissues captured in the transmission mode when illuminated by a laser light (He-Ne 632.8nm laser). It is well known that the morphological changes occurring during the progression of diseases like cancer manifest in their optical properties which can be probed for differentiating the various stages of cancer. Here, we use the multi-resolution properties of the wavelet transform to analyze the optical changes. For this, we have used a novel laser imagery technique which provides us with a composite image of the absorption by the different cellular organelles. As the disease progresses, due to the growth of new cells, the ratio of the organelle to cellular volume changes manifesting in the laser imagery of such tissues. In order to develop a metric that can quantify the changes in such systems, we make use of the wavelet-based fluctuation analysis. The changing self- similarity during disease progression can be well characterized by the Hurst exponent and the scaling exponent. Due to the use of the Daubechies' family of wavelet kernels, we can extract polynomial trends of different orders, which help us characterize the underlying processes effectively. In this study, we observe that the Hurst exponent decreases as the cancer progresses. This measure could be relatively used to differentiate between different stages of cancer which could lead to the development of a novel non-invasive method for cancer detection and characterization.

  2. Comparison of analysis techniques for aerial image metrology on advanced photomask

    NASA Astrophysics Data System (ADS)

    Hwang, Seolchong; Woo, Sungha; Jang, Heeyeon; Lee, Youngmo; Kim, Sangpyo; Yang, Hyunjo; Schulz, Kristian; Garetto, Anthony

    2016-05-01

    The standard method for defect disposition and verification of repair success in the mask shop is through the utilization of the aerial imaging platform, AIMSTM. The CD (Critical Dimension) deviation of the defective or repaired region as well as the pattern shift can be calculated by comparing the measured aerial images of this region to that of a reference. Through this analysis it can be determined if the defect or repaired region will be printed on the wafer under the illumination conditions of the scanner. The analysis of the measured aerial images from the AIMSTM are commonly performed manually using the analysis software available on the system or with the help of an analysis software called RV (Repair Verification). Because the process is manual, it is not standardized and is subject to operator variations. This method of manual aerial image analysis is time consuming, dependent on the skill level of the operator and significantly contributes to the overall mask manufacturing process flow. AutoAnalysis (AA), the first application available for the FAVOR® platform, provides fully automated analysis of AIMSTM aerial images [1] and runs in parallel to the measurement of the aerial images. In this paper, we investigate the initial AutoAnalysis performance compared to the conventional method using RV and its application to a production environment. The evaluation is based on the defect CD of three pattern types: contact holes, dense line and spaces and peripheral structure. The defect analysis results for different patterns and illumination conditions will be correlated and challenges in transitioning to the new approach will be discussed.

  3. Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review.

    PubMed

    Hamedi, Mahyar; Salleh, Sh-Hussain; Noor, Alias Mohd

    2016-06-01

    Recent research has reached a consensus on the feasibility of motor imagery brain-computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most MI-BCI systems rely on temporal, spectral, and spatial features of single channels to distinguish different MI patterns. However, no successful communication has been established for a completely locked-in subject. To provide more useful and informative features, it has been recommended to take into account the relationships among electroencephalographic (EEG) sensor/source signals in the form of brain connectivity as an efficient tool of neuroscience. In this review, we briefly report the challenges and limitations of conventional MI-BCIs. Brain connectivity analysis, particularly functional and effective, has been described as one of the most promising approaches for improving MI-BCI performance. An extensive literature on EEG-based MI brain connectivity analysis of healthy subjects is reviewed. We subsequently discuss the brain connectomes during left and right hand, feet, and tongue MI movements. Moreover, key components involved in brain connectivity analysis that considerably affect the results are explained. Finally, possible technical shortcomings that may have influenced the results in previous research are addressed and suggestions are provided.

  4. Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review.

    PubMed

    Hamedi, Mahyar; Salleh, Sh-Hussain; Noor, Alias Mohd

    2016-06-01

    Recent research has reached a consensus on the feasibility of motor imagery brain-computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most MI-BCI systems rely on temporal, spectral, and spatial features of single channels to distinguish different MI patterns. However, no successful communication has been established for a completely locked-in subject. To provide more useful and informative features, it has been recommended to take into account the relationships among electroencephalographic (EEG) sensor/source signals in the form of brain connectivity as an efficient tool of neuroscience. In this review, we briefly report the challenges and limitations of conventional MI-BCIs. Brain connectivity analysis, particularly functional and effective, has been described as one of the most promising approaches for improving MI-BCI performance. An extensive literature on EEG-based MI brain connectivity analysis of healthy subjects is reviewed. We subsequently discuss the brain connectomes during left and right hand, feet, and tongue MI movements. Moreover, key components involved in brain connectivity analysis that considerably affect the results are explained. Finally, possible technical shortcomings that may have influenced the results in previous research are addressed and suggestions are provided. PMID:27137671

  5. Near infrared-red models for the remote estimation of chlorophyll- a concentration in optically complex turbid productive waters: From in situ measurements to aerial imagery

    NASA Astrophysics Data System (ADS)

    Gurlin, Daniela

    Today the water quality of many inland and coastal waters is compromised by cultural eutrophication in consequence of increased human agricultural and industrial activities and remote sensing is widely applied to monitor the trophic state of these waters. This study explores near infrared-red models for the remote estimation of chlorophyll-a concentration in turbid productive waters and compares several near infrared-red models developed within the last 35 years. Three of these near infrared-red models were calibrated for a dataset with chlorophyll-a concentrations from 2.3 to 81.2 mg m -3 and validated for independent and statistically significantly different datasets with chlorophyll-a concentrations from 4.0 to 95.5 mg m-3 and 4.0 to 24.2 mg m-3 for the spectral bands of the MEdium Resolution Imaging Spectrometer (MERIS) and Moderate-resolution Imaging Spectroradiometer (MODIS). The developed MERIS two-band algorithm estimated chlorophyll-a concentrations from 4.0 to 24.2 mg m-3, which are typical for many inland and coastal waters, very accurately with a mean absolute error 1.2 mg m-3. These results indicate a high potential of the simple MERIS two-band algorithm for the reliable estimation of chlorophyll-a concentration without any reduction in accuracy compared to more complex algorithms, even though more research seems required to analyze the sensitivity of this algorithm to differences in the chlorophyll-a specific absorption coefficient of phytoplankton. Three near infrared-red models were calibrated and validated for a smaller dataset of atmospherically corrected multi-temporal aerial imagery collected by the hyperspectral airborne imaging spectrometer for applications (AisaEAGLE). The developed algorithms successfully captured the spatial and temporal variability of the chlorophyll-a concentrations and estimated chlorophyll- a concentrations from 2.3 to 81.2 mg m-3 with mean absolute errors from 4.4 mg m-3 for the AISA two band algorithm to 5.2 mg m-3

  6. An Information-Processing Analysis of a Piagetian Imagery Task.

    ERIC Educational Resources Information Center

    Dean, Anne L.; Harvey, Wade O.

    1979-01-01

    Children at three age levels (4-6, 7-9, and 10-14 years) performed a reaction-time version of Piaget and Inhelder's rotating squares imagery task and a pivot and shape conservation recognition task. (JMB)

  7. Target detection in FLIR imagery using independent component analysis

    NASA Astrophysics Data System (ADS)

    Sadeque, A. Z.; Alam, M. S.

    2006-05-01

    In this paper, we propose a target detection algorithm in FLIR imagery using independent component analysis (ICA). Here FLIR images of some real targets with practical background regions are used for training. Dimension of the training regions is chosen depending on the size of the target. After performing ICA transformation on these training images, we obtain a ICA matrix, where each row gives the transformed version of the previous matrix, and a weight matrix. Using these matrices, a transformed matrix of the input image can be found with enhanced features. Then cosine of the angle between the training and test vectors is employed as the parameter for detecting the unknown target. A test region is selected from the first frame of FLIR image, which is of the same size as the training region. This region is transformed following the proposed algorithm and then the cosine value is measured between this transformed vector and the corresponding vector of the transformed training matrix. Next the test region is shifted by one pixel and the same transformation and measurement are done. Thus the whole input frame is scanned and we get a matrix for cosine values. Finally a target is detected in a region of the input frame where it gives the highest cosine value. A detailed computer simulation program is developed for the proposed algorithm and a satisfactory performance is observed when tested with real FLIR images.

  8. 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

  9. 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

  10. Mission control of multiple unmanned aerial vehicles: a workload analysis.

    PubMed

    Dixon, Stephen R; Wickens, Christopher D; Chang, Dervon

    2005-01-01

    With unmanned aerial vehicles (UAVs), 36 licensed pilots flew both single-UAV and dual-UAV simulated military missions. Pilots were required to navigate each UAV through a series of mission legs in one of the following three conditions: a baseline condition, an auditory autoalert condition, and an autopilot condition. Pilots were responsible for (a) mission completion, (b) target search, and (c) systems monitoring. Results revealed that both the autoalert and the autopilot automation improved overall performance by reducing task interference and alleviating workload. The autoalert system benefited performance both in the automated task and mission completion task, whereas the autopilot system benefited performance in the automated task, the mission completion task, and the target search task. Practical implications for the study include the suggestion that reliable automation can help alleviate task interference and reduce workload, thereby allowing pilots to better handle concurrent tasks during single- and multiple-UAV flight control.

  11. Characterising Upland Swamps Using Object-Based Classification Methods and Hyper-Spatial Resolution Imagery Derived from AN Unmanned Aerial Vehicle

    NASA Astrophysics Data System (ADS)

    Lechner, A. M.; Fletcher, A.; Johansen, K.; Erskine, P.

    2012-07-01

    Subsidence, resulting from underground coal mining can alter the structure of overlying rock formations changing hydrological conditions and potentially effecting ecological communities found on the surface. Of particular concern are impacts to endangered and/or protected swamp communities and swamp species sensitive to changes in hydrologic conditions. This paper describes a monitoring approach that uses UAVs with modified digital cameras and object-based image analysis methods to characterise swamp landcover on the Newnes plateau in the Blue Mountains near Sydney, Australia. The characterisation of swamp spatial distribution is key to identifying long term changes in swamp condition. In this paper we describe i) the characteristics of the UAV and the sensor, ii) the pre-processing of the remote sensing data with sub-decimeter pixel size to derive visible and near infrared multispectral imagery and a digital surface model (DSM), and iii) the application of object-based image analysis in eCognition using the multi-spectral data and DSM to map swamp extent. Finally, we conclude with a discussion of the potential application of remote sensing data derived from UAVs to conduct environmental monitoring.

  12. Preliminary analysis of the potential of LANDSAT imagery to study desertification. [Xique-Xique, Brazil

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Lombardo, M. A.; Decarvalho, V. C.

    1980-01-01

    The use of LANDSAT imagery to define and delimit areas under process of desertification was investigated. Imagery for two different years (1973 and 1978) and two different seasons (dry and rainy seasons in 1976), were used to identify terrain morphology and vegetation cover. The analysis of LANDSAT interpretation, combined with geological and soil information obtained from published literature, allowed the identification of eleven ecological units which were classified corresponding to the degree of the Xique Xique region of Rio Sao Francisco.

  13. Meltwater Origin of the 2005 Mount Steller Landslide Confirmed by Analysis of Global Fiducials Program Imagery

    NASA Astrophysics Data System (ADS)

    Molnia, B. F.; Angeli, K.

    2012-12-01

    Alaska's Mt. Steller, a 3,236 m Chugach Mountains peak, is one of the target areas of the Bering Glacier Global Fiducials Program (GFP) site. On September 14, 2005, a large mass of rock, glacier ice, and snow, with a volume of ~50 million cubic meters, fell from just below Mt. Steller's south-facing summit and landed on the surface of a tributary to Bering Glacier, nearly 2,500 m below. The slide, which extended ~8 km down-glacier, was actually an ice-rock avalanche. The impact generated a seismic signal recorded with a magnitude of up to 5.2. Oblique aerial photography of the mountain, the head scarp, and the slide mass was collected for the U.S. Geological Survey's Alaska Volcano Observatory (AVO) on September 15, 2005. The photography delineated the morphology of the failed south-facing slope of the mountain and showed details of the sheared, near-summit hanging glacier and snow mass. Based on the photography, the AVO calculated the slide volume and length. Several weeks later, the AVO provided the first author with digital copies of the September 15 photography. These images were enhanced and examined in order to determine properties of the slide and to evaluate if the cause of the event could be determined. A number of features observed led to the conclusion that meltwater was probably responsible for destabilizing the glacier ice-bedrock contact and triggering the landslide. Specifically, a 10-15 m diameter englacial stream channel was seen in the truncated glacier ice that comprised the east wall of the landslide scarp and a water-polished channel opening was noted on the west wall scarp. Additionally, several depressions were noted that might have temporarily stored water. To confirm these observations, new cloud-free GFP imagery was obtained on October 24 and 28, 2005. Analysis of both sets of imagery documented that: (1) more than a month after the event, meltwater was exiting the east wall scarp channel and flowing down the face of the mountain; (2) the

  14. 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.

  15. Land cover/use mapping using multi-band imageries captured by Cropcam Unmanned Aerial Vehicle Autopilot (UAV) over Penang Island, Malaysia

    NASA Astrophysics Data System (ADS)

    Fuyi, Tan; Boon Chun, Beh; Mat Jafri, Mohd Zubir; Hwee San, Lim; Abdullah, Khiruddin; Mohammad Tahrin, Norhaslinda

    2012-11-01

    The problem of difficulty in obtaining cloud-free scene at the Equatorial region from satellite platforms can be overcome by using airborne imagery. Airborne digital imagery has proved to be an effective tool for land cover studies. Airborne digital camera imageries were selected in this present study because of the airborne digital image provides higher spatial resolution data for mapping a small study area. The main objective of this study is to classify the RGB bands imageries taken from a low-altitude Cropcam UAV for land cover/use mapping over USM campus, penang Island, Malaysia. A conventional digital camera was used to capture images from an elevation of 320 meter on board on an UAV autopilot. This technique was cheaper and economical compared with other airborne studies. The artificial neural network (NN) and maximum likelihood classifier (MLC) were used to classify the digital imageries captured by using Cropcam UAV over USM campus, Penang Islands, Malaysia. The supervised classifier was chosen based on the highest overall accuracy (<80%) and Kappa statistic (<0.8). The classified land cover map was geometrically corrected to provide a geocoded map. The results produced by this study indicated that land cover features could be clearly identified and classified into a land cover map. This study indicates the use of a conventional digital camera as a sensor on board on an UAV autopilot can provide useful information for planning and development of a small area of coverage.

  16. High-resolution Brillouin analysis in a carbon-fiber-composite unmanned aerial vehicle model wing

    NASA Astrophysics Data System (ADS)

    Stern, Yonatan; London, Yosef; Preter, Eyal; Antman, Yair; Shlomi, Orel; Silbiger, Maayan; Adler, Gadi; Zadok, Avi

    2016-05-01

    Standard optical fibers are successfully embedded within a model wing of an unmanned aerial vehicle, constructed of carbon fiber and epoxy, during its production. Time-gated Brillouin optical correlation domain analysis along the embedded optical fibers is performed with a spatial resolution of 4 cm. Tests were carried out using a portable measurement setup prototype. The results represent an important step towards applications of high-resolution Brillouin analysis outside the research laboratory.

  17. Structural lineament and pattern analysis of Missouri, using LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Martin, J. A.; Kisvarsanyi, G. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. Major linear, circular, and arcuate traces were observed on LANDSAT imagery of Missouri. Lineaments plotted within the state boundaries range from 20 to nearly 500 km in length. Several extend into adjoining states. Lineaments plots indicate a distinct pattern and in general reflect structural features of the Precambrian basement of the platform. Coincidence of lineaments traced from the imagery and known structural features in Missouri is high, thus supporting a causative relation between them. The lineament pattern apparently reveals a fundamental style of the deformation of the intracontinental craton. Dozens of heretofore unknown linear features related to epirogenic movements and deformation of this segment of the continental crust were delineated. Lineaments and mineralization are interrelated in a geometrically classifiable pattern.

  18. Phytochemical Analysis and Antioxidant Activity of Salvia chloroleuca Aerial Extracts

    PubMed Central

    Salimikia, Iraj; Reza Monsef-Esfahani, Hamid; Gohari, Ahmad Reza; Salek, Mehrnoosh

    2016-01-01

    Background Salvia, known as Maryam Goli in the Persian language, is an important genus that includes approximately 900 species in the Lamiaceae family. There are 58 Salvia species growing naturally in Iran, including Salvia chloroleuca Rech. f. and Allen., which grows wild in the northeastern and central parts of the country. Objectives This study was designed to determine the chemical composition, in vitro antioxidant activity, and total phenol content of various extracts of S. chloroleuca. Materials and Methods Dried aerial parts of the plant were crushed, then sequentially extracted with n-hexane, ethyl acetate, and methanol. The fractions of S. chloroleuca were subjected to silica gel column chromatography and Sephedex LH-20. The antioxidant activities of these extracts were measured by ferric reducing antioxidant power (FRAP), and the total phenolic contents of the extracts were evaluated using Folin-Ciocalteu reagent. Results The separation and purification processes were carried out using different chromatographic methods. Structural elucidation was on the basis 1H-NMR and 13C-NMR spectral data, in comparison with that reported in the literature. The isolated compounds were salvigenin (1), luteolin (2), cirsiliol (3), β-sitosterol (4), and daucosterol (5). Ethyl acetate extract displayed the highest level of total antioxidants and total polyphenols compared to the other analyzed extracts (n-hexane and methanol). In the FRAP assay, ethyl acetate extract had the highest (230.4±10.5) FRAP value, followed by methanol (211.4 ± 8.3) and n-hexane (143.4 ± 12.04). Total phenol contents were calculated to be 13.8 ± 0.3, 58.25 ± 0.05, and 43.48 ± 0.38 mg of gallic acid/100 g in the n-hexane, ethyl acetate, and methanol extracts, respectively. Conclusions The above-mentioned compounds were isolated for the first time from S. chloroleuca. The antioxidant activity of this plant could be in part related to isolated flavonoids and sterols. The results of this study

  19. Uncorrelated multiway discriminant analysis for motor imagery EEG classification.

    PubMed

    Liu, Ye; Zhao, Qibin; Zhang, Liqing

    2015-06-01

    Motor imagery-based brain-computer interfaces (BCIs) training has been proved to be an effective communication system between human brain and external devices. A practical problem in BCI-based systems is how to correctly and efficiently identify and extract subject-specific features from the blurred scalp electroencephalography (EEG) and translate those features into device commands in order to control external devices. In real BCI-based applications, we usually define frequency bands and channels configuration that related to brain activities beforehand. However, a steady configuration usually loses effects due to individual variability among different subjects in practical applications. In this study, a robust tensor-based method is proposed for a multiway discriminative subspace extraction from tensor-represented EEG data, which performs well in motor imagery EEG classification without the prior neurophysiologic knowledge like channels configuration and active frequency bands. Motor imagery EEG patterns in spatial-spectral-temporal domain are detected directly from the multidimensional EEG, which may provide insights to the underlying cortical activity patterns. Extensive experiment comparisons have been performed on a benchmark dataset from the famous BCI competition III as well as self-acquired data from healthy subjects and stroke patients. The experimental results demonstrate the superior performance of the proposed method over the contemporary methods. PMID:25986750

  20. Detecting and monitoring aquacultural patterns through multitemporal SAR imagery analysis

    NASA Astrophysics Data System (ADS)

    Profeti, Giuliana; Travaglia, Carlo; Carla, Roberto

    2003-03-01

    The inventory and monitoring of aquaculture areas are essential tools for decision-making at a governmental level in developing countries. With the use of satellite imagery, these tasks can be performed in an accurate, rapid and objective way. This approach is also economically viable, as the worth of aquaculture far outweighs its cost. This paper describes a methodology for identifying and monitoring shrimp farms by means of multi-temporal satellite SAR data. SAR offer all-weather capabilities, an important characteristic since shrimp farms exist in tropical and sub-tropical areas. Moreover, the backscatter effect created by the dykes surrounding the ponds produces a typical pattern which allows the interpreter to distinguish them from other types of water-covered surfaces. However, the presence of speckle noise limits the interpretability of SAR imagery. To increase it, a multi-temporal set of four scenes covering the study area was processed by using a method that enhances time-invariant spatial features and reduces speckle without compromising the geometrical resolution of the images. The enhanced SAR imagery has proved to be valuable in identifying shrimp farm patterns with a field-tested accuracy of more than 90 percent. The methodology reported in this study has been tested with the ground truth obtained under operative conditions in Sri Lanka, thanks to the support of the FAO TCP/SRL/6712 project.

  1. Analysis of RapidEye imagery for agricultural land mapping

    NASA Astrophysics Data System (ADS)

    Sang, Huiyong; Zhang, Jixian; Zhai, Liang; Xie, Wenhan; Sun, Xiaoxia

    2015-12-01

    With the improvement of remote sensing technology, the spatial, structural and texture information of land covers are present clearly in high resolution imagery, which enhances the ability of crop mapping. Since the satellite RapidEye was launched in 2009, high resolution multispectral imagery together with wide red edge band has been utilized in vegetation monitoring. Broad red edge band related vegetation indices improved land use classification and vegetation studies. RapidEye high resolution imagery was used in this study to evaluate the potential of red edge band in agricultural land cover/use mapping using an objected-oriented classification approach. A new object-oriented decision tree classifier was introduced in this study to map agricultural lands in the study area. Besides the five bands of RapidEye image, the vegetation indexes derived from spectral bands and the structural and texture features are utilized as inputs for agricultural land cover/use mapping in the study. The optimization of input features for classification by reducing redundant information improves the mapping precision about 18% for AdaTree. WL decision tree, and 5% for SVM, the accuracy is over 90% for both classifiers.

  2. The ASPRS Digital Imagery Product Guideline Project

    NASA Technical Reports Server (NTRS)

    Ryan, Robert; Kuper, Philip; Stanley, Thomas; Mondello, Charles

    2001-01-01

    The American Society for Photogrammetry and Remote Sensing (ASPRS) Primary Data Acquisition Division is developing a Digital Imagery Product Guideline in conjunction with NASA, the U.S. Geological Survey (USGS), the National Imagery and Mapping Agency (NIMA), academia, and industry. The goal of the guideline is to offer providers and users of digital imagery a set of recommendatons analogous those defined by the ASPRS Aerial Photography 1995 Draft Standard for film-based imagery. This article offers a general outline and description of the Digital Imagery Product Guideline and Digital Imagery Tutorial/Reference documents for defining digital imagery requirements.

  3. Photogrammetric Tools For Panoramic Sector Scan Imagery In The VIDARS Analysis Station

    NASA Astrophysics Data System (ADS)

    Leberl, Franz W.; Kaufmann, Viktor; Gustafson, Glen C.; Stevens, Matt; Kienegger, Erwin

    1985-12-01

    Computer-assisted photo-interpretation is a recent development supported by the advent of numerous interpretation stations. A unique universal station is VIDARS--manufactured by the Richards Corporation of McLean, Virginia--since it has recently been equipped with a new software system that incorporates complex photogrammetric mensuration capabilities. Photo-interpreters typically find it difficult to perform mensuration tasks; therefore the implementation of the photogrammetric functions must not burden the user with a need to understand photogrammetric theories. This paper illustrates a difficult application of VIDARS to sector-scan panoramic film (Long Range Aerial Panoramic--LORAP) imagery and will show how well the user can perform target positioning tasks within his interpretation work.

  4. Choosing a DIVA: a comparison of emerging digital imagery vegetation analysis techniques

    USGS Publications Warehouse

    Jorgensen, Christopher F.; Stutzman, Ryan J.; Anderson, Lars C.; Decker, Suzanne E.; Powell, Larkin A.; Schacht, Walter H.; Fontaine, Joseph J.

    2013-01-01

    Question: What is the precision of five methods of measuring vegetation structure using ground-based digital imagery and processing techniques? Location: Lincoln, Nebraska, USA Methods: Vertical herbaceous cover was recorded using digital imagery techniques at two distinct locations in a mixed-grass prairie. The precision of five ground-based digital imagery vegetation analysis (DIVA) methods for measuring vegetation structure was tested using a split-split plot analysis of covariance. Variability within each DIVA technique was estimated using coefficient of variation of mean percentage cover. Results: Vertical herbaceous cover estimates differed among DIVA techniques. Additionally, environmental conditions affected the vertical vegetation obstruction estimates for certain digital imagery methods, while other techniques were more adept at handling various conditions. Overall, percentage vegetation cover values differed among techniques, but the precision of four of the five techniques was consistently high. Conclusions: DIVA procedures are sufficient for measuring various heights and densities of standing herbaceous cover. Moreover, digital imagery techniques can reduce measurement error associated with multiple observers' standing herbaceous cover estimates, allowing greater opportunity to detect patterns associated with vegetation structure.

  5. Utilizing ERTS-A imagery for tectonic analysis through study of the Bighorn Mountains Region

    NASA Technical Reports Server (NTRS)

    Hoppin, R. A. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. Preliminary vegetation analysis has been undertaken on MSS scene 1085-17294, Oct. 16, 1973 in the Bighorn region. Forest Service maps showing detailed distribution of dominant forest types have been compared with MSS bands 5 and 7 positive transparencies, enlarged positive prints, and color imagery produced on an Addcol viewer. Patterns on the ERTS imagery match those on the Forest Service maps quite well. A tectonic map ovearlay of MSS band 7 of the Bighorn region reveals a strong concentration of linears in the uplift as compared to basins. Folds in the Bighorn Basin are visible where not covered by post-Paleocene deposits. In regions where far less is known of the geology than in this area, it might be possible to predict the subsurface occurrence of folds and lineaments on the basis of imagery analysis and more confidently explore covered areas for concealed oil structures and mineral deposits.

  6. 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.

  7. 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. PMID:24146963

  8. 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

  9. Small UAV-Acquired, High-resolution, Georeferenced Still Imagery

    SciTech Connect

    Ryan Hruska

    2005-09-01

    Currently, small Unmanned Aerial Vehicles (UAVs) are primarily used for capturing and down-linking real-time video. To date, their role as a low-cost airborne platform for capturing high-resolution, georeferenced still imagery has not been fully utilized. On-going work within the Unmanned Vehicle Systems Program at the Idaho National Laboratory (INL) is attempting to exploit this small UAV-acquired, still imagery potential. Initially, a UAV-based still imagery work flow model was developed that includes initial UAV mission planning, sensor selection, UAV/sensor integration, and imagery collection, processing, and analysis. Components to support each stage of the work flow are also being developed. Critical to use of acquired still imagery is the ability to detect changes between images of the same area over time. To enhance the analysts’ change detection ability, a UAV-specific, GIS-based change detection system called SADI or System for Analyzing Differences in Imagery is under development. This paper will discuss the associated challenges and approaches to collecting still imagery with small UAVs. Additionally, specific components of the developed work flow system will be described and graphically illustrated using varied examples of small UAV-acquired still imagery.

  10. Integrating multisource imagery and GIS analysis for mapping Bermuda`s benthic habitats

    SciTech Connect

    Vierros, M.K.

    1997-06-01

    Bermuda is a group of isolated oceanic situated in the northwest Atlantic Ocean and surrounded by the Sargasso Sea. Bermuda possesses the northernmost coral reefs and mangroves in the Atlantic Ocean, and because of its high population density, both the terrestrial and marine environments are under intense human pressure. Although a long record of scientific research exists, this study is the first attempt to comprehensively map the area`s benthic habitats, despite the need for such a map for resource assessment and management purposes. Multi-source and multi-date imagery were used for producing the habitat map due to lack of a complete up-to-date image. Classifications were performed with SPOT data, and the results verified from recent aerial photography and current aerial video, along with extensive ground truthing. Stratification of the image into regions prior to classification reduced the confusing effects of varying water depth. Classification accuracy in shallow areas was increased by derivation of a texture pseudo-channel, while bathymetry was used as a classification tool in deeper areas, where local patterns of zonation were well known. Because of seasonal variation in extent of seagrasses, a classification scheme based on density could not be used. Instead, a set of classes based on the seagrass area`s exposure to the open ocean were developed. The resulting habitat map is currently being assessed for accuracy with promising preliminary results, indicating its usefulness as a basis for future resource assessment studies.

  11. Increased productivity of repair verification by offline analysis of aerial images

    NASA Astrophysics Data System (ADS)

    Villa, Ernesto; Sartelli, Luca; Miyashita, Hiroyuki; Scheruebl, Thomas; Richter, Rigo; Thaler, Thomas

    2010-05-01

    Using AIMSTM to qualify repairs of defects on photomasks is the industry standard. AIMSTM provides a reasonable matching of lithographic imaging performances without the need of wafer prints. The need of utilisation of this capability by photomask manufacturers has risen due to the increased complexity of layouts incorporating aggressive RET and phase shift technologies as well as tighter specifications have pushed aerial image metrology to consider CD performance results in addition to the traditional intensity verification. The content of the paper describes the utilisation of the AIMSTM Repair Verification (RV) software for the verification of aerial images in a mask shop production environment. The software is used to analyze images from various AIMSTM tool generations and the two main routines, Multi Slice Analysis (MSA) and Image Compare (IC), are used to compare defective and non-defective areas of aerial images. It is detailed how the RV software cleans "non real" errors potentially induced by operator misjudgements, thus providing accurate and repeatable analyses all proven against the results achieved manually. A user friendly GUI drives the user through few simple, fast and safe operations and automatically provides summary tables containing all the relevant results of the analysis that can be easily exported in a proper format and sent out to the customer as a technical documentation. This results in a sensible improvement of the throughput of the printability evaluation process in a mask manufacturing environment, providing reliable analyses at a higher productivity.

  12. Satellite geological and geophysical remote sensing of Iceland: Preliminary results from analysis of MSS imagery

    NASA Technical Reports Server (NTRS)

    Williams, R. S., Jr.; Boedvarsson, A.; Fridriksson, S.; Palmason, G.; Rist, S.; Sigtryggsson, H.; Thorarinsson, S.; Thorsteinsson, I.

    1973-01-01

    A binational, multidisciplinary research effort in Iceland is directed at an analysis of MSS imagery from ERTS-1 to study a variety of geologic, hydrologic, oceanographic, and agricultural phenomena. A preliminary evaluation of available MSS imagery of Iceland has yielded several significant results - some of which may have direct importance to the Icelandic economy. Initial findings can be summarized as follows: (1) recent lava flows can be delineated from older flows at Askja and Hekla; (2) MSS imagery from ERTS-1 and VHRR visible and infrared imagery from NOAA-2 recorded the vocanic eruption on Heimaey, Vestmann Islands; (3) coastline changes, particularly changes in the position of bars and beaches along the south coast are mappable; and (4) areas covered with new and residual snow can be mapped, and the appearance of newly fallen snow on ERTS-1, MSS band 7 appears dark where it is melting. ERTS-1 imagery provides a means of updating various types of maps of Iceland and will permit the compilation of special maps specifically aimed at those dynamic environmental phenomena which impact on the Icelandic economy.

  13. A multinomial modeling analysis of the mnemonic benefits of bizarre imagery.

    PubMed

    Riefer, D M; Rouder, J N

    1992-11-01

    A series of experiments was conducted to explore the cognitive processes that mediate the bizarreness effect, that is, the finding that bizarre or unusual imagery is recalled better than common imagery. In all experiments, subjects were presented with noun pairs that were embedded within bizarre or common sentences in a mixed-list design. None of the experiments produced a bizarreness effect for cued recall; however, for two of the experiments, the bizarre noun pairs were remembered significantly better than the common pairs for free recall. To determine if these differences were due to the storage or retrieval of the items, a multinomial model for the analysis of imagery mediation in paired-associate learning was developed and applied to the data from the experiments. The model revealed that bizarre sentences benefited the retrieval of the noun pairs but not their storage within memory. The empirical and modeling results are discussed relative to previous findings and theories on the bizarreness effect. PMID:1435263

  14. LANDSAT imagery analysis: An aid for predicting landslide prone areas for highway construction. [in Arkansas

    NASA Technical Reports Server (NTRS)

    Macdonald, H. C.; Grubbs, R. S.

    1975-01-01

    The most obvious landform features of geologic significance revealed on LANDSAT imagery are linear trends or lineaments. These trends were found to correspond, at least to a large degree, with unmapped faults or complex fracture zones. LANDSAT imagery analysis in northern Arkansas revealed a lineament complex which provides a remarkable correlation with landslide-prone areas along major highway routes. The weathering properties of various rock types, which are considered in designing stable cut slopes and drainage structures, appear to be adversely influenced by the location and trends of LANDSAT defined lineaments. Geologic interpretation of LANDSAT imagery, where applicable and utilized effectively, provides the highway engineer with a tool for predicting and evaluating landslide-prone areas.

  15. Hydrodynamic impact analysis and testing of an unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Bird, Isabel

    Analysis and testing have been conducted to assess the feasibility of a small UAV that can be landed in the water and recovered for continued use. Water landings may be desirable in a number of situations, for example when testing UAVs outside of the territorial waters of the US to avoid violating FAA regulations. Water landings may also be desirable when conducting surveillance missions in marine environments. Although the goal in landing is to have the UAV lightly set down on the water, rough seas or gusty winds may result in a nose-in landing where the UAV essentially impacts the surface of the water. The tested UAV is a flying wing design constructed of expanded polypropylene foam wings with a hollowed out center-section for the avionics. Acceleration data was collected by means of LIS331 3-axis accelerometers positioned at five locations, including the wingtips. This allowed conclusions to be drawn with respect to the loads experienced on impact throughout the airframe. This data was also used to find loads corresponding to the maximum decelerations experienced during impact. These loads were input into a finite element analysis model of the wing spars to determine stress in the wing spars. Upon impact, the airframe experienced high-frequency oscillation. Surprisingly, peak accelerations at the wingtips were observed at up to 15g greater than corresponding accelerations at the center of the fuselage.

  16. Vegetational analysis with Skylab-3 imagery. [Perquimans County, North Carolina

    NASA Technical Reports Server (NTRS)

    Welby, C. W. (Principal Investigator); Holman, R. E.

    1975-01-01

    The author has identified the following significant results. Color infrared photography from Skylab 3 appeared to be superior to ERTS imagery in a vegetational study of northeastern North Carolina. An accuracy of 87% was achieved in delimiting species composition and zonation patterns of three coastal, vegetation classes. A vegetation map of Perquimans County, North Carolina, seemed to have a high degree of correlation with information provided by high altitude U-2 photography. Random verification sites revealed an overall interpretation accuracy above 84%. Comparison of maps drawn utilizing Skylab photography with North Carolina Dept. of Agriculture estimates of crop acreage revealed some marked discrepancies. The chief difference lies in the nonagricultural category in which there is a 30% discrepancy. This fact raised some questions as to the definition of nonagricultural land uses and methods used by the State Dept. of Agriculture to determine actual percentages of crops grown.

  17. Analysis of Jamaican lineaments visible in Seasat-SAR imagery

    NASA Technical Reports Server (NTRS)

    Dixon, T. H.

    1981-01-01

    Three digitally correlated Seasat SAR frames of Jamaica are used to examine the fault-related topography of the island. The major fault-controlled lineaments visible in the imagery are described, and some generalizations are made with respect to the recent tectonics of Jamaica. It is suggested that: (1) the island of Jamaica may represent the original position of a bend or discontinuity in the northern Caribbean Plate boundary; (2) the present tectonic regime may indicate the complex modification of a regional stress field at a discontinuity in an otherwise linear shear zone; (3) the island represents a tectonically maintained mass excess; and (4) the observed rapid uplift along the island's north coast may be related to compression-induced reverse faulting.

  18. Multistage, Multiband and sequential imagery to identify and quantify non-forest vegetation resources

    NASA Technical Reports Server (NTRS)

    Driscoll, R. S.

    1971-01-01

    Analysis and recognition processing of multispectral scanner imagery for plant community classification and interpretations of various film-filter-scale aerial photographs are reported. Data analyses and manuscript preparation of research on microdensitometry for plant community and component identification and remote estimates of biomass are included.

  19. Applicability of ERTS-1 imagery to the study of suspended sediment and aquatic fronts

    NASA Technical Reports Server (NTRS)

    Klemas, V.; Srna, R.; Treasure, W.; Otley, M.

    1973-01-01

    Imagery from three successful ERTS-1 passes over the Delaware Bay and Atlantic Coastal Region have been evaluated to determine visibility of aquatic features. Data gathered from ground truth teams before and during the overflights, in conjunction with aerial photographs taken at various altitudes, were used to interpret the imagery. The overpasses took place on August 16, October 10, 1972, and January 26, 1973, with cloud cover ranging from about zero to twenty percent. (I.D. Nos. 1024-15073, 1079-15133, and 1187-15140). Visual inspection, density slicing and multispectral analysis of the imagery revealed strong suspended sediment patterns and several distinct types of aquatic interfaces or frontal systems.

  20. Automatic vehicle detection based on automatic histogram-based fuzzy C-means algorithm and perceptual grouping using very high-resolution aerial imagery and road vector data

    NASA Astrophysics Data System (ADS)

    Ghaffarian, Saman; Gökaşar, Ilgın

    2016-01-01

    This study presents an approach for the automatic detection of vehicles using very high-resolution images and road vector data. Initially, road vector data and aerial images are integrated to extract road regions. Then, the extracted road/street region is clustered using an automatic histogram-based fuzzy C-means algorithm, and edge pixels are detected using the Canny edge detector. In order to automatically detect vehicles, we developed a local perceptual grouping approach based on fusion of edge detection and clustering outputs. To provide the locality, an ellipse is generated using characteristics of the candidate clusters individually. Then, ratio of edge pixels to nonedge pixels in the corresponding ellipse is computed to distinguish the vehicles. Finally, a point-merging rule is conducted to merge the points that satisfy a predefined threshold and are supposed to denote the same vehicles. The experimental validation of the proposed method was carried out on six very high-resolution aerial images that illustrate two highways, two shadowed roads, a crowded narrow street, and a street in a dense urban area with crowded parked vehicles. The evaluation of the results shows that our proposed method performed 86% and 83% in overall correctness and completeness, respectively.

  1. Aerial Image Systems

    NASA Astrophysics Data System (ADS)

    Clapp, Robert E.

    1987-09-01

    Aerial images produce the best stereoscopic images of the viewed world. Despite the fact that every optic in existence produces an aerial image, few persons are aware of their existence and possible uses. Constant reference to the eye and other optical systems have produced a psychosis of design that only considers "focal planes" in the design and analysis of optical systems. All objects in the field of view of the optical device are imaged by the device as an aerial image. Use of aerial images in vision and visual display systems can provide a true stereoscopic representation of the viewed world. This paper discusses aerial image systems - their applications and designs and presents designs and design concepts that utilize aerial images to obtain superior visual displays, particularly with application to visual simulation.

  2. Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients.

    PubMed

    Wang, Li; Zhang, Jingna; Zhang, Ye; Yan, Rubing; Liu, Hongliang; Qiu, Mingguo

    2016-01-01

    Aims. Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients. Methods. Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery. Results. Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1), the premotor cortex (PMC), and the supplementary motor area (SMA) in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere. Conclusions. The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function. PMID:27200373

  3. Object-Oriented Analysis of Sea Ice Fragmentation Using SAR Imagery to Determine Pacific Walrus Habitat

    NASA Astrophysics Data System (ADS)

    Brigham, C.; Kolkowitz, I.; Dolson, M.; Rudy, J.; Brooks, A.; Hiatt, C.; Schmidt, C. L.; Skiles, J.

    2006-12-01

    Changes in climate are causing alterations in sea ice formation resulting in a changing habitat for Pacific walrus (Odobenus rosmarus divergens). Students from NASA Ames Research Center's DEVELOP Internship Program worked with the US Fish and Wildlife Service (USFWS) in Alaska to assess the use of satellite imagery for studying walrus habitat on sea ice. Few studies use satellite imagery to observe marine mammal habitats in polar regions because of the difficulty in obtaining imagery and georeferenced data points of species location for the same time period. This study used a method for sea ice image analysis that incorporated remote sensing segmentation and classification techniques with RADARSAT1 SAR (Synthetic Aperture Radar) imagery. Results were correlated with ground point data to determine the relationships of sea ice features to walrus' preferred habitat. MODIS data were utilized, where possible, to verify the classifications of sea ice surfaces obtained by RADARSAT1. The goal of the study was to define geophysical information from radar images that correlate with georeferenced species data points for the same time period. The students determined that walrus prefer thin to medium ice thicknesses. This finding means that aircraft census of walrus populations will not need to be done over areas of thick ice, saving flight time and allowing USFWS personnel to concentrate on locations where walrus populations can be expected to be found.

  4. A geologic analysis of the Side-Looking Airborne Radar imagery of southern New England

    USGS Publications Warehouse

    Banks, Paul T.

    1975-01-01

    Analysis of the side looking airborn radar imagery of Massachusetts, Connecticut and Rhode Island indicates that radar shows the topography in great detail. Since bedrock geologic features are frequently expressed in the topography the radar lends itself to geologic interpretation. The radar was studied by comparisons with field mapped geologic data first at a scale of approximately 1:125,000 and then at a scale of 1:500,000. The larger scale comparison revealed that faults, minor faults, joint sets, bedding and foliation attitudes, lithology and lithologic contacts all have a topographic expression interpretable on the imagery. Surficial geologic features were far less visible on the imagery over most of the area studied. The smaller scale comparisons revealed a pervasive, near orthogonal fracture set cutting all types and ages of rock and trending roughly N40?E and N30?W. In certain places the strike of bedding and foliation attitudes and some lithologic Contacts were visible in addition to the fractures. Fracturing in southern New England is apparently far more important than has been previously recognized. This new information, together with the visibility of many bedding and foliation attitudes and lithologic contacts, indicates the importance of radar imagery in improving the geologic interpretation of an area.

  5. Utilizing ERTS-1 imagery for tectonic analysis through study of the Bighorn Mountains region

    NASA Technical Reports Server (NTRS)

    Hoppin, R. A. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. Comparisons of imagery of three seasons, late summer-fall, winter, and spring indicate that for this region fall imagery is the best for overall geologic analysis. Winter scenes with light to moderate snow cover provide excellent topographic detail owing to snow enhancement, lower sun angle, and clarity of the atmosphere. Spring imagery has considerable reduction of tonal contrast owing to the low reflecting heavy green grass cover which subdues lithologic effects; heavy snow cover in the uplands masks topography. Mapping of geologic formations is impractical in most cases. Separation into tonal units can provide some general clues on structure. A given tonal unit can include parts of several geologic formations and different stratigraphic units can have the same tonal signature. Drainage patterns and anomalies provide the most consistent clues for detecting folds, monoclines, and homoclines. Vegetation only locally reflects lithology and structure. False color infrared 9 x 9 transparencies are the most valuable single imagery. Where these can be supplemented by U-2 color infrared for more detailed work, a tremendous amount of information is available. Adequately field checking such a large area just in one scene is the major logistic problem even in a fairly well known region.

  6. Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients

    PubMed Central

    Wang, Li; Zhang, Jingna; Zhang, Ye; Yan, Rubing; Liu, Hongliang; Qiu, Mingguo

    2016-01-01

    Aims. Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients. Methods. Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery. Results. Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1), the premotor cortex (PMC), and the supplementary motor area (SMA) in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere. Conclusions. The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function. PMID:27200373

  7. Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

    2003-12-01

    Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative

  8. Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

    2004-01-01

    Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative

  9. Strengthened IAEA Safeguards-Imagery Analysis: Geospatial Tools for Nonproliferation Analysis

    SciTech Connect

    Pabian, Frank V

    2012-08-14

    This slide presentation focuses on the growing role and importance of imagery analysis for IAEA safeguards applications and how commercial satellite imagery, together with the newly available geospatial tools, can be used to promote 'all-source synergy.' As additional sources of openly available information, satellite imagery in conjunction with the geospatial tools can be used to significantly augment and enhance existing information gathering techniques, procedures, and analyses in the remote detection and assessment of nonproliferation relevant activities, facilities, and programs. Foremost of the geospatial tools are the 'Digital Virtual Globes' (i.e., GoogleEarth, Virtual Earth, etc.) that are far better than previously used simple 2-D plan-view line drawings for visualization of known and suspected facilities of interest which can be critical to: (1) Site familiarization and true geospatial context awareness; (2) Pre-inspection planning; (3) Onsite orientation and navigation; (4) Post-inspection reporting; (5) Site monitoring over time for changes; (6) Verification of states site declarations and for input to State Evaluation reports; and (7) A common basis for discussions among all interested parties (Member States). Additionally, as an 'open-source', such virtual globes can also provide a new, essentially free, means to conduct broad area search for undeclared nuclear sites and activities - either alleged through open source leads; identified on internet BLOGS and WIKI Layers, with input from a 'free' cadre of global browsers and/or by knowledgeable local citizens (a.k.a.: 'crowdsourcing'), that can include ground photos and maps; or by other initiatives based on existing information and in-house country knowledge. They also provide a means to acquire ground photography taken by locals, hobbyists, and tourists of the surrounding locales that can be useful in identifying and discriminating between relevant and non-relevant facilities and their associated

  10. Automatic aerial image shadow detection through the hybrid analysis of RGB and HIS color space

    NASA Astrophysics Data System (ADS)

    Wu, Jun; Li, Huilin; Peng, Zhiyong

    2015-12-01

    This paper presents our research on automatic shadow detection from high-resolution aerial image through the hybrid analysis of RGB and HIS color space. To this end, the spectral characteristics of shadow are firstly discussed and three kinds of spectral components including the difference between normalized blue and normalized red component - BR, intensity and saturation components are selected as criterions to obtain initial segmentation of shadow region (called primary segmentation). After that, within the normalized RGB color space and HIS color space, the shadow region is extracted again (called auxiliary segmentation) using the OTSU operation, respectively. Finally, the primary segmentation and auxiliary segmentation are combined through a logical AND-connection operation to obtain reliable shadow region. In this step, small shadow areas are removed from combined shadow region and morphological algorithms are apply to fill small holes as well. The experimental results show that the proposed approach can effectively detect the shadow region from high-resolution aerial image and in high degree of automaton.

  11. Calculated Drag of an Aerial Refueling Assembly Through Airplane Performance Analysis

    NASA Technical Reports Server (NTRS)

    Vachon, Michael Jacob; Ray, Ronald J.

    2004-01-01

    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. A standard Navy air refueling store with a retractable refueling hose and paradrogue was mounted to the centerline pylon of the F/A-18A airplane. As the paradrogue assembly was deployed and stowed, changes in the calculated thrust of the airplane occurred and were equated to changes in vehicle drag. These drag changes were attributable to the drag of the paradrogue assembly. The drag of the paradrogue assembly was determined to range from 200 to 450 lbf at airspeeds from 170 to 250 KIAS. Analysis of the drag data resulted in a single drag coefficient of 0.0056 for the paradrogue assembly that adequately matched the calculated drag for all flight conditions. The drag relief provided to the tanker airplane when a receiver airplane engaged the paradrogue is also documented from 35 to 270 lbf at the various flight conditions tested. The results support the development of accurate aerodynamic models to be used in refueling simulations and control laws for fully autonomous refueling.

  12. Land utilization and ecological aspects in the Sylhet-Mymensingh Haor Region of Bangladesh: An analysis of LANDSAT data

    NASA Technical Reports Server (NTRS)

    Chowdhury, M. I.; Elahi, K. M.

    1977-01-01

    The use of remote sensing data from LANDSAT (ERTS) imageries in identifying, evaluating and mapping land use patterns of the Haor area in Bangladesh was investigated. Selected cloud free imageries of the area for the period 1972-75 were studied. Imageries in bands 4, 5 and 7 were mostly used. The method of analysis involved utilization of both human and computer services of information from ground, aerial photographs taken during this period and space imageries.

  13. Lineament extraction and analysis, comparison of LANDSAT ETM and ASTER imagery. Case study: Suoimuoi tropical karst catchment, Vietnam

    NASA Astrophysics Data System (ADS)

    Hung, L. Q.; Batelaan, O.; De Smedt, F.

    2005-10-01

    Vast areas of the world consist of hard rocks (basement complexes), where water is restricted to secondary permeability, and thus to the fractures and the weathered zones. As the success ratio of drilling in hard rock terrain may be low, and the use of geophysics is often judged as too expensive, the study of lineaments from remote sensed imagery offers an attractive alternative analysis technique. High production areas in hard-rock aquifers are generally associated with conductive fracture zones. An effective approach for delineation of fracture zones is based on lineament indices extracted from satellite imagery. Together with a detailed structural analysis and understanding of the tectonic evolution of a given area it provides useful information for geological mapping and understanding of groundwater flow and occurrence in fractured rocks. The accuracy of extracted lineaments depends strongly on the spatial resolution of the imagery, higher resolution imagery result in a higher quality of lineament map. The ASTER sensor provides imagery with a higher resolution (15m) than the LANDSAT sensor (30m). It is tested and shown here that extracted lineaments from the VNIR ASTER imagery are considerably less noisy and show a higher accuracy than lineaments extracted from other imagery.

  14. Reevaluating brain networks activated during mental imagery of finger movements using probabilistic Tensorial Independent Component Analysis (TICA).

    PubMed

    Sauvage, Chloé; Poirriez, S; Manto, Mario; Jissendi, Patrice; Habas, Christophe

    2011-06-01

    The cerebral and cerebellar networks involved in execution and mental imagery of the same sequential finger movements performed with the non-dominant hand were assessed by 3T functional magnetic resonance imaging using multivariate model-free analysis. Eight right-handed healthy volunteers successively performed execution and mental imagery tasks (sequential thumb to fingers opposition). The same data were analyzed by using (1) the linear General Model (p < 0.05 corrected), and (2) probabilistic tensorial independent component analysis (TICA). TICA confirmed that overt movement execution and motor imagery share a common network mainly including: premotor, parietal, insular, temporal, cerebellar cortices and putamen. Motor imagery specifically and bilaterally recruited frontopolar, prefrontal, cingulate, medial insula, neocerebellar cortices and precuneus. Non-dominant hand movements induced bilateral brain and cerebellar activation. In comparison with GLM, TICA identified a more widespread and bilateral network especially during motor imagery. TICA revealed that motor imagery also recruits frontopolar precuneal and occipital cortices, rostral M1/S1 corresponding to the hand somatotopic representation, thalamus and cerebellar lobule VIII. TICA also showed concomitant activation of (1) a cerebello-thalamo-cortical network during motor execution, and (2) a control executive network during imagination. TICA therefore allows precise identification of the brain networks collaborating in the same performance. TICA constitutes a valuable tool to assess and improve detection of brain networks engaged in mental imagery in comparison with GLM.

  15. A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management.

    PubMed

    Hocraffer, Amy; Nam, Chang S

    2017-01-01

    A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm's level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field.

  16. Identifying Contingency Requirements using Obstacle Analysis on an Unpiloted Aerial Vehicle

    NASA Technical Reports Server (NTRS)

    Lutz, Robyn R.; Nelson, Stacy; Patterson-Hine, Ann; Frost, Chad R.; Tal, Doron

    2005-01-01

    This paper describes experience using Obstacle Analysis to identify contingency requirements on an unpiloted aerial vehicle. A contingency is an operational anomaly, and may or may not involve component failure. The challenges to this effort were: ( I ) rapid evolution of the system while operational, (2) incremental autonomy as capabilities were transferred from ground control to software control and (3) the eventual safety-criticality of such systems as they begin to fly over populated areas. The results reported here are preliminary but show that Obstacle Analysis helped (1) identify new contingencies that appeared as autonomy increased; (2) identify new alternatives for handling both previously known and new contingencies; and (3) investigate the continued validity of existing software requirements for contingency handling. Since many mobile, intelligent systems are built using a development process that poses the same challenges, the results appear to have applicability to other similar systems.

  17. A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management.

    PubMed

    Hocraffer, Amy; Nam, Chang S

    2017-01-01

    A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm's level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. PMID:27633199

  18. Statistical techniques applied to aerial radiometric surveys (STAARS): principal components analysis user's manual. [NURE program

    SciTech Connect

    Koch, C.D.; Pirkle, F.L.; Schmidt, J.S.

    1981-01-01

    A Principal Components Analysis (PCA) has been written to aid in the interpretation of multivariate aerial radiometric data collected by the US Department of Energy (DOE) under the National Uranium Resource Evaluation (NURE) program. The variations exhibited by these data have been reduced and classified into a number of linear combinations by using the PCA program. The PCA program then generates histograms and outlier maps of the individual variates. Black and white plots can be made on a Calcomp plotter by the application of follow-up programs. All programs referred to in this guide were written for a DEC-10. From this analysis a geologist may begin to interpret the data structure. Insight into geological processes underlying the data may be obtained.

  19. 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

  20. Jakobshavn Isbrae, Greenland: DEMs, orthophotos, surface velocities, and ice loss derived from photogrammetric re-analysis of July 1985 repeat aerial photography

    NASA Astrophysics Data System (ADS)

    Motyka, R.; Fahnestock, M.; Howat, I.; Truffer, M.; Brecher, H.; Luethi, M.

    2008-12-01

    Jakobshavn Isbrae drains about 7 % of the Greenland Ice Sheet and is the ice sheet's largest outlet glacier. Two sets of high elevation (~13,500 m), high resolution (2 m) aerial photographs of Jakobshavn Isbrae were obtained about two weeks apart during July 1985 (Fastook et al, 1995). These historic photo sets have become increasingly important for documenting and understanding the dynamic state of this outlet stream prior to the rapid retreat and massive ice loss that began in 1998 and continues today. The original photogrammetric analysis of this imagery is summarized in Fastook et al. (1995). They derived a coarse DEM (3 km grid spacing) covering an area of approximately 100 km x 100 km by interpolating several hundred positions determined manually from block-aerial triangulation. We have re-analyzed these photos sets using digital photogrammetry (BAE Socet Set©) and significantly improved DEM quality and resolution (20, 50, and 100 m grids). The DEMs were in turn used to produce high quality orthophoto mosaics. Comparing our 1985 DEM to a DEM we derived from May 2006 NASA ATM measurements showed a total ice volume loss of ~ 105 km3 over the lower drainage area; almost all of this loss has occurred since 1997. Ice stream surface velocities derived from the 1985 orthomosaics showed speeds of 20 m/d on the floating tongue, diminishing to 5 m/d at 50 km further upstream. Velocities have since nearly doubled along the ice stream during its current retreat. Fastook, J.L., H.H. Brecher, and T.J. Hughes, 1995. J.of Glaciol. 11 (137), 161-173.

  1. Vegetation analysis in the Laramie Basin, Wyoming from ERTS-1 imagery

    NASA Technical Reports Server (NTRS)

    Evans, M. A.; Redfern, F. R.

    1973-01-01

    The author has identified the following significant results. The application of ERTS-1 imagery to vegetation mapping and identification was tested and confirmed by field checking. ERTS-1 imagery interpretation and density contour mapping allows definition of minute vegetation features and estimation of vegetative biomass and species composition. Large- and small-scale vegetation maps were constructed for test areas in the Laramie Basin and Laramie mountains of Wyoming. Vegetative features reflecting grazing intensity, moisture availability, changes within the growing season, cutting of hay crops, and plant community constituents in forest and grassland are discussed and illustrated. Theoretical considerations of scattering, sun angle, slope, and instrument aperture upon image and map resolution were investigated. Future suggestions for applications of ERTS-1 data to vegetative analysis are included.

  2. SPECTRUM analysis of multispectral imagery in conjunction with wavelet/KLT data compression

    SciTech Connect

    Bradley, J.N.; Brislawn, C.M.

    1993-12-01

    The data analysis program, SPECTRUM, is used for fusion, visualization, and classification of multi-spectral imagery. The raw data used in this study is Landsat Thematic Mapper (TM) 7-channel imagery, with 8 bits of dynamic range per channel. To facilitate data transmission and storage, a compression algorithm is proposed based on spatial wavelet transform coding and KLT decomposition of interchannel spectral vectors, followed by adaptive optimal multiband scalar quantization. The performance of SPECTRUM clustering and visualization is evaluated on compressed multispectral data. 8-bit visualizations of 56-bit data show little visible distortion at 50:1 compression and graceful degradation at higher compression ratios. Two TM images were processed in this experiment: a 1024 x 1024-pixel scene of the region surrounding the Chernobyl power plant, taken a few months before the reactor malfunction, and a 2048 x 2048 image of Moscow and surrounding countryside.

  3. An evaluation of the use of ERTS-1 satellite imagery for grizzly bear habitat analysis

    NASA Technical Reports Server (NTRS)

    Varney, J. R.; Craighead, J. J.; Sumner, J.

    1973-01-01

    Multispectral scanner images taken by the ERTS-1 satellite in August and October, 1972, were examined to determine if they would be useful in identifying and mapping favorable habitat for grizzly bears. It was possible to identify areas having a suitable mixture of alpine meadow and timber, and to eliminate those which did not meet the isolation requirements of grizzlies because of farming or grazing activity. High altitude timbered areas mapped from satellite imagery agreed reasonably well with the distribution of whitebark pine, an important food species. Analysis of satellite imagery appears to be a valuable supplement to present ground observation methods, since it allows the most important areas to be identified for intensive study and many others to be eliminated from consideration. A sampling plan can be developed from such data which will minimize field effort and overall program cost.

  4. Analysis of forest-fire smoke using satellite imagery. Master's thesis

    SciTech Connect

    De Vries, P.J.

    1989-03-01

    NOAA-9 AVHRR data from 17 and 18 September 1987 were used to perform forest-fire smoke analysis and tracking. The analysis included alignment, subtraction and division of image digital values to produce an Aerosol Particle Size Index (S12) after Frost (1988). S12 provides information about the slope of the aerosol particle size distribution curve and can be used to infer particle-size distribution changes over time. The results provide evidence that the smoke aging process may be successfully studied using satellite imagery, provided careful analysis and removal of background effects are performed.

  5. 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

  6. A Jamesonian Analysis of "Flat World" Imagery in Education Discourse

    ERIC Educational Resources Information Center

    Collin, Ross

    2016-01-01

    This article presents a discourse analysis of Kylene Beers' presidential address to the 2009 conference of the National Council of Teachers of English (NCTE-USA). The address, titled "Sailing over the Edge: Navigating the Uncharted Waters of a World Gone Flat," calls teachers to reject the standardized education of the industrial order…

  7. 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.

  8. Automated imagery orthorectification pilot

    NASA Astrophysics Data System (ADS)

    Slonecker, E. Terrence; Johnson, Brad; McMahon, Joe

    2009-10-01

    Automated orthorectification of raw image products is now possible based on the comprehensive metadata collected by Global Positioning Systems and Inertial Measurement Unit technology aboard aircraft and satellite digital imaging systems, and based on emerging pattern-matching and automated image-to-image and control point selection capabilities in many advanced image processing systems. Automated orthorectification of standard aerial photography is also possible if a camera calibration report and sufficient metadata is available. Orthorectification of historical imagery, for which only limited metadata was available, was also attempted and found to require some user input, creating a semi-automated process that still has significant potential to reduce processing time and expense for the conversion of archival historical imagery into geospatially enabled, digital formats, facilitating preservation and utilization of a vast archive of historical imagery. Over 90 percent of the frames of historical aerial photos used in this experiment were successfully orthorectified to the accuracy of the USGS 100K base map series utilized for the geospatial reference of the archive. The accuracy standard for the 100K series maps is approximately 167 feet (51 meters). The main problems associated with orthorectification failure were cloud cover, shadow and historical landscape change which confused automated image-to-image matching processes. Further research is recommended to optimize automated orthorectification methods and enable broad operational use, especially as related to historical imagery archives.

  9. Analysis of Unmanned Aerial Vehicle (UAV) hyperspectral remote sensing monitoring key technology in coastal wetland

    NASA Astrophysics Data System (ADS)

    Ma, Yi; Zhang, Jie; Zhang, Jingyu

    2016-01-01

    The coastal wetland, a transitional zone between terrestrial ecosystems and marine ecosystems, is the type of great value to ecosystem services. For the recent 3 decades, area of the coastal wetland is decreasing and the ecological function is gradually degraded with the rapid development of economy, which restricts the sustainable development of economy and society in the coastal areas of China in turn. It is a major demand of the national reality to carry out the monitoring of coastal wetlands, to master the distribution and dynamic change. UAV, namely unmanned aerial vehicle, is a new platform for remote sensing. Compared with the traditional satellite and manned aerial remote sensing, it has the advantage of flexible implementation, no cloud cover, strong initiative and low cost. Image-spectrum merging is one character of high spectral remote sensing. At the same time of imaging, the spectral curve of each pixel is obtained, which is suitable for quantitative remote sensing, fine classification and target detection. Aimed at the frontier and hotspot of remote sensing monitoring technology, and faced the demand of the coastal wetland monitoring, this paper used UAV and the new remote sensor of high spectral imaging instrument to carry out the analysis of the key technologies of monitoring coastal wetlands by UAV on the basis of the current situation in overseas and domestic and the analysis of developing trend. According to the characteristic of airborne hyperspectral data on UAV, that is "three high and one many", the key technology research that should develop are promoted as follows: 1) the atmosphere correction of the UAV hyperspectral in coastal wetlands under the circumstance of complex underlying surface and variable geometry, 2) the best observation scale and scale transformation method of the UAV platform while monitoring the coastal wetland features, 3) the classification and detection method of typical features with high precision from multi scale

  10. Terrestrial and aerial laser scanning data integration using wavelet analysis for the purpose of 3D building modeling.

    PubMed

    Kedzierski, Michal; Fryskowska, Anna

    2014-07-07

    Visualization techniques have been greatly developed in the past few years. Three-dimensional models based on satellite and aerial imagery are now being enhanced by models generated using Aerial Laser Scanning (ALS) data. The most modern of such scanning systems have the ability to acquire over 50 points per square meter and to register a multiple echo, which allows the reconstruction of the terrain together with the terrain cover. However, ALS data accuracy is less than 10 cm and the data is often incomplete: there is no information about ground level (in most scanning systems), and often around the facade or structures which have been covered by other structures. However, Terrestrial Laser Scanning (TLS) not only acquires higher accuracy data (1-5 cm) but is also capable of registering those elements which are incomplete or not visible using ALS methods (facades, complicated structures, interiors, etc.). Therefore, to generate a complete 3D model of a building in high Level of Details, integration of TLS and ALS data is necessary. This paper presents the wavelet-based method of processing and integrating data from ALS and TLS. Methods of choosing tie points to combine point clouds in different datum will be analyzed.

  11. Terrestrial and Aerial Laser Scanning Data Integration Using Wavelet Analysis for the Purpose of 3D Building Modeling

    PubMed Central

    Kedzierski, Michal; Fryskowska, Anna

    2014-01-01

    Visualization techniques have been greatly developed in the past few years. Three-dimensional models based on satellite and aerial imagery are now being enhanced by models generated using Aerial Laser Scanning (ALS) data. The most modern of such scanning systems have the ability to acquire over 50 points per square meter and to register a multiple echo, which allows the reconstruction of the terrain together with the terrain cover. However, ALS data accuracy is less than 10 cm and the data is often incomplete: there is no information about ground level (in most scanning systems), and often around the facade or structures which have been covered by other structures. However, Terrestrial Laser Scanning (TLS) not only acquires higher accuracy data (1–5 cm) but is also capable of registering those elements which are incomplete or not visible using ALS methods (facades, complicated structures, interiors, etc.). Therefore, to generate a complete 3D model of a building in high Level of Details, integration of TLS and ALS data is necessary. This paper presents the wavelet-based method of processing and integrating data from ALS and TLS. Methods of choosing tie points to combine point clouds in different datum will be analyzed. PMID:25004157

  12. Detection of Harbours from High Resolution Remote Sensing Imagery via Saliency Analysis and Feature Learning

    NASA Astrophysics Data System (ADS)

    Wang, Yetianjian; Pan, Li; Wang, Dagang; Kang, Yifei

    2016-06-01

    Harbours are very important objects in civil and military fields. To detect them from high resolution remote sensing imagery is important in various fields and also a challenging task. Traditional methods of detecting harbours mainly focus on the segmentation of water and land and the manual selection of knowledge. They do not make enough use of other features of remote sensing imagery and often fail to describe the harbours completely. In order to improve the detection, a new method is proposed. First, the image is transformed to Hue, Saturation, Value (HSV) colour space and saliency analysis is processed via the generation and enhancement of the co-occurrence histogram to help detect and locate the regions of interest (ROIs) that is salient and may be parts of the harbour. Next, SIFT features are extracted and feature learning is processed to help represent the ROIs. Then, by using classified feature of the harbour, a classifier is trained and used to check the ROIs to find whether they belong to the harbour. Finally, if the ROIs belong to the harbour, a minimum bounding rectangle is formed to include all the harbour ROIs and detect and locate the harbour. The experiment on high resolution remote sensing imagery shows that the proposed method performs better than other methods in precision of classifying ROIs and accuracy of completely detecting and locating harbours.

  13. Analysis of temporal dynamics in imagery during acute limb ischemia and reperfusion

    NASA Astrophysics Data System (ADS)

    Irvine, John M.; Regan, John; Spain, Tammy A.; Caruso, Joseph D.; Rodriquez, Maricela; Luthra, Rajiv; Forsberg, Jonathon; Crane, Nicole J.; Elster, Eric

    2014-03-01

    Ischemia and reperfusion injuries present major challenges for both military and civilian medicine. Improved methods for assessing the effects and predicting outcome could guide treatment decisions. Specific issues related to ischemia and reperfusion injury can include complications arising from tourniquet use, such as microvascular leakage in the limb, loss of muscle strength and systemic failures leading to hypotension and cardiac failure. Better methods for assessing the viability of limbs/tissues during ischemia and reducing complications arising from reperfusion are critical to improving clinical outcomes for at-risk patients. The purpose of this research is to develop and assess possible prediction models of outcome for acute limb ischemia using a pre-clinical model. Our model relies only on non-invasive imaging data acquired from an animal study. Outcome is measured by pathology and functional scores. We explore color, texture, and temporal features derived from both color and thermal motion imagery acquired during ischemia and reperfusion. The imagery features form the explanatory variables in a model for predicting outcome. Comparing model performance to outcome prediction based on direct observation of blood chemistry, blood gas, urinalysis, and physiological measurements provides a reference standard. Initial results show excellent performance for the imagery-base model, compared to predictions based direct measurements. This paper will present the models and supporting analysis, followed by recommendations for future investigations.

  14. A parallel environment for structural analysis of range imagery

    SciTech Connect

    Perez, A.; Abidi, M.A.; Gonzalez, R.C.

    1988-01-01

    Rigid objects can be modeled by quadric or planar polyhedra. This representation allows low-level data driven algorithms to determine the identity and pose of an object. Before an object can be matched with an internal model, however, its image must be first segmented into basic components, such as smooth patches. This paper describes a low-level parallel range data analysis system that uses input range data to characterize the underlying scene in terms of the visible surfaces, using simple, invariant features to generate a view independent description of the scene. The central components of the system are a parallel segmenter and a parallel surface fitter. The segmentation algorithms are based on the estimation of surface curvatures. Surface fitting allows for pose estimation and recognition of objects in range scenes. Mathematically, surface fitting can be formulated as an overdetermined linear system which can be solved in the least-square sense. Because of numerical stability and ease of implementation, the QR-factorization using the Givens transformation is suited for the parallel solution of overdetermined systems. We discuss the implementation of the range analysis system on a distributed-memory hypercube parallel computer. 18 refs., 7 figs.

  15. Exploration applications of satellite imagery in mature basins - A summation

    SciTech Connect

    Berger, Z. )

    1991-08-01

    A series of examples supported by surface and subsurface controls illustrates procedures used to integrate satellite imagery interpretation into a conventional exploration program, and the potential contribution of such an approach to the recognition of new hydrocarbon plays in mature basins. Integrated analysis of satellite imagery data consists of four major steps. The first step focuses on the recognition of style, trend, and timing of deformation of exposed structures located at the basin interior or around its margins. This information is obtained through an integrated analysis of satellite imagery data, stereo aerial photography, surface geological mapping, and field observations. The second step consists of integrating the satellite imagery with gravity and magnetic data to recognize obscured and/or buried structures. The third step involves the analysis of available seismic data which is specifically processes to enhance subtle basement topography in order to determine influences on reservoir quality. In the fourth step, subsurface structure, isopach, show, and pool maps derived from available well information are integrated into the structural interpretation. These four analytical steps are demonstrated with examples form the Powder River basin, Western Canada basin, Paris basin, and Central basin platform of west Texas. In all of these highly mature basins, it is easy to demonstrate that (1) hydrocarbon migration and accumulation was largely controlled by subtle basement structures, and (2) these structures can be detected through the integrated analysis of satellite imagery.

  16. Comparative Assessment of Very High Resolution Satellite and Aerial Orthoimagery

    NASA Astrophysics Data System (ADS)

    Agrafiotis, P.; Georgopoulos, A.

    2015-03-01

    This paper aims to assess the accuracy and radiometric quality of orthorectified high resolution satellite imagery from Pleiades-1B satellites through a comparative evaluation of their quantitative and qualitative properties. A Pleiades-B1 stereopair of high resolution images taken in 2013, two adjacent GeoEye-1 stereopairs from 2011 and aerial orthomosaic (LSO) provided by NCMA S.A (Hellenic Cadastre) from 2007 have been used for the comparison tests. As control dataset orthomosaic from aerial imagery provided also by NCMA S.A (0.25m GSD) from 2012 was selected. The process for DSM and orthoimage production was performed using commercial digital photogrammetric workstations. The two resulting orthoimages and the aerial orthomosaic (LSO) were relatively and absolutely evaluated for their quantitative and qualitative properties. Test measurements were performed using the same check points in order to establish their accuracy both as far as the single point coordinates as well as their distances are concerned. Check points were distributed according to JRC Guidelines for Best Practice and Quality Checking of Ortho Imagery and NSSDA standards while areas with different terrain relief and land cover were also included. The tests performed were based also on JRC and NSSDA accuracy standards. Finally, tests were carried out in order to assess the radiometric quality of the orthoimagery. The results are presented with a statistical analysis and they are evaluated in order to present the merits and demerits of the imaging sensors involved for orthoimage production. The results also serve for a critical approach for the usability and cost efficiency of satellite imagery for the production of Large Scale Orthophotos.

  17. Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery

    PubMed Central

    Chaddad, Ahmad; Desrosiers, Christian; Bouridane, Ahmed; Toews, Matthew; Hassan, Lama; Tanougast, Camel

    2016-01-01

    Purpose This paper proposes to characterize the continuum of colorectal cancer (CRC) using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT) are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma. Materials and Methods In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG) filter, discrete wavelets (DW) and gray level co-occurrence matrices (GLCM). To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models. Results Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01). Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%. Conclusions These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images. PMID:26901134

  18. Autonomous Particle Recognition and Analysis of Carbon Flux Explorer Imagery

    NASA Astrophysics Data System (ADS)

    Hamilton, C. M.; Bishop, J. K.; Wood, T.

    2013-12-01

    The biologically mediated export, or sedimentation, of particulate organic carbon to ocean depths below 100 m is approximately 10 Pg C per year and is highly variable in space and time. Despite the need to understand the biological drivers for export and the depth dependence of carbon remineralization for carbon cycle prediction, there are scant observations of sedimentation dynamics in the upper 1000 m. The Carbon Flux Explorer (CFE) is a robotic ocean profiling system, which combines the Scripps Sounding Oceanographic Lagrangian Observer (SOLO) and the LBNL/Berkeley optical sedimentation recorder. The CFE is designed to conduct high-frequency (hourly) observations of particulate organic and inorganic carbon sedimentation to kilometer depths, absent of ships, in all sea conditions, be reprogrammable and adaptive once deployed, and relay data to shore in near real time via Iridium satellite links for seasons to years. The CFE operates by sequentially imaging settled particles at ~15 micrometer size resolution in transmitted, transmitted cross-polarized, and dark field illumination. At present, these images must be stored on the CFE until recovery. In other words, the CFE is deployable in the context of multi-month long process studies. Here we present progress on particle recognition and quantification methodology, which will enable a 100,000:1 compression of image data needed for efficient satellite telemetry and fully autonomous real-time operation. Our methodology includes corrective thresh-holding, cross imaging comparison, distinction of aggregates from organisms, and the classification of particle properties including particle fractal dimension. We also look at these findings in context of particle vertical velocity, float performance, and oceanic conditions. Data analysis examples drawing on recent CFE missions to California coastal and offshore waters and to the subarctic N Pacific ocean, some lasting 41 days, will be presented.

  19. 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

  20. 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. PMID:25902148

  1. 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.

  2. A study of the effects of degraded imagery on tactical 3D model generation using structure-from-motion

    NASA Astrophysics Data System (ADS)

    Bolick, Leslie; Harguess, Josh

    2016-05-01

    An emerging technology in the realm of airborne intelligence, surveillance, and reconnaissance (ISR) systems is structure-from-motion (SfM), which enables the creation of three-dimensional (3D) point clouds and 3D models from two-dimensional (2D) imagery. There are several existing tools, such as VisualSFM and open source project OpenSfM, to assist in this process, however, it is well-known that pristine imagery is usually required to create meaningful 3D data from the imagery. In military applications, such as the use of unmanned aerial vehicles (UAV) for surveillance operations, imagery is rarely pristine. Therefore, we present an analysis of structure-from-motion packages on imagery that has been degraded in a controlled manner.

  3. Unmanned Aerial Mass Spectrometer Systems for In-Situ Volcanic Plume Analysis

    NASA Astrophysics Data System (ADS)

    Diaz, Jorge Andres; Pieri, David; Wright, Kenneth; Sorensen, Paul; Kline-Shoder, Robert; Arkin, C. Richard; Fladeland, Matthew; Bland, Geoff; Buongiorno, Maria Fabrizia; Ramirez, Carlos; Corrales, Ernesto; Alan, Alfredo; Alegria, Oscar; Diaz, David; Linick, Justin

    2015-02-01

    Technology advances in the field of small, unmanned aerial vehicles and their integration with a variety of sensor packages and instruments, such as miniature mass spectrometers, have enhanced the possibilities and applications of what are now called unmanned aerial systems (UAS). With such technology, in situ and proximal remote sensing measurements of volcanic plumes are now possible without risking the lives of scientists and personnel in charge of close monitoring of volcanic activity. These methods provide unprecedented, and otherwise unobtainable, data very close in space and time to eruptions, to better understand the role of gas volatiles in magma and subsequent eruption products. Small mass spectrometers, together with the world's smallest turbo molecular pump, have being integrated into NASA and University of Costa Rica UAS platforms to be field-tested for in situ volcanic plume analysis, and in support of the calibration and validation of satellite-based remote sensing data. These new UAS-MS systems are combined with existing UAS flight-tested payloads and assets, such as temperature, pressure, relative humidity, SO2, H2S, CO2, GPS sensors, on-board data storage, and telemetry. Such payloads are capable of generating real time 3D concentration maps of the Turrialba volcano active plume in Costa Rica, while remote sensing data are simultaneously collected from the ASTER and OMI space-borne instruments for comparison. The primary goal is to improve the understanding of the chemical and physical properties of emissions for mitigation of local volcanic hazards, for the validation of species detection and abundance of retrievals based on remote sensing, and to validate transport models.

  4. 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.

  5. Unmanned aerial mass spectrometer systems for in-situ volcanic plume analysis.

    PubMed

    Diaz, Jorge Andres; Pieri, David; Wright, Kenneth; Sorensen, Paul; Kline-Shoder, Robert; Arkin, C Richard; Fladeland, Matthew; Bland, Geoff; Buongiorno, Maria Fabrizia; Ramirez, Carlos; Corrales, Ernesto; Alan, Alfredo; Alegria, Oscar; Diaz, David; Linick, Justin

    2015-02-01

    Technology advances in the field of small, unmanned aerial vehicles and their integration with a variety of sensor packages and instruments, such as miniature mass spectrometers, have enhanced the possibilities and applications of what are now called unmanned aerial systems (UAS). With such technology, in situ and proximal remote sensing measurements of volcanic plumes are now possible without risking the lives of scientists and personnel in charge of close monitoring of volcanic activity. These methods provide unprecedented, and otherwise unobtainable, data very close in space and time to eruptions, to better understand the role of gas volatiles in magma and subsequent eruption products. Small mass spectrometers, together with the world's smallest turbo molecular pump, have being integrated into NASA and University of Costa Rica UAS platforms to be field-tested for in situ volcanic plume analysis, and in support of the calibration and validation of satellite-based remote sensing data. These new UAS-MS systems are combined with existing UAS flight-tested payloads and assets, such as temperature, pressure, relative humidity, SO2, H2S, CO2, GPS sensors, on-board data storage, and telemetry. Such payloads are capable of generating real time 3D concentration maps of the Turrialba volcano active plume in Costa Rica, while remote sensing data are simultaneously collected from the ASTER and OMI space-borne instruments for comparison. The primary goal is to improve the understanding of the chemical and physical properties of emissions for mitigation of local volcanic hazards, for the validation of species detection and abundance of retrievals based on remote sensing, and to validate transport models. PMID:25588720

  6. 'unlocking the Archive': Using Digital Photogrammetry of Modern Airborne Aerial Photography for Analysis of Historic Aerial Photographs to Extend the Record of Glacier Mass Balance Change on the Antarctic Peninsula

    NASA Astrophysics Data System (ADS)

    Clarke, L. E.; Miller, P.; Fox, A. J.; Mills, J. P.

    2014-12-01

    Changes to glacier fronts and ice shelves and glacier acceleration are well documented, but there are almost no data on mass changes for the more than 400 glaciers on the Antarctic Peninsula. Satellite data have been used to calculate change over the last 3 decades, but methods to quantify this over longer timescales have eluded researchers. However there is an archive of aerial photography dating back to the 1940s, this has been largely ignored due to the range of technical problems associated with deriving quantitative data from historic imagery and the lack of ground control data. This presentation demonstrates how advances in photogrammetric processing and capture of modern aerial photography has allowed this archive to be 'unlocked'. Accurate photogrammetric reconstruction from aerial photographs traditionally requires known ground control points acquired in the field; however, in remote and inaccessible areas, such as the Antarctic Peninsula, this is often impossible. A method for providing control for historic photos without fieldwork, by linking them to a newly acquired, highly accurate photogrammetric model adjusted through direct kinematic GPS positioning of the camera has been applied to a number of glaciers across the Antarctic Peninsula. This presentation will outline the photogrammetric workflow and associated errors to highlight the suitability of this technique and demonstrate the data that can be obtained. Accurate measurements of surface elevation change on glaciers on the Antarctic Peninsula over a 70 year time span have enabled quantification of spatial and temporal patterns of change. The results show a general trend of glacier retreat, but with thinning of the glacier terminus marginally offset by accumulation in the upper areas of the glacier. The use of this technique opens up possibilities for 'unlocking the archive' in other remote glacial areas where historic aerial photography exists but the collection of ground control points is limited.

  7. Analysis of the Greenland Ice Sheet's surface hydrology using Synthetic Aperture Radar imagery

    NASA Astrophysics Data System (ADS)

    Miles, Katie; Benedek, Corinne; Tedesco, Marco; Willis, Ian

    2016-04-01

    The behaviour of surface water on the Greenland Ice Sheet (GrIS) has recently received much attention due to its ponding to form supraglacial lakes. These can drain and impact ice sheet dynamics by facilitating increased basal sliding, thus leading to a more rapid transfer of ice to the oceans and contributing to rising sea levels. Research into supraglacial lakes has primarily used the optical and infrared wavelength bands of MODIS due to their high temporal resolution. However, this comes with an associated low spatial resolution, potentially resulting in smaller lakes being overlooked, and an inability to image through clouds or in darkness. Conversely, Synthetic Aperture Radar (SAR), a satellite-borne active imaging method uses microwave wavelength bands which are unaffected by cloud or lack of illumination from the sun. SAR imagery often has a much higher spatial resolution than optical imagery without compromising temporal resolution, and radar systems have even detected lakes covered by ice/snow or buried at shallow depths [Koenig et al., 2015]. This gives SAR imagery the potential to significantly increase the size of the database of supraglacial lakes. The current Sentinel-1A mission comprises two polar-orbiting satellites performing C-band SAR imaging, and provides a novel method for investigating the surface hydrology of the GrIS. Here, we explore a year's worth of images since the launch of Sentinel-1A in April 2014. These images have a higher spatial (5 m x 20 m) and temporal (up to daily) resolution than any previously available imagery, so will revolutionise the amount of information that can be yielded about GrIS hydrology. We use these images in combination with other remotely sensed data, including Landsat-8 imagery, to elicit spatial and temporal variations in the water content of the GrIS's surface ice layers. Our primary focus is on the area upstream of Jakobshavn Isbræ, where preliminary analysis has indicated that liquid water may persist

  8. Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

    NASA Astrophysics Data System (ADS)

    Othman, M. N. K.; Zuradzman, M. Razlan; Hazry, D.; Khairunizam, Wan; Shahriman, A. B.; Yaacob, S.; Ahmed, S. Faiz; Hussain, Abadalsalam T.

    2014-12-01

    This paper explain the analysis of internal air flow velocity of a bladeless vertical takeoff and landing (VTOL) Micro Aerial Vehicle (MAV) hemisphere body. In mechanical design, before produce a prototype model, several analyses should be done to ensure the product's effectiveness and efficiency. There are two types of analysis method can be done in mechanical design; mathematical modeling and computational fluid dynamic. In this analysis, I used computational fluid dynamic (CFD) by using SolidWorks Flow Simulation software. The idea came through to overcome the problem of ordinary quadrotor UAV which has larger size due to using four rotors and the propellers are exposed to environment. The bladeless MAV body is designed to protect all electronic parts, which means it can be used in rainy condition. It also has been made to increase the thrust produced by the ducted propeller compare to exposed propeller. From the analysis result, the air flow velocity at the ducted area increased to twice the inlet air. This means that the duct contribute to the increasing of air velocity.

  9. Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

    SciTech Connect

    Othman, M. N. K. E-mail: zuradzman@unimap.edu.my E-mail: khairunizam@unimap.edu.my E-mail: s.yaacob@unimap.edu.my E-mail: abadal@unimap.edu.my; Zuradzman, M. Razlan E-mail: zuradzman@unimap.edu.my E-mail: khairunizam@unimap.edu.my E-mail: s.yaacob@unimap.edu.my E-mail: abadal@unimap.edu.my; Hazry, D. E-mail: zuradzman@unimap.edu.my E-mail: khairunizam@unimap.edu.my E-mail: s.yaacob@unimap.edu.my E-mail: abadal@unimap.edu.my; Khairunizam, Wan E-mail: zuradzman@unimap.edu.my E-mail: khairunizam@unimap.edu.my E-mail: s.yaacob@unimap.edu.my E-mail: abadal@unimap.edu.my; Shahriman, A. B. E-mail: zuradzman@unimap.edu.my E-mail: khairunizam@unimap.edu.my E-mail: s.yaacob@unimap.edu.my E-mail: abadal@unimap.edu.my; Yaacob, S. E-mail: zuradzman@unimap.edu.my E-mail: khairunizam@unimap.edu.my E-mail: s.yaacob@unimap.edu.my E-mail: abadal@unimap.edu.my; Ahmed, S. Faiz E-mail: zuradzman@unimap.edu.my E-mail: khairunizam@unimap.edu.my E-mail: s.yaacob@unimap.edu.my E-mail: abadal@unimap.edu.my; and others

    2014-12-04

    This paper explain the analysis of internal air flow velocity of a bladeless vertical takeoff and landing (VTOL) Micro Aerial Vehicle (MAV) hemisphere body. In mechanical design, before produce a prototype model, several analyses should be done to ensure the product's effectiveness and efficiency. There are two types of analysis method can be done in mechanical design; mathematical modeling and computational fluid dynamic. In this analysis, I used computational fluid dynamic (CFD) by using SolidWorks Flow Simulation software. The idea came through to overcome the problem of ordinary quadrotor UAV which has larger size due to using four rotors and the propellers are exposed to environment. The bladeless MAV body is designed to protect all electronic parts, which means it can be used in rainy condition. It also has been made to increase the thrust produced by the ducted propeller compare to exposed propeller. From the analysis result, the air flow velocity at the ducted area increased to twice the inlet air. This means that the duct contribute to the increasing of air velocity.

  10. Task-irrelevant alpha component analysis in motor imagery based brain computer interface.

    PubMed

    Lou, Bin; Hong, Bo; Gao, Shangkai

    2008-01-01

    In motor imagery based BCI, the alpha rhythm shares the same frequency band with sensorimotor rhythm (SMR), and does not correlate with mental task, which contaminates the SMR recording. Independent component analysis (ICA) was applied to decompose original EEG signal into source components, and a comprehensive method was proposed to discriminate those source components by combining temporal, frequency, spatial, and class label information. Task-irrelevant alpha components were sorted out and their projections were reduced by proper bipolar electrode placement for improving the BCI performance.

  11. Overview of independent component analysis technique with an application to synthetic aperture radar (SAR) imagery processing.

    PubMed

    Fiori, Simone

    2003-01-01

    We present an overview of independent component analysis, an emerging signal processing technique based on neural networks, with the aim to provide an up-to-date survey of the theoretical streams in this discipline and of the current applications in the engineering area. We also focus on a particular application, dealing with a remote sensing technique based on synthetic aperture radar imagery processing: we briefly review the features and main applications of synthetic aperture radar and show how blind signal processing by neural networks may be advantageously employed to enhance the quality of remote sensing data.

  12. Aerodynamic Analysis of Flexible Flapping Wing Micro Aerial Vehicle Using Quasi-Steady Approach

    NASA Astrophysics Data System (ADS)

    Vijayakumar, Kolandapaiyan; Chandrasekhar, Uttam; Chandrashekhar, Nagaraj

    2016-04-01

    In recent times flexible flapping-wing aerodynamics has generated a great deal of interest and is the topic of contemporary research because of its potential application in micro aerial vehicles (MAVs). The prominent features of MAVs include low Reynolds Number, changing the camber of flapping wings, development of related mechanisms, study of the suitability airfoil shape selection and other parameters. Generally, low Reynolds Number is similar to that of an insect or a bird (103-105). The primary goal of this project work is to perform CFD analysis on flexible flapping wing MAVs in order to estimate the lift and drag by using engineering methods such as quasi-steady approach. From the wind tunnel data, 3-D deformation is obtained. For CFD analysis, two types of quasi-steady methods are considered. The first method is to slice the wing section chord-wise and span wise at multiple regions, frame by frame, and obtain the 2-D corrugated camber section for each frame. This 2-D corrugated camber is analysed using CFD techniques and all the individual 2-D corrugated camber results are summed up frame by frame, to obtain the total lift and drag for one wing beat. The second method is to consider the 3D wing in entirety and perform the CFD analysis to obtain the lift and drag for five wing beat.

  13. Artic and subarctic environmental analyses utilizing ERTS-1 imagery. Cold regions environmental analysis based on ERTS-1 imagery (preprint)

    NASA Technical Reports Server (NTRS)

    Anderson, D. M. (Principal Investigator); Haugen, R. K.; Gatto, L. W.; Slaughter, C. W.; Marlar, T. L.; Mckim, H. L.

    1972-01-01

    There are no author-identified significant results in this report. An overriding problem in arctic and subarctic environmental research has been the absence of long-term observational data and the sparseness of geographical coverage of existing data. A first look report is presented on the use of ERTS-1 imagery as a major tool in two large area environmental studies: (1) investigation of sedimentation and other nearshore marine processes in Cook Inlet, Alaska; and (2) a regional study of permafrost regimes in the discontinuous permafrost zone of Alaska. These studies incorporate ground truth acquisition techniques that are probably similar to most ERTS investigations. Studies of oceanographic processes in Cook Inlet will be focused on seasonal changes in nearshore bathymetry, tidal and major current circulation patterns, and coastal sedimentation processes, applicable to navigation, construction, and maintenance of harbors. Analyses will be made of the regional permafrost distribution and regimes in the Upper Koyukuk-Kobuk River area located in NW Alaska.

  14. Obtaining biophysical measurements of woody vegetation from high resolution digital aerial photography in tropical and arid environments: Northern Territory, Australia

    NASA Astrophysics Data System (ADS)

    Staben, G. W.; Lucieer, A.; Evans, K. G.; Scarth, P.; Cook, G. D.

    2016-10-01

    Biophysical parameters obtained from woody vegetation are commonly measured using field based techniques which require significant investment in resources. Quantitative measurements of woody vegetation provide important information for ecological studies investigating landscape change. The fine spatial resolution of aerial photography enables identification of features such as trees and shrubs. Improvements in spatial and spectral resolution of digital aerial photographic sensors have increased the possibility of using these data in quantitative remote sensing. Obtaining biophysical measurements from aerial photography has the potential to enable it to be used as a surrogate for the collection of field data. In this study quantitative measurements obtained from digital aerial photography captured at ground sampling distance (GSD) of 15 cm (n = 50) and 30 cm (n = 52) were compared to woody biophysical parameters measured from 1 ha field plots. Supervised classification of the aerial photography using object based image analysis was used to quantify woody and non-woody vegetation components in the imagery. There was a high correlation (r ≥ 0.92) between all field measured woody canopy parameters and aerial derived green woody cover measurements, however only foliage projective cover (FPC) was found to be statistically significant (paired t-test; α = 0.01). There was no significant difference between measurements derived from imagery captured at either GSD of 15 cm and 30 cm over the same field site (n = 20). Live stand basal area (SBA) (m2 ha-1) was predicted from the aerial photographs by applying an allometric equation developed between field-measured live SBA and woody FPC. The results show that there was very little difference between live SBA predicted from FPC measured in the field or from aerial photography. The results of this study show that accurate woody biophysical parameters can be obtained from aerial photography from a range of woody vegetation

  15. Cost and effectiveness analysis on unmanned aerial vehicle (UAV) use at border security

    NASA Astrophysics Data System (ADS)

    Yilmaz, Bahadır.

    2013-06-01

    Drones and Remotely Piloted Vehicles are types of Unmanned Aerial Vehicles. UAVs began to be used with the war of Vietnam, they had a great interest when Israel used them in Bekaa Valley Operations of 1982. UAVs have been used by different countries with different aims with the help of emerging technology and investments. In this article, in the context of areas of UAV usage in national security, benefits and disadvantages of UAVs are put forward. Particularly, it has been evaluated on the basis of cost-effectiveness by focusing the use of UAV in the border security. UAVs have been studied by taking cost analysis, procurement and operational costs into consideration. Analysis of effectiveness has been done with illegal passages of people and drugs from flight times of UAVs. Although the procurement cost of the medium-level UAVs is low, its operational costs are high. For this reason, the idea of less costly alternative systems have been revealed for the border security. As the costs are reduced to acceptable level involving national security and border security in future with high-technology products in their structure, it will continue to be used in an increasing proportion.

  16. Thermal Analysis on Cryogenic Liquid Hydrogen Tank on an Unmanned Aerial Vehicle System

    NASA Technical Reports Server (NTRS)

    Wang, Xiao-Yen; Harpster, George; Hunter, James

    2007-01-01

    Thermal analyses are performed on the liquid hydrogen (LH2) tank designed for an unmanned aerial vehicle (UAV) powered by solar arrays and a regenerative proton-exchange membrane (PEM) fuel cell. A 14-day cruise mission at a 65,000 ft altitude is considered. Thermal analysis provides the thermal loads on the tank system and the boiling-off rates of LH2. Different approaches are being considered to minimize the boiling-off rates of the LH2. It includes an evacuated multilayer insulation (MLI) versus aerogel insulation on the LH2 tank and aluminum versus stainless steel spacer rings between the inner and outer tank. The resulting boil-off rates of LH2 provided by the one-dimensional model and three-dimensional finite element analysis (FEA) on the tank system are presented and compared to validate the results of the three-dimensional FEA. It concludes that heat flux through penetrations by conduction is as significant as that through insulation around the tank. The tank system with MLI insulation and stainless steel spacer rings result in the lowest boiling-off rate of LH2.

  17. Measuring Delta Progradation Using Delta Front Flow Patterns: A New Method of Remote Imagery Analysis on the Wax Lake Delta, Louisiana, U.S.A.

    NASA Astrophysics Data System (ADS)

    Estep, J. D.; Shaw, J.; Edmonds, D. A.

    2015-12-01

    Quantifying the progradation of the Wax Lake Delta (WLD), a sub-delta of the Mississippi River Delta, can lend valuable insight into coastal land-building patterns. Previous studies of WLD progradation have relied on subaerially-exposed land for indicating delta extent, but an inherent problem with this method lies in the high variability of exposed land due to vegetative, hydrologic, and atmospheric fluctuations. By mapping water surface films observed in remote imagery which form streaklines along flow paths in the delta, we show that the shallow delta front flow patterns are relatively unaffected by short term water level changes and can be used to evaluate WLD progradation over time. Remotely sensed imagery from multiple sources (infrared aerial photography, SPOT, UAVSAR) spanning from 1988 to 2015 was used to map streaklines from which we calculate a flow direction divergence field across the delta. Measuring the translation of this field through time, such as areas containing extreme divergence values along the delta front, quantifies the progradation over the time elapsed. Preliminary measurements of WLD progradation were subdivided into the eastern, southern, and western thirds of the delta. The eastern third prograded at 110 ±20m/yr from 1988 - 1997, 100 ±40m/yr from 1997 - 2002, and then remained relatively constant to 2015. The southern third prograded at 130 ±20m/yr from 1988 - 1997, 200 ±40m/yr from 1997 - 2002, and remained relatively constant to 2015. The western third prograded at 130 ±30m/yr from 1988 - 1997, 220 ±60 m from 1997 - 2002, and then remained relatively constant from 2002 - 2015. Also of note is the retrogradation on the average of 700 ±400m observed from January to August, 1992 which we interpret as being caused by the impact of Hurricane Andrew. The streakline methodology of evaluating WLD progradation could provide new methods for analysis of land change in other deltas around the world.

  18. Proximity graph analysis for linear networks extraction from high-resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Skourikhine, Alexei N.

    2006-05-01

    Reliable and accurate methods for detection and extraction of linear network, such as road networks, in satellite imagery are essential to many applications. We present an approach to the road network extraction from high-resolution satellite imagery that is based on proximity graph analysis. We are jumping off from the classification provided by existing spectral and textural classification tools, which produce a set of candidate road patches. Then, constrained Delaunay triangulation and Chordal Axis transform are used to extract centerline characterization of the delineated candidate road patches. We refine produced center lines to reduce noise influence on patch boundaries, resulting in a smaller set of robust center lines authentically representing their road patches. Refined center lines are triangulated using constrained Delaunay triangulation (CDT) algorithm to generate a sub-optimal mesh of interconnections among them. The generated triangle edges connecting different center lines are used for spatial analysis of the center lines relations. A subset of the Delaunay tessellation grid contains the Euclidian Minimum Spanning Tree (EMST) that provides an approximation of road network. The approach can be generalized to the multi-criteria MST and multi-criteria shortest path algorithms to integrate other factors important for road network extraction, in addition to proximity relations considered by standard EMST.

  19. Error modeling based on geostatistics for uncertainty analysis in crop mapping using Gaofen-1 multispectral imagery

    NASA Astrophysics Data System (ADS)

    You, Jiong; Pei, Zhiyuan

    2015-01-01

    With the development of remote sensing technology, its applications in agriculture monitoring systems, crop mapping accuracy, and spatial distribution are more and more being explored by administrators and users. Uncertainty in crop mapping is profoundly affected by the spatial pattern of spectral reflectance values obtained from the applied remote sensing data. Errors in remotely sensed crop cover information and the propagation in derivative products need to be quantified and handled correctly. Therefore, this study discusses the methods of error modeling for uncertainty characterization in crop mapping using GF-1 multispectral imagery. An error modeling framework based on geostatistics is proposed, which introduced the sequential Gaussian simulation algorithm to explore the relationship between classification errors and the spectral signature from remote sensing data source. On this basis, a misclassification probability model to produce a spatially explicit classification error probability surface for the map of a crop is developed, which realizes the uncertainty characterization for crop mapping. In this process, trend surface analysis was carried out to generate a spatially varying mean response and the corresponding residual response with spatial variation for the spectral bands of GF-1 multispectral imagery. Variogram models were employed to measure the spatial dependence in the spectral bands and the derived misclassification probability surfaces. Simulated spectral data and classification results were quantitatively analyzed. Through experiments using data sets from a region in the low rolling country located at the Yangtze River valley, it was found that GF-1 multispectral imagery can be used for crop mapping with a good overall performance, the proposal error modeling framework can be used to quantify the uncertainty in crop mapping, and the misclassification probability model can summarize the spatial variation in map accuracy and is helpful for

  20. Analysis of Actual Soil Degradation by Erosion Using Satellite Imagery and Terrain Attributes in the Czech Republic

    NASA Astrophysics Data System (ADS)

    Zizala, Daniel

    2015-04-01

    statistical data of areas under farm crops from Czech Statistical Office. Information on number of scenes where bare soils are identified for each land parcel is available. This set of images with bare soils is used for assessment of soil degradation stage. Some land parcels were found without vegetation cover up to 40 times. Analysis was performed on 5 test sites in the Czech Republic and also using data from database of Soil Erosion Monitoring of Agricultural Land. Currently, more than 500 erosion events are registered in this database. Additional remote sensing data (Hyperion data, aerial hyperspectral data) was used for detailed analysis on the test sites. Results reveal that satellite imagery set, soil maps, terrain attributes and erosion modelling can be successfully applied in assessment of actual soil degradation by erosion. The research has been supported by the project no. QJ330118 "Using Remote Sensing for Monitoring of Soil Degradation by Erosion and Erosion Effects" funding by Ministry of Agriculture.

  1. Quaternion-Based Signal Analysis for Motor Imagery Classification from Electroencephalographic Signals

    PubMed Central

    Batres-Mendoza, Patricia; Montoro-Sanjose, Carlos R.; Guerra-Hernandez, Erick I.; Almanza-Ojeda, Dora L.; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene J.; Ibarra-Manzano, Mario A.

    2016-01-01

    Quaternions can be used as an alternative to model the fundamental patterns of electroencephalographic (EEG) signals in the time domain. Thus, this article presents a new quaternion-based technique known as quaternion-based signal analysis (QSA) to represent EEG signals obtained using a brain-computer interface (BCI) device to detect and interpret cognitive activity. This quaternion-based signal analysis technique can extract features to represent brain activity related to motor imagery accurately in various mental states. Experimental tests in which users where shown visual graphical cues related to left and right movements were used to collect BCI-recorded signals. These signals were then classified using decision trees (DT), support vector machine (SVM) and k-nearest neighbor (KNN) techniques. The quantitative analysis of the classifiers demonstrates that this technique can be used as an alternative in the EEG-signal modeling phase to identify mental states. PMID:26959029

  2. Fractal-based EEG data analysis of body parts movement imagery tasks.

    PubMed

    Phothisonothai, Montri; Nakagawa, Masahiro

    2007-08-01

    The objective of this study is to analyze the spontaneous electroencephalographic (EEG) data corresponding to body parts movement imagery tasks in terms of fractal properties. We proposed the six algorithms of fractal dimension (FD) estimators; box-counting algorithm, Higuchi algorithm, variance fractal algorithm, detrended fluctuation analysis, power spectral density analysis, and critical exponent analysis. The different parts of human body movement imagination such as feet, tongue, and index finger are proposed for use as the tasks in this experiment. The EEG data were recorded from three healthy subjects (2 males and 1 female). The experimental results are useful in the measurement of FD changes in EEG data and present different characteristics in terms of variability. The probability density function (PDF) is also applied to show that the FD distribution is along each electrode. This study proposes that the performances of each method can extract information from the EEG data of imagined movement. PMID:17637165

  3. Quaternion-Based Signal Analysis for Motor Imagery Classification from Electroencephalographic Signals.

    PubMed

    Batres-Mendoza, Patricia; Montoro-Sanjose, Carlos R; Guerra-Hernandez, Erick I; Almanza-Ojeda, Dora L; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene J; Ibarra-Manzano, Mario A

    2016-01-01

    Quaternions can be used as an alternative to model the fundamental patterns of electroencephalographic (EEG) signals in the time domain. Thus, this article presents a new quaternion-based technique known as quaternion-based signal analysis (QSA) to represent EEG signals obtained using a brain-computer interface (BCI) device to detect and interpret cognitive activity. This quaternion-based signal analysis technique can extract features to represent brain activity related to motor imagery accurately in various mental states. Experimental tests in which users where shown visual graphical cues related to left and right movements were used to collect BCI-recorded signals. These signals were then classified using decision trees (DT), support vector machine (SVM) and k-nearest neighbor (KNN) techniques. The quantitative analysis of the classifiers demonstrates that this technique can be used as an alternative in the EEG-signal modeling phase to identify mental states. PMID:26959029

  4. Quaternion-Based Signal Analysis for Motor Imagery Classification from Electroencephalographic Signals.

    PubMed

    Batres-Mendoza, Patricia; Montoro-Sanjose, Carlos R; Guerra-Hernandez, Erick I; Almanza-Ojeda, Dora L; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene J; Ibarra-Manzano, Mario A

    2016-01-01

    Quaternions can be used as an alternative to model the fundamental patterns of electroencephalographic (EEG) signals in the time domain. Thus, this article presents a new quaternion-based technique known as quaternion-based signal analysis (QSA) to represent EEG signals obtained using a brain-computer interface (BCI) device to detect and interpret cognitive activity. This quaternion-based signal analysis technique can extract features to represent brain activity related to motor imagery accurately in various mental states. Experimental tests in which users where shown visual graphical cues related to left and right movements were used to collect BCI-recorded signals. These signals were then classified using decision trees (DT), support vector machine (SVM) and k-nearest neighbor (KNN) techniques. The quantitative analysis of the classifiers demonstrates that this technique can be used as an alternative in the EEG-signal modeling phase to identify mental states.

  5. Imagery Production Specialist (AFSC 23350).

    ERIC Educational Resources Information Center

    Air Univ., Gunter AFS, Ala. Extension Course Inst.

    This course of study is designed to lead the student to full qualification as an Air Force imagery production specialist. The complete course consists of six volumes: general subjects in imagery production (39 hours), photographic fundamentals (57 hours), continuous imagery production (54 hours), chemical analysis and process control (volumes A…

  6. Design and Analysis of a Single-Camera Omnistereo Sensor for Quadrotor Micro Aerial Vehicles (MAVs).

    PubMed

    Jaramillo, Carlos; Valenti, Roberto G; Guo, Ling; Xiao, Jizhong

    2016-02-06

    We describe the design and 3D sensing performance of an omnidirectional stereo (omnistereo) vision system applied to Micro Aerial Vehicles (MAVs). The proposed omnistereo sensor employs a monocular camera that is co-axially aligned with a pair of hyperboloidal mirrors (a vertically-folded catadioptric configuration). We show that this arrangement provides a compact solution for omnidirectional 3D perception while mounted on top of propeller-based MAVs (not capable of large payloads). The theoretical single viewpoint (SVP) constraint helps us derive analytical solutions for the sensor's projective geometry and generate SVP-compliant panoramic images to compute 3D information from stereo correspondences (in a truly synchronous fashion). We perform an extensive analysis on various system characteristics such as its size, catadioptric spatial resolution, field-of-view. In addition, we pose a probabilistic model for the uncertainty estimation of 3D information from triangulation of back-projected rays. We validate the projection error of the design using both synthetic and real-life images against ground-truth data. Qualitatively, we show 3D point clouds (dense and sparse) resulting out of a single image captured from a real-life experiment. We expect the reproducibility of our sensor as its model parameters can be optimized to satisfy other catadioptric-based omnistereo vision under different circumstances.

  7. Phytochemical analysis with the antioxidant and aldose reductase inhibitory capacities of Tephrosia humilis aerial parts' extracts.

    PubMed

    Plioukas, Michael; Gabrieli, Chrysi; Lazari, Diamanto; Kokkalou, Eugene

    2016-06-01

    The aerial parts of Tephrosia humilis were tested about their antioxidant potential, their ability to inhibit the aldose/aldehyde reductase enzymes and their phenolic content. The plant material was exhaustively extracted with petroleum ether, dichloromethane and methanol, consecutively. The concentrated methanol extract was re-extracted, successively, with diethyl ether, ethyl acetate and n-butanol. All extracts showed significant antioxidant capacity, but the most effective was the ethyl acetate extract. As about the aldose reductase inhibition, all fractions, except the aqueous, were strong inhibitors of the enzyme, with the n-butanolic and ethyl acetate fractions to inhibit the enzyme above 75%. These findings provide support to the ethnopharmacological usage of the plant as antioxidant and validate its potential to act against the long-term diabetic complications. The phytochemical analysis showed the presence of 1,4-dihydroxy-3,4-(epoxyethano)-5-cyclohexene(1), cleroindicin E(2), lupeol(3), methyl p-coumarate(4), methyl 4-hydroxybenzoate(5), prunin(6), 5,7,2',5'-tetrahydroxyflavanone 7-rutinoside(7), protocatechuic acid(8), luteolin 7-glucoside(9), apigenin(10), naringin(11), rhoifolin(12) and luteolin 7-glucuronate(13).

  8. Phytochemical analysis with the antioxidant and aldose reductase inhibitory capacities of Tephrosia humilis aerial parts' extracts.

    PubMed

    Plioukas, Michael; Gabrieli, Chrysi; Lazari, Diamanto; Kokkalou, Eugene

    2016-06-01

    The aerial parts of Tephrosia humilis were tested about their antioxidant potential, their ability to inhibit the aldose/aldehyde reductase enzymes and their phenolic content. The plant material was exhaustively extracted with petroleum ether, dichloromethane and methanol, consecutively. The concentrated methanol extract was re-extracted, successively, with diethyl ether, ethyl acetate and n-butanol. All extracts showed significant antioxidant capacity, but the most effective was the ethyl acetate extract. As about the aldose reductase inhibition, all fractions, except the aqueous, were strong inhibitors of the enzyme, with the n-butanolic and ethyl acetate fractions to inhibit the enzyme above 75%. These findings provide support to the ethnopharmacological usage of the plant as antioxidant and validate its potential to act against the long-term diabetic complications. The phytochemical analysis showed the presence of 1,4-dihydroxy-3,4-(epoxyethano)-5-cyclohexene(1), cleroindicin E(2), lupeol(3), methyl p-coumarate(4), methyl 4-hydroxybenzoate(5), prunin(6), 5,7,2',5'-tetrahydroxyflavanone 7-rutinoside(7), protocatechuic acid(8), luteolin 7-glucoside(9), apigenin(10), naringin(11), rhoifolin(12) and luteolin 7-glucuronate(13). PMID:26209262

  9. Multi-temporal water extent analysis of a hypersaline playa lake using Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Kilic, Ecenur; Kamil Yilmaz, Koray; Lutfi Suzen, Mehmet

    2016-04-01

    Distinguishing inland water bodies from satellite imagery has always been one of the main practices of remote sensing. In some cases this differentiation can directly be obtained by visual interpretation. However, in case of hyper-saline playa lakes, presence of high albedo salt crust in the lake bed hampers visual interpretation and requires further attention. Lake Tuz is a hypersaline playa lake which is ranked as the second largest lake in Turkey. Spatio-temporal changes in lake water extent are important both economically and hydrologically including salt production, lake water balance, drought and over-exploitation issues. This study investigates the spatiotemporal changes in Lake Tuz water extent during the last decade using single-band thresholding and multi-band indices extracted from the multi-temporal Landsat 5 TM and Landsat 7 ETM+ images. The applicability of different satellite-derived indices including Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Automated Water Extraction Index (AWEI) and Tasseled Cap Wetness (TCw) were investigated for the extraction of lake water extent from Landsat imagery. Our analysis indicated that, overall, NDWI is superior to other tested indices in separating wet/dry pixels over the lake bottom covered with salt crust. Using a NDWI thresholding procedure, the annual and seasonal variation in the Lake Tuz water extent were determined and further linked to hydro-meteorological variables such as precipitation.

  10. Techniques for automatic large scale change analysis of temporal multispectral imagery

    NASA Astrophysics Data System (ADS)

    Mercovich, Ryan A.

    Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring

  11. Geolocation with error analysis using imagery from an experimental spotlight SAR

    NASA Astrophysics Data System (ADS)

    Wonnacott, William Mark

    This dissertation covers the development of a geometry-based sensor model for a specific monostatic spotlight synthetic aperture radar (SAR) system---referred to as the ExSAR (for experimental SAR). This sensor model facilitates single- and multiple-image geopositioning with error analysis. It allows for the use of known ground control points in refining the collection geometry parameters (a process called image resection) and for the subsequent geopositioning of other points using the resected image. Theoretically, the model also allows for the potential recovery of bias-like, persistent errors common across multiple images. The model also includes multi-image correspondence equations to aid in the cross-image identification of conjugate points. The sensor model development begins with a generic, theoretical approach to the modeling of spotlight SAR. A closed-form solution to the range and range-rate condition equations and the corresponding error propagation equation are presented. (The SAR condition equations have traditionally been solved iteratively.) The application of the closed-form solution in the image-to-ground and ground-to-image transformations is documented. The theoretical work also includes a preliminary error sensitivity analysis and a treatment of the spotlight SAR resection process. The ExSAR-specific model is established and assessed with an extensive set of images collected using the experimental radar over arrays of ground control points. Using this set, the imagery metadata elements are assessed, and the optimal element set for geopositioning is determined. The ExSAR imagery is shown to be transformed to the ground plane in only one dimension. The eventual ExSAR sensor model is used with known elevations and single-image geopositioning to show a horizontal accuracy of 8.23 m (rms). With resection using five ground-surveyed control points per image, the horizontal accuracy of reserved check points is 0.45 m (rms). Resections using the same

  12. Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

    NASA Astrophysics Data System (ADS)

    Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

    2016-06-01

    With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high

  13. An analysis task comparison of uncorrected vs. geo-registered airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Sun, Yihang; Kerekes, John

    2015-05-01

    Geo-registration is the task of assigning geospatial coordinates to the pixels of an image and placing them in a geographic coordinate system. However, the process of geo-registration can impair the quality of the image. This paper studies this topic by applying a comparison methodology to uncorrected and geo-registered airborne hyperspectral images obtained from the RIT SHARE 2012 data set. The uncorrected image was analyzed directly as collected by the sensor without being treated, while the geo-registered image was corrected using the nearest neighbor resampling approach. A comparison of performance was done for the analysis tasks of spectral unmixing and subpixel target detection, which can represent a measure of utility. The comparison demonstrates that the geo-registration process can affect the utility of hyperspectral imagery to a limited extent.

  14. Unmanned aerial vehicles for rangeland mapping and monitoring: a comparison of two systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aerial photography from unmanned aerial vehicles (UAVs) bridges the gap between ground-based observations and remotely sensed imagery from aerial and satellite platforms. UAVs can be deployed quickly and repeatedly, are less costly and safer than piloted aircraft, and can obtain very high-resolution...

  15. 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.

  16. "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…

  17. Using Airborne and Satellite Imagery to Distinguish and Map Black Mangrove

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper reports the results of studies evaluating color-infrared (CIR) aerial photography, CIR aerial true digital imagery, and high resolution QuickBird multispectral satellite imagery for distinguishing and mapping black mangrove [Avicennia germinans (L.) L.] populations along the lower Texas g...

  18. Use of Kendall's coefficient of concordance to assess agreement among observers of very high resolution imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ground-based vegetation monitoring methods are expensive, time-consuming, and limited in sample-size. Aerial imagery is appealing to managers because of the reduced time and expense and the increase in sample size. One challenge of aerial imagery is detecting differences among observers of the sam...

  19. Land use analysis of US urban areas using high-resolution imagery from Skylab

    NASA Technical Reports Server (NTRS)

    Gallagher, D. B. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. The S-190B imagery from Skylab 3 permitted the detection of higher levels of land use detail than any satellite imagery previously evaluated using manual interpretation techniques. Resolution approaches that of 1:100,000 scale infrared aircraft photography, especially regarding urban areas. Nonurban areas are less distinct.

  20. Sediment Sampling in Estuarine Mudflats with an Aerial-Ground Robotic Team.

    PubMed

    Deusdado, Pedro; Guedes, Magno; Silva, André; Marques, Francisco; Pinto, Eduardo; Rodrigues, Paulo; Lourenço, André; Mendonça, Ricardo; Santana, Pedro; Corisco, José; Almeida, Susana Marta; Portugal, Luís; Caldeira, Raquel; Barata, José; Flores, Luis

    2016-01-01

    This paper presents a robotic team suited for bottom sediment sampling and retrieval in mudflats, targeting environmental monitoring tasks. The robotic team encompasses a four-wheel-steering ground vehicle, equipped with a drilling tool designed to be able to retain wet soil, and a multi-rotor aerial vehicle for dynamic aerial imagery acquisition. On-demand aerial imagery, properly fused on an aerial mosaic, is used by remote human operators for specifying the robotic mission and supervising its execution. This is crucial for the success of an environmental monitoring study, as often it depends on human expertise to ensure the statistical significance and accuracy of the sampling procedures. Although the literature is rich on environmental monitoring sampling procedures, in mudflats, there is a gap as regards including robotic elements. This paper closes this gap by also proposing a preliminary experimental protocol tailored to exploit the capabilities offered by the robotic system. Field trials in the south bank of the river Tagus' estuary show the ability of the robotic system to successfully extract and transport bottom sediment samples for offline analysis. The results also show the efficiency of the extraction and the benefits when compared to (conventional) human-based sampling. PMID:27618060

  1. Sediment Sampling in Estuarine Mudflats with an Aerial-Ground Robotic Team

    PubMed Central

    Deusdado, Pedro; Guedes, Magno; Silva, André; Marques, Francisco; Pinto, Eduardo; Rodrigues, Paulo; Lourenço, André; Mendonça, Ricardo; Santana, Pedro; Corisco, José; Almeida, Susana Marta; Portugal, Luís; Caldeira, Raquel; Barata, José; Flores, Luis

    2016-01-01

    This paper presents a robotic team suited for bottom sediment sampling and retrieval in mudflats, targeting environmental monitoring tasks. The robotic team encompasses a four-wheel-steering ground vehicle, equipped with a drilling tool designed to be able to retain wet soil, and a multi-rotor aerial vehicle for dynamic aerial imagery acquisition. On-demand aerial imagery, properly fused on an aerial mosaic, is used by remote human operators for specifying the robotic mission and supervising its execution. This is crucial for the success of an environmental monitoring study, as often it depends on human expertise to ensure the statistical significance and accuracy of the sampling procedures. Although the literature is rich on environmental monitoring sampling procedures, in mudflats, there is a gap as regards including robotic elements. This paper closes this gap by also proposing a preliminary experimental protocol tailored to exploit the capabilities offered by the robotic system. Field trials in the south bank of the river Tagus’ estuary show the ability of the robotic system to successfully extract and transport bottom sediment samples for offline analysis. The results also show the efficiency of the extraction and the benefits when compared to (conventional) human-based sampling. PMID:27618060

  2. Sediment Sampling in Estuarine Mudflats with an Aerial-Ground Robotic Team.

    PubMed

    Deusdado, Pedro; Guedes, Magno; Silva, André; Marques, Francisco; Pinto, Eduardo; Rodrigues, Paulo; Lourenço, André; Mendonça, Ricardo; Santana, Pedro; Corisco, José; Almeida, Susana Marta; Portugal, Luís; Caldeira, Raquel; Barata, José; Flores, Luis

    2016-09-09

    This paper presents a robotic team suited for bottom sediment sampling and retrieval in mudflats, targeting environmental monitoring tasks. The robotic team encompasses a four-wheel-steering ground vehicle, equipped with a drilling tool designed to be able to retain wet soil, and a multi-rotor aerial vehicle for dynamic aerial imagery acquisition. On-demand aerial imagery, properly fused on an aerial mosaic, is used by remote human operators for specifying the robotic mission and supervising its execution. This is crucial for the success of an environmental monitoring study, as often it depends on human expertise to ensure the statistical significance and accuracy of the sampling procedures. Although the literature is rich on environmental monitoring sampling procedures, in mudflats, there is a gap as regards including robotic elements. This paper closes this gap by also proposing a preliminary experimental protocol tailored to exploit the capabilities offered by the robotic system. Field trials in the south bank of the river Tagus' estuary show the ability of the robotic system to successfully extract and transport bottom sediment samples for offline analysis. The results also show the efficiency of the extraction and the benefits when compared to (conventional) human-based sampling.

  3. Semi-Automated Classification of Gray Scale Aerial Photographs using Geographic Object Based Image Analysis (GEOBIA) Technique

    NASA Astrophysics Data System (ADS)

    Harb Rabia, Ahmed; Terribile, Fabio

    2013-04-01

    Aerial photography is an important source of high resolution remotely sensed data. Before 1970, aerial photographs were the only remote sensing data source for land use and land cover classification. Using these old aerial photographs improve the final output of land use and land cover change detection. However, classic techniques of aerial photographs classification like manual interpretation or screen digitization require great experience, long processing time and vast effort. A new technique needs to be developed in order to reduce processing time and effort and to give better results. Geographic object based image analysis (GEOBIA) is a newly developed area of Geographic Information Science and remote sensing in which automatic segmentation of images into objects of similar spectral, temporal and spatial characteristics is undertaken. Unlike pixel-based technique, GEOBIA deals with the object properties such as texture, square fit, roundness and many other properties that can improve classification results. GEOBIA technique can be divided into two main steps; segmentation and classification. Segmentation process is grouping adjacent pixels into objects of similar spectral and spatial characteristics. Classification process is assigning classes to the generated objects based on the characteristics of the individual objects. This study aimed to use GEOBIA technique to develop a novel approach for land use and land cover classification of aerial photographs that saves time and effort and gives improved results. Aerial photographs from 1954 of Valle Telesina in Italy were used in this study. Images were rectified and georeferenced in Arcmap using topographic maps. Images were then processed in eCognition software to generate land use and land cover map of 1954. A decision tree rule set was developed in eCognition to classify images and finally nine classes of general land use and land cover in the study area were recognized (forest, trees stripes, agricultural

  4. 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.

  5. Small target detection based on three-dimensional principal component analysis in hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Xing; Wen, Gongjian

    2014-10-01

    Research on target detection in hyperspectral imagery (HSI) has drawn much attention recently in many areas. Due to the limitation of the HSI sensor's spatial resolution, the target of interest normally occupies only a few pixels, sometimes are even present as subpixels. This may increase the difficulties in target detection. Moreover, in some cases, such as in the rescue and surveillance tasks, small targets are the most significant information. Therefore, it is very difficult but important to effectively detect the interested small target. Using a three-dimensional tensor to model an HSI data cube can preserve as many as possible the original spatial-spectral constraint structures, which is conducive to utilize the whole information for small target detection. This paper proposes a novel and effective algorithm for small target detection in HSI based on three-dimensional principal component analysis (3D-PCA). According to the 3D-PCA, the significant components usually contain most information of imagery, in contrast, the details of small targets exist in the insignificant components. So, after 3D-PCA implemented on the HSI, the significant components which indicate the background of HSI are removed and the insignificant components are used to detect small targets. The algorithm is outstanding thanks to the tensor-based method which is applied to process the HSI directly, making full use of spatial and spectral information, by employing multilinear algebra. Experiments with a real HSI show that the detection probability of interested small targets improved greatly compared to the classical RX detector.

  6. Using IKONOS and Aerial Videography to Validate Landsat Land Cover Maps of Central African Tropical Rain Forests

    NASA Astrophysics Data System (ADS)

    Lin, T.; Laporte, N. T.

    2003-12-01

    Compared to the traditional validation methods, aerial videography is a relatively inexpensive and time-efficient approach to collect "field" data for validating satellite-derived land cover map over large areas. In particular, this approach is valuable in remote and inaccessible locations. In the Sangha Tri-National Park region of Central Africa, where road access is limited to industrial logging sites, we are using IKONOS imagery and aerial videography to assess the accuracy of Landsat-derived land cover maps. As part of a NASA Land Cover Land Use Change project (INFORMS) and in collaboration with the Wildlife Conservation Society in the Republic of Congo, over 1500km of aerial video transects were collected in the Spring of 2001. The use of MediaMapper software combined with a VMS 200 video mapping system enabled the collection of aerial transects to be registered with geographic locations from a Geographic Positioning System. Video frame were extracted, visually interpreted, and compared to land cover types mapped by Landsat. We addressed the limitations of accuracy assessment using aerial-base data and its potential for improving vegetation mapping in tropical rain forests. The results of the videography and IKONOS image analysis demonstrate the utility of very high resolution imagery for map validation and forest resource assessment.

  7. High-resolution spatial patterns of Soil Organic Carbon content derived from low-altitude aerial multi-band imagery on the Broadbalk Wheat Experiment at Rothamsted,UK

    NASA Astrophysics Data System (ADS)

    Aldana Jague, Emilien; Goulding, Keith; Heckrath, Goswin; Macdonald, Andy; Poulton, Paul; Stevens, Antoine; Van Wesemael, Bas; Van Oost, Kristof

    2014-05-01

    Soil organic C (SOC) contents in arable landscapes change as a function of management, climate and topography (Johnston et al, 2009). Traditional methods to measure soil C stocks are labour intensive, time consuming and expensive. Consequently, there is a need for developing low-cost methods for monitoring SOC contents in agricultural soils. Remote sensing methods based on multi-spectral images may help map SOC variation in surface soils. Recently, the costs of both Unmanned Aerial Vehicles (UAVs) and multi-spectral cameras have dropped dramatically, opening up the possibility for more widespread use of these tools for SOC mapping. Long-term field experiments with distinct SOC contents in adjacent plots, provide a very useful resource for systematically testing remote sensing approaches for measuring SOC. This study focusses on the Broadbalk Wheat Experiment at Rothamsted (UK). The Broadbalk experiment started in 1843. It is widely acknowledged to be the oldest continuing agronomic field experiment in the world. The initial aim of the experiment was to test the effects of different organic manures and inorganic fertilizers on the yield of winter wheat. The experiment initially contained 18 strips, each about 320m long and 6m wide, separated by paths of 1.5-2.5m wide. The strips were subsequently divided into ten sections (>180 plots) to test the effects of other factors (crop rotation, herbicides, pesticides etc.). The different amounts and combinations of mineral fertilisers (N,P,K,Na & Mg) and Farmyard Manure (FYM) applied to these plots for over 160 years has resulted in very different SOC contents in adjacent plots, ranging between 0.8% and 3.5%. In addition to large inter-plot variability in SOC there is evidence of within-plot trends related to the use of discard areas between plots and movement of soil as a result of ploughing. The objectives of this study are (i) to test whether low-altitude multi-band imagery can be used to accurately predict spatial

  8. Satellite imagery and discourses of transparency

    NASA Astrophysics Data System (ADS)

    Harris, Chad Vincent

    In the last decade there has been a dramatic increase in satellite imagery available in the commercial marketplace and to the public in general. Satellite imagery systems and imagery archives, a knowledge domain formally monopolized by nation states, have become available to the public, both from declassified intelligence data and from fully integrated commercial vendors who create and market imagery data. Some of these firms have recently launched their own satellite imagery systems and created rather large imagery "architectures" that threaten to rival military reconnaissance systems. The increasing resolution of the imagery and the growing expertise of software and imagery interpretation developers has engendered a public discourse about the potentials for increased transparency in national and global affairs. However, transparency is an attribute of satellite remote sensing and imagery production that is taken for granted in the debate surrounding the growing public availability of high-resolution satellite imagery. This paper examines remote sensing and military photo reconnaissance imagery technology and the production of satellite imagery in the interests of contemplating the complex connections between imagery satellites, historically situated discourses about democratic and global transparency, and the formation and maintenance of nation state systems. Broader historical connections will also be explored between satellite imagery and the history of the use of cartographic and geospatial technologies in the formation and administrative control of nation states and in the discursive formulation of national identity. Attention will be on the technology itself as a powerful social actor through its connection to both national sovereignty and transcendent notions of scientific objectivity. The issues of the paper will be explored through a close look at aerial photography and satellite imagery both as communicative tools of power and as culturally relevant

  9. Multiresolution analysis over graphs for a motor imagery based online BCI game.

    PubMed

    Asensio-Cubero, Javier; Gan, John Q; Palaniappan, Ramaswamy

    2016-01-01

    Multiresolution analysis (MRA) over graph representation of EEG data has proved to be a promising method for offline brain-computer interfacing (BCI) data analysis. For the first time we aim to prove the feasibility of the graph lifting transform in an online BCI system. Instead of developing a pointer device or a wheel-chair controller as test bed for human-machine interaction, we have designed and developed an engaging game which can be controlled by means of imaginary limb movements. Some modifications to the existing MRA analysis over graphs for BCI have also been proposed, such as the use of common spatial patterns for feature extraction at the different levels of decomposition, and sequential floating forward search as a best basis selection technique. In the online game experiment we obtained for three classes an average classification rate of 63.0% for fourteen naive subjects. The application of a best basis selection method helps significantly decrease the computing resources needed. The present study allows us to further understand and assess the benefits of the use of tailored wavelet analysis for processing motor imagery data and contributes to the further development of BCI for gaming purposes.

  10. Change analysis at Stuttgart airport using TerraSAR-X imagery

    NASA Astrophysics Data System (ADS)

    Boldt, Markus; Thiele, Antje; Cadario, Erich; Schulz, Karsten; Hinz, Stefan

    2014-10-01

    Change detection based on remote sensing imagery is a topic highly on demand with various fields of application. Probably, disaster management is the best known, where it is crucial to get fast and reliable results to enable a suitable supply of the affected region. Another important issue, for example in city or land-use planning, is the regular monitoring of specific regions of interest. For both scenarios, it would be significant to have information about the type or category of the detected changes. Since High-Resolution (HR) Synthetic Aperture Radar (SAR) is in opposite to optical sensors an active technique, it is well-capable for all change detection topics where a regular monitoring is intended. SAR sensors illuminate the investigated scene by their own microwave radiation and most applied microwave wavelengths make SAR nearly independent from atmospheric effects like dust, fog, and clouds. Moreover, the time of day makes no difference using SAR sensors. Acquired in HR SpotLight mode 300 (HS300) by the German satellite TerraSAR-X (TSX), images have a resolution of better than one meter, which allows to separate small objects placed close together. In this paper, a concept of change analysis focusing on small-sized areas is presented. Those change areas can be caused by man-made objects (e.g. vehicles, small construction sites) or natural events like phenologically based changes of the vegetation. Since the presented change analysis concept deals with the analysis of time series imagery, other seasonal also man-made caused changes (e.g. agriculture) can be detected. Furthermore, the concept comprises the categorization of the detected changes, which separates it from many of the existing change detection approaches. It includes five central components given by the change detection itself, the pre-categorization of change pixels, the feature extraction for change blobs, the analysis of their spatial context, and the final decision making forming a

  11. Design and analysis of multifunctional structures for embedded electronics in unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Kothari, Rushabh M.

    Multifunctional structures are a new trend in the aerospace industry for the next generation structural design. Many future structures are expected to be something in addition to a load bearing structure. The design and analysis of multifunctional structures combining structural, electrical and thermal functionalities are presented here. The sandwich beam is considered as a starting point for the load bearing structure and then it is modified with a cavity to embed avionics and thermal controls. The embedded avionics inside the load bearing structure would allow weight reduction of the aerospace vehicle due to elimination of separate electronics housing, interconnects, cables etc. The cavity reduces strength of the structure so various reinforcements methods are evaluated. The result of various reinforcements and their effectiveness are presented. The current generation of electronics produce massive amount of heat. In the case of embedded electronics, the excessive heat presents a major challenge to the structural and heat transfer engineers. The embedded nature of electronics prevents the use of the classical heat dissipative methods such as fans and high velocity air flows, etc. The integrated thermal control of the electronics has been designed using passive heat transfer device and highly optimized particulate composite thermal interface material (TIM). The TIMs are used to fill the air gaps and reduce contact resistance between two surfaces, such as electronics and heat dissipators. The efficiency of TIM directly affects the overall heat transfer ability of the integrated thermal control system. The effect of the particles at micron and nano scales are studied for the particulate composite TIM. The thermal boundary resistance study for the particulate composite TIM with nano silica particles is presented in this thesis. The FEA analysis is used to model thermal boundary resistance and compared with the theoretical micromechanics model. The heat pipes are

  12. Mimicking human expert interpretation of remotely sensed raster imagery by using a novel segmentation analysis within ArcGIS

    NASA Astrophysics Data System (ADS)

    Le Bas, Tim; Scarth, Anthony; Bunting, Peter

    2015-04-01

    Traditional computer based methods for the interpretation of remotely sensed imagery use each pixel individually or the average of a small window of pixels to calculate a class or thematic value, which provides an interpretation. However when a human expert interprets imagery, the human eye is excellent at finding coherent and homogenous areas and edge features. It may therefore be advantageous for computer analysis to mimic human interpretation. A new toolbox for ArcGIS 10.x will be presented that segments the data layers into a set of polygons. Each polygon is defined by a K-means clustering and region growing algorithm, thus finding areas, their edges and any lineations in the imagery. Attached to each polygon are the characteristics of the imagery such as mean and standard deviation of the pixel values, within the polygon. The segmentation of imagery into a jigsaw of polygons also has the advantage that the human interpreter does not need to spend hours digitising the boundaries. The segmentation process has been taken from the RSGIS library of analysis and classification routines (Bunting et al., 2014). These routines are freeware and have been modified to be available in the ArcToolbox under the Windows (v7) operating system. Input to the segmentation process is a multi-layered raster image, for example; a Landsat image, or a set of raster datasets made up from derivatives of topography. The size and number of polygons are set by the user and are dependent on the imagery used. Examples will be presented of data from the marine environment utilising bathymetric depth, slope, rugosity and backscatter from a multibeam system. Meaningful classification of the polygons using their numerical characteristics is the next goal. Object based image analysis (OBIA) should help this workflow. Fully calibrated imagery systems will allow numerical classification to be translated into more readily understandable terms. Peter Bunting, Daniel Clewley, Richard M. Lucas and Sam

  13. Applications of Landsat imagery to a coastal inlet stability study

    NASA Technical Reports Server (NTRS)

    Wang, Y.-H.

    1981-01-01

    Polcyn and Lyzenga (1975) and Middleton and Barber (1976) have demonstrated that it is possible to correlate the radiance values of a multispectral imagery, such as Landsat imagery, with the depth related information. The present study is one more example of such an effort. Two sets of Landsat magnetic tape were obtained and displayed on the screen of an Image-100 computer. Spectral analysis was performed to produce various signatures, their extent, and location. Subsequent ground truth observations and measurements were gathered by means of hydrographic surveys and low altitude aerial photographs for interpretation and calibration of the Landsat data. Finally, a coastal engineering assessment based on the Landsat data was made. Recommendations regarding the navigational canal alignment and dredging practice are presented in the light of inlet stability.

  14. Imagery Integration Team

    NASA Technical Reports Server (NTRS)

    Calhoun, Tracy; Melendrez, Dave

    2014-01-01

    The Human Exploration Science Office (KX) provides leadership for NASA's Imagery Integration (Integration 2) Team, an affiliation of experts in the use of engineering-class imagery intended to monitor the performance of launch vehicles and crewed spacecraft in flight. Typical engineering imagery assessments include studying and characterizing the liftoff and ascent debris environments; launch vehicle and propulsion element performance; in-flight activities; and entry, landing, and recovery operations. Integration 2 support has been provided not only for U.S. Government spaceflight (e.g., Space Shuttle, Ares I-X) but also for commercial launch providers, such as Space Exploration Technologies Corporation (SpaceX) and Orbital Sciences Corporation, servicing the International Space Station. The NASA Integration 2 Team is composed of imagery integration specialists from JSC, the Marshall Space Flight Center (MSFC), and the Kennedy Space Center (KSC), who have access to a vast pool of experience and capabilities related to program integration, deployment and management of imagery assets, imagery data management, and photogrammetric analysis. The Integration 2 team is currently providing integration services to commercial demonstration flights, Exploration Flight Test-1 (EFT-1), and the Space Launch System (SLS)-based Exploration Missions (EM)-1 and EM-2. EM-2 will be the first attempt to fly a piloted mission with the Orion spacecraft. The Integration 2 Team provides the customer (both commercial and Government) with access to a wide array of imagery options - ground-based, airborne, seaborne, or vehicle-based - that are available through the Government and commercial vendors. The team guides the customer in assembling the appropriate complement of imagery acquisition assets at the customer's facilities, minimizing costs associated with market research and the risk of purchasing inadequate assets. The NASA Integration 2 capability simplifies the process of securing one

  15. Analysis of the Shoreline Position Extracted from Landsat TM and ETM+ Imagery

    NASA Astrophysics Data System (ADS)

    Sanchez-Garcia, E.; Pardo-Pascual, J. E.; Balaguer-Beser, A.; Almonacid-Caballer, J.

    2015-04-01

    A statistical analysis of the results obtained by the tool SELI (Shoreline Extraction from Landsat Imagery) is made in order to characterise the medium and long term period changes occurring on beaches. The analysis is based on the hypothesis that intraannual shifts of coastline positions hover around an average position, which would be significant when trying to set these medium and long term trends. Fluctuations around this average are understood as the effect of short-term changes -variations related to sea level, wave run-up, and the immediate morphological beach profile settings of the incident waves- whilst the alterations of the average position will obey changes relating to the global sedimentary harmony of the analysed beach segment. The goal of this study is to assess the validity of extracted Landsat shorelines knowing whether the intrinsic error could alter the position of the computed mean annual shoreline or if it is balanced out between the successive averaged images. Two periods are stablished for the temporal analysis in the area according to the availability of other data taken from high precision sources. Statistical tests performed to compare samples (Landsat versus high accuracy) indicate that the two sources of data provide similar information regarding annual means; coastal behaviour and dynamics, thereby verifying Landsat shorelines as useful data for evolutionary studies.

  16. Synthetic Aperture Radar (sar) and Optical Imagery Data Fusion: Crop Yield Analysis in Southeast Asia

    NASA Astrophysics Data System (ADS)

    Parks, S. M.

    2012-08-01

    With the expanding energy crisis and rising food prices, crop yield analysis in Southeast Asia is an increasingly important topic in this region. Rice is the most important food crop in Southeast Asia and the ability to accurately predict crop yields during a growing season is useful for decision-makers, aid providers, and commercial trade organizations. The use of optical satellite image data by itself is difficult due to the almost constant cloud in many parts of Southeast Asia. However, Synthetic Aperture Radar (SAR), or SAR data, which can image the Earth's surface through cloud cover, is suitable for many agricultural purposes, such as the detection of rice fields, and the identification of different crop species. Crop yield analysis is difficult in this region due to many factors. Rice cropping systems are often characterized by the type of rice planted, the size of rice field, the sowing dates for different fields, different types of rice cropping systems from one area to another, as well as cultural practices such as sowing and transplanting. This paper will discuss the use of SAR data fused with optical imagery to improve the ability to perform crop yield analysis on rice crops in Southeast Asia.

  17. Mapping land cover gradients through analysis of hyper-temporal NDVI imagery

    NASA Astrophysics Data System (ADS)

    Ali, Amjad; de Bie, C. A. J. M.; Skidmore, A. K.; Scarrott, R. G.; Hamad, Amina; Venus, V.; Lymberakis, Petros

    2013-08-01

    The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typically fail to express such differences as gradients. Present interpretation techniques still make insufficient use of freely available spatial-temporal Earth Observation (EO) data that allow detection of existing land cover gradients. This study explores the use of hyper-temporal NDVI imagery to detect and delineate land cover gradients analyzing the temporal behavior of NDVI values. MODIS-Terra MVC-images (250 m, 16-day) of Crete, Greece, from February 2000 to July 2009 are used. The analysis approach uses an ISODATA unsupervised classification in combination with a Hierarchical Clustering Analysis (HCA). Clustering of class-specific temporal NDVI profiles through HCA resulted in the identification of gradients in landcover vegetation growth patterns. The detected gradients were arranged in a relational diagram, and mapped. Three groups of NDVI-classes were evaluated by correlating their class-specific annual average NDVI values with the field data (tree, shrub, grass, bare soil, stone, litter fraction covers). Multiple regression analysis showed that within each NDVI group, the fraction cover data were linearly related with the NDVI data, while NDVI groups were significantly different with respect to tree cover (adj. R2 = 0.96), shrub cover (adj. R2 = 0.83), grass cover (adj. R2 = 0.71), bare soil (adj. R2 = 0.88), stone cover (adj. R2 = 0.83) and litter cover (adj. R2 = 0.69) fractions. Similarly, the mean Sorenson dissimilarity values were found high and significant at confidence interval of 95% in all pairs of three NDVI groups. The study demonstrates that hyper-temporal NDVI imagery can successfully detect and map land cover gradients. The results may improve land

  18. The use of large-scale aerial photography for interpreting Landsat digital data in an elk habitat-analysis project

    NASA Technical Reports Server (NTRS)

    Isaacson, D. L.; Alexander, C. J.; Leckenby, D. A.

    1982-01-01

    Large-scale aerial photography was used to interpret Landsat multispectral scanner data processed through an unsupervised classifier. After scale adjustment and interpretation by application of an elk-habitat photointerpretation legend, the photographs were registered with the spectral classification, and the co-occurrence of spectral picture elements with photointerpreted habitat classes was tabulated. Analysis of the resulting table of data permitted the description of spectral classes in terms meaningful and useful to elk research and management unit in the Blue Mountains of northeastern Oregon.

  19. GC-MS analysis of insecticidal essential oil of flowering aerial parts of Saussurea nivea Turcz

    PubMed Central

    2012-01-01

    Background Several species from Saussurea have been used in the traditional medicine, such as S. lappa, S. involucrate, and S. obvallata. There is no report on medicinal use of S. nivea. The aim of this research was to determine chemical composition and insecticidal activity of the essential oil of S. nivea Turcz (Asteraceae) aerial parts against maize weevils (Sitophilus zeamais Motschulsky) for the first time. Results Essential oil of S. nivea flowering aerial parts was obtained by hydrodistillation and analyzed by gas chromatography–mass spectrometry (GC-MS). A total of 43 components of the essential oil of S. nivea were identified. The principal compounds in the essential oil were (+)-limonene (15.46%), caryophyllene oxide (7.62%), linalool (7.20%), α-pinene (6.43%), β-pinene (5.66%) and spathulenol (5.02%) followed by β-eudesmoll (4.64%) and eudesma-4,11-dien-2-ol (3.76%). The essential oil of S. nivea exhibited strong contact toxicity against S. zeamais with an LD50 value of 10.56 μg/adult. The essential oil also possessed fumigant toxicity against S. zeamais with an LC50 value of 8.89 mg/L. Conclusion The study indicates that the essential oil of S. nivea flowering aerial parts has a potential for development into a natural insecticide/fumigant for control of insects in stored grains. PMID:23351592

  20. Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

    PubMed Central

    Scottá, Fernando C.; da Fonseca, Eliana L.

    2015-01-01

    This study aimed to evaluate changes in the aboveground net primary productivity (ANPP) of grasslands in the Pampa biome by using experimental plots and changes in the spectral responses of similar vegetation communities obtained by remote sensing and to compare both datasets with meteorological variations to validate the transition scales of the datasets. Two different geographic scales were considered in this study. At the local scale, an analysis of the climate and its direct influences on grassland ANPP was performed using data from a long-term experiment. At the regional scale, the influences of climate on the grassland reflectance patterns were determined using vegetation sensor imagery data. Overall, the monthly variations of vegetation canopy growth analysed using environmental changes (air temperature, total rainfall and total evapotranspiration) were similar. The results from the ANPP data and the NDVI data showed the that variations in grassland growth were similar and independent of the analysis scale, which indicated that local data and the relationships of local data with climate can be considered at the regional scale in the Pampa biome by using remote sensing. PMID:26197320

  1. A review and analysis of neural networks for classification of remotely sensed multispectral imagery

    NASA Technical Reports Server (NTRS)

    Paola, Justin D.; Schowengerdt, Robert A.

    1993-01-01

    A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

  2. Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery.

    PubMed

    Scottá, Fernando C; da Fonseca, Eliana L

    2015-07-21

    This study aimed to evaluate changes in the aboveground net primary productivity (ANPP) of grasslands in the Pampa biome by using experimental plots and changes in the spectral responses of similar vegetation communities obtained by remote sensing and to compare both datasets with meteorological variations to validate the transition scales of the datasets. Two different geographic scales were considered in this study. At the local scale, an analysis of the climate and its direct influences on grassland ANPP was performed using data from a long-term experiment. At the regional scale, the influences of climate on the grassland reflectance patterns were determined using vegetation sensor imagery data. Overall, the monthly variations of vegetation canopy growth analysed using environmental changes (air temperature, total rainfall and total evapotranspiration) were similar. The results from the ANPP data and the NDVI data showed the that variations in grassland growth were similar and independent of the analysis scale, which indicated that local data and the relationships of local data with climate can be considered at the regional scale in the Pampa biome by using remote sensing.

  3. Mineral target areas in Nevada from geological analysis of LANDSAT-1 imagery

    NASA Technical Reports Server (NTRS)

    Abdel-Gawad, M.; Tubbesing, L.

    1975-01-01

    Geological analysis of LANDSAT-1 Scene MSS 1053-17540 suggests that certain known mineral districts in east-central Nevada frequently occur near faults or at faults or lineament intersections and areas of complex deformation and flexures. Seventeen (17) areas of analogous characteristics were identified as favorable targets for mineral exploration. During reconnaissance field trips eleven areas were visited. In three areas evidence was found of mining and/or prospecting not known before the field trips. In four areas favorable structural and alteration features were observed which call for more detailed field studies. In one of the four areas limonitic iron oxide samples were found in the regolith of a brecciated dolomite ridge. This area contains quartz veins, granitic and volcanic rocks and lies near the intersection of two linear fault structures identified in the LANDSAT-1 imagery. Semiquantitative spectroscopic analysis of selected portions of the samples showed abnormal contents of arsenic, molybdenum, copper, lead, zinc, and silver. These limonitic samples found were not in situ and further field studies are required to assess their source and significance.

  4. Thermal imagery for census of ungulates

    NASA Technical Reports Server (NTRS)

    Wride, M. C.; Baker, K.

    1977-01-01

    A Daedalus thermal linescanner mounted in a light single engine aircraft was used to image the entire 270 square kilometers within the fenced perimeter of ElK Island Park, Alberta, Canada. The data were collected during winter, 1976 in morning and midday (overcast conditions) processed and analyzed to obtain a number for total ungulates. Five different ungulate species were present during the survey. Ungulates were easily observed during the analysis of linescanner imagery and the total number of ungulates was established at 2175 compared to figures of 1010 and 1231 for visual method aerial survey results of the same area that year. It was concluded that the scanner was much more accurate and precise for census of ungulates than visual techniques.

  5. Parallax visualization of UAV FMV and WAMI imagery

    NASA Astrophysics Data System (ADS)

    Mayhew, Christopher A.; Mayhew, Craig M.

    2012-06-01

    The US Military is increasingly relying on the use of unmanned aerial vehicles (UAV) for intelligence, surveillance, and reconnaissance (ISR) missions. Complex arrays of Full-Motion Video (FMV), Wide-Area Motion Imaging (WAMI) and Wide Area Airborne Surveillance (WAAS) technologies are being deployed on UAV platforms for ISR applications. Nevertheless, these systems are only as effective as the Image Analyst's (IA) ability to extract relevant information from the data. A variety of tools assist in the analysis of imagery captured with UAV sensors. However, until now, none has been developed to extract and visualize parallax three-dimensional information. Parallax Visualization (PV) is a technique that produces a near-three-dimensional visual response to standard UAV imagery. The overlapping nature of UAV imagery lends itself to parallax visualization. Parallax differences can be obtained by selecting frames that differ in time and, therefore, points of view of the area of interest. PV is accomplished using software tools to critically align a common point in two views while alternately displaying both views in a square-wave manner. Humans produce an autostereoscopic response to critically aligned parallax information presented alternately on a standard unaided display at frequencies between 3 and 6 Hz. This simple technique allows for the exploitation of spatial and temporal differences in image sequences to enhance depth, size, and spatial relationships of objects in areas of interest. PV of UAV imagery has been successfully performed in several US Military exercises over the last two years.

  6. 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.

  7. Korean coastal water depth/sediment and land cover mapping /1:25,000/ by computer analysis of Landsat imagery

    NASA Technical Reports Server (NTRS)

    Park, K. Y.; Miller, L. D.

    1980-01-01

    Computer analysis was applied to single data Landsat MSS imagery of a coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map, and featuring large dynamic sediment transport processes. Supervised image processing yielded a test classification map containing five water depth/sediment classes, two shoreline/tidal classes and five coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%; the training sets were selected by direct examination of the digitally displayed imagery. The unsupervised ISOCLAS (Senkus, 1976) clustering analysis was performed to assess the relative value of this approach to image classification in areas of sparse or nonexistent ground control. Results indicate that it is feasible to produce quantitative maps for detailed study of dynamic coastal processes given a Landsat image data base at sufficiently frequent time intervals.

  8. D Object Classification Based on Thermal and Visible Imagery in Urban Area

    NASA Astrophysics Data System (ADS)

    Hasani, H.; Samadzadegan, F.

    2015-12-01

    The spatial distribution of land cover in the urban area especially 3D objects (buildings and trees) is a fundamental dataset for urban planning, ecological research, disaster management, etc. According to recent advances in sensor technologies, several types of remotely sensed data are available from the same area. Data fusion has been widely investigated for integrating different source of data in classification of urban area. Thermal infrared imagery (TIR) contains information on emitted radiation and has unique radiometric properties. However, due to coarse spatial resolution of thermal data, its application has been restricted in urban areas. On the other hand, visible image (VIS) has high spatial resolution and information in visible spectrum. Consequently, there is a complementary relation between thermal and visible imagery in classification of urban area. This paper evaluates the potential of aerial thermal hyperspectral and visible imagery fusion in classification of urban area. In the pre-processing step, thermal imagery is resampled to the spatial resolution of visible image. Then feature level fusion is applied to construct hybrid feature space include visible bands, thermal hyperspectral bands, spatial and texture features and moreover Principle Component Analysis (PCA) transformation is applied to extract PCs. Due to high dimensionality of feature space, dimension reduction method is performed. Finally, Support Vector Machines (SVMs) classify the reduced hybrid feature space. The obtained results show using thermal imagery along with visible imagery, improved the classification accuracy up to 8% respect to visible image classification.

  9. Habitat mapping of the Brazilian Pantanal using synthetic aperture radar imagery and object based image analysis

    NASA Astrophysics Data System (ADS)

    Evans, Teresa Lynne

    for both fine and medium resolution classifications related to issues of 1) scale of habitats, for instance, capoes, cordilheiras, and lakes, in relation to spatial resolution of the imagery, and 2) issues relating to variable flooding patterns in the subregion, and 3) arbitrary class membership rules. The 50 m spatial resolution classification of the entire Pantanal wetland resulted in an overall accuracy of 80%, and defined ten land cover classes. Given the analysis of the comparison of fine and relatively medium spatial resolution classifications of the Lower Nhecolândia subregion, I conclude that significant improvements in accuracy can be achieved with the finer spatial resolution dataset, particularly in subregions with high spatial heterogeneity in land cover. The produced habitat spatial distribution maps will provide vital information for determining refuge zones for terrestrial species, connectivity of aquatic habitats during the dry season, and crucial baseline data to aid in monitoring changes in the region, as well as to help define conservation strategies for habitat in this critically important wetland.

  10. Objective indicators of pasture degradation from spectral mixture analysis of Landsat imagery

    NASA Astrophysics Data System (ADS)

    Davidson, Eric A.; Asner, Gregory P.; Stone, Thomas A.; Neill, Christopher; Figueiredo, Ricardo O.

    2008-03-01

    Degradation of cattle pastures is a management concern that influences future land use in Amazonia. However, "degradation" is poorly defined and has different meanings for ranchers, ecologists, and policy makers. Here we analyze pasture degradation using objective scalars of photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and exposed soil (S) derived from Landsat imagery. A general, probabilistic spectral mixture model decomposed satellite spectral reflectance measurements into subpixel estimates of PV, NPV, and S covers at ranches in western and eastern Amazonia. Most pasture management units at all ranches fell along a single line of decreasing PV with increasing NPV and S, which could be considered a degradation continuum. The ranch with the highest stocking densities and most intensive management had greater NPV and S than a less intensively managed ranch. The number of liming, herbiciding, and disking treatments applied to each pasture management unit was positively correlated with NPV and negatively correlated with PV. Although these objective scalars revealed signs of degradation, intensive management kept exposed soil to <40% cover and maintained economically viable cattle production over several decades. In ranches with few management inputs, the high PV cover in young pastures declined with increasing pasture age, while NPV and S increased, even where grazing intensity was low. Both highly productive pastures and vigorous regrowth of native vegetation cause high PV values. Analysis of spectral properties holds promise for identifying areas where grazing intensity has exceeded management inputs, thus increasing coverage of senescent foliage and exposed soil.

  11. Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

    USGS Publications Warehouse

    Wallace, C.S.A.; Marsh, S.E.

    2005-01-01

    Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

  12. General theory for the processing of compressed and encrypted imagery with taxonomic analysis

    NASA Astrophysics Data System (ADS)

    Schmalz, Mark S.

    1992-07-01

    The processing of compressed and encrypted imagery can exhibit advantages of computational efficiency as well as data security. Due to the data reduction inherent in compression, the computational speedup achieved via compressive processing can equal or exceed the compression ratio. Encryptive transformations which yield compressed ciphertext can similarly facilitate computational speedup, and are well known. However, due to analytical difficulties inherent in the derivation of operations which compute over the range space of commonly employed compressive transforms, reports of such processing paradigms are not evident in the open literature. In this introductory paper, we describe compressive and encryptive transformations in terms of functional mappings derived from abstract mathematics and image algebra (IA). An emerging technology, IA is a rigorous, concise notation which unifies linear and nonlinear mathematics in the image domain, and has been implemented on a variety of serial and parallel computers. Additionally, we derive a taxonomy of image transformations. Each taxonomic class is analyzed in terms of computational complexity and applicability to image and signal processing. We further present decompositions specific to each transformational class, which facilitate the design of operations over a given transform's range space. Examples and analysis are given for several image operations.

  13. An Analysis of Fuel Cell Options for an All-electric Unmanned Aerial Vehicle

    NASA Technical Reports Server (NTRS)

    Kohout, Lisa L.; Schmitz, Paul C.

    2007-01-01

    A study was conducted to assess the performance characteristics of both PEM and SOFC-based fuel cell systems for an all-electric high altitude, long endurance Unmanned Aerial Vehicle (UAV). Primary and hybrid systems were considered. Fuel options include methane, hydrogen, and jet fuel. Excel-based models were used to calculate component mass as a function of power level and mission duration. Total system mass and stored volume as a function of mission duration for an aircraft operating at 65 kft altitude were determined and compared.

  14. Integration of thermal and hyperspectral VNIR imagery for architectural and artistic heritage analysis and monitoring

    NASA Astrophysics Data System (ADS)

    Cavalli, Rosa Maria; Masini, Nicola; Pascucci, Simone; Palombo, Angelo; Pignatti, Stefano

    2010-05-01

    The application of integrated hyperspectral VNIR and thermal data for analyzing and monitoring the architectural and artistic heritage status is becoming a remarkable tool to be combined with other non-destructive techniques (e.g. GPR), and prior to destructive checking, in order to extract appropriate information and make useful decisions [1]. As the analysis of some kind of damages (e.g. water infiltrations) or alterations is not always fulfilled with visible and thermographic imagery, the proposed study aims at integrating hyperspectral reflectances and temperature and apparent thermal inertia behaviours. Hyperspectral data is able to discriminate materials on the basis of their different patterns of wavelength-specific absorption; in fact, they are successfully used for identifying minerals and rocks, as well as detecting soil properties including moisture, organic content and salinity [2]. Moreover, the potential to find out alterations or damages and monitoring them through non-destructive sensors is particularly appreciated in structural analysis for restoration works such as water infiltrations in outdoor cultural assets and moisture penetration in a wall that is a major source of paint alteration [3, 4]. The jointly use of the reflective and infrared (emitted, absorbed, reflected and transmitted) radiation for this research study is encouraged by the technical and operative characteristics of the observation systems at disposal that can provide high spectral resolution and high-frequency images with low Ne?R e Ne?T values and able to observe the variables and physical and optical parameters in quasi real-time and connected to the cultural heritage status. The following portable field instruments are used for this study: (a) HYSPEX hyperspectral scanner working in the VNIR (0.4-1.0μm) spectral region, which is an imaging spectrometer with a very high spectral and spatial resolution, (b) 2 FLIR SC7000 Thermal cams working in the MWIR (3-5 micron) and LWIR

  15. Integration of thermal and hyperspectral VNIR imagery for architectural and artistic heritage analysis and monitoring

    NASA Astrophysics Data System (ADS)

    Cavalli, Rosa Maria; Masini, Nicola; Pascucci, Simone; Palombo, Angelo; Pignatti, Stefano

    2010-05-01

    The application of integrated hyperspectral VNIR and thermal data for analyzing and monitoring the architectural and artistic heritage status is becoming a remarkable tool to be combined with other non-destructive techniques (e.g. GPR), and prior to destructive checking, in order to extract appropriate information and make useful decisions [1]. As the analysis of some kind of damages (e.g. water infiltrations) or alterations is not always fulfilled with visible and thermographic imagery, the proposed study aims at integrating hyperspectral reflectances and temperature and apparent thermal inertia behaviours. Hyperspectral data is able to discriminate materials on the basis of their different patterns of wavelength-specific absorption; in fact, they are successfully used for identifying minerals and rocks, as well as detecting soil properties including moisture, organic content and salinity [2]. Moreover, the potential to find out alterations or damages and monitoring them through non-destructive sensors is particularly appreciated in structural analysis for restoration works such as water infiltrations in outdoor cultural assets and moisture penetration in a wall that is a major source of paint alteration [3, 4]. The jointly use of the reflective and infrared (emitted, absorbed, reflected and transmitted) radiation for this research study is encouraged by the technical and operative characteristics of the observation systems at disposal that can provide high spectral resolution and high-frequency images with low Ne?R e Ne?T values and able to observe the variables and physical and optical parameters in quasi real-time and connected to the cultural heritage status. The following portable field instruments are used for this study: (a) HYSPEX hyperspectral scanner working in the VNIR (0.4-1.0μm) spectral region, which is an imaging spectrometer with a very high spectral and spatial resolution, (b) 2 FLIR SC7000 Thermal cams working in the MWIR (3-5 micron) and LWIR

  16. Analysis of Small-Scale Convective Dynamics in a Crown Fire Using Infrared Video Camera Imagery.

    NASA Astrophysics Data System (ADS)

    Clark, Terry L.; Radke, Larry; Coen, Janice; Middleton, Don

    1999-10-01

    A good physical understanding of the initiation, propagation, and spread of crown fires remains an elusive goal for fire researchers. Although some data exist that describe the fire spread rate and some qualitative aspects of wildfire behavior, none have revealed the very small timescales and spatial scales in the convective processes that may play a key role in determining both the details and the rate of fire spread. Here such a dataset is derived using data from a prescribed burn during the International Crown Fire Modelling Experiment. A gradient-based image flow analysis scheme is presented and applied to a sequence of high-frequency (0.03 s), high-resolution (0.05-0.16 m) radiant temperature images obtained by an Inframetrics ThermaCAM instrument during an intense crown fire to derive wind fields and sensible heat flux. It was found that the motions during the crown fire had energy-containing scales on the order of meters with timescales of fractions of a second. Estimates of maximum vertical heat fluxes ranged between 0.6 and 3 MW m2 over the 4.5-min burn, with early time periods showing surprisingly large fluxes of 3 MW m2. Statistically determined velocity extremes, using five standard deviations from the mean, suggest that updrafts between 10 and 30 m s1, downdrafts between 10 and 20 m s1, and horizontal motions between 5 and 15 m s1 frequently occurred throughout the fire.The image flow analyses indicated a number of physical mechanisms that contribute to the fire spread rate, such as the enhanced tilting of horizontal vortices leading to counterrotating convective towers with estimated vertical vorticities of 4 to 10 s1 rotating such that air between the towers blew in the direction of fire spread at canopy height and below. The IR imagery and flow analysis also repeatedly showed regions of thermal saturation (infrared temperature > 750°C), rising through the convection. These regions represent turbulent bursts or hairpin vortices resulting again from

  17. Unmanned aerial systems for photogrammetry and remote sensing: A review

    NASA Astrophysics Data System (ADS)

    Colomina, I.; Molina, P.

    2014-06-01

    We discuss the evolution and state-of-the-art of the use of Unmanned Aerial Systems (UAS) in the field of Photogrammetry and Remote Sensing (PaRS). UAS, Remotely-Piloted Aerial Systems, Unmanned Aerial Vehicles or simply, drones are a hot topic comprising a diverse array of aspects including technology, privacy rights, safety and regulations, and even war and peace. Modern photogrammetry and remote sensing identified the potential of UAS-sourced imagery more than thirty years ago. In the last five years, these two sister disciplines have developed technology and methods that challenge the current aeronautical regulatory framework and their own traditional acquisition and processing methods. Navety and ingenuity have combined off-the-shelf, low-cost equipment with sophisticated computer vision, robotics and geomatic engineering. The results are cm-level resolution and accuracy products that can be generated even with cameras costing a few-hundred euros. In this review article, following a brief historic background and regulatory status analysis, we review the recent unmanned aircraft, sensing, navigation, orientation and general data processing developments for UAS photogrammetry and remote sensing with emphasis on the nano-micro-mini UAS segment.

  18. Does motor imagery share neural networks with executed movement: a multivariate fMRI analysis

    PubMed Central

    Sharma, Nikhil; Baron, Jean-Claude

    2013-01-01

    Introduction: Motor imagery (MI) is the mental rehearsal of a motor first person action-representation. There is interest in using MI to access the motor network after stroke. Conventional fMRI modeling has shown that MI and executed movement (EM) activate similar cortical areas but it remains unknown whether they share cortical networks. Proving this is central to using MI to access the motor network and as a form of motor training. Here we use multivariate analysis (tensor independent component analysis-TICA) to map the array of neural networks involved during MI and EM. Methods: Fifteen right-handed healthy volunteers (mean-age 28.4 years) were recruited and screened for their ability to carry out MI (Chaotic MI Assessment). fMRI consisted of an auditory-paced (1 Hz) right hand finger-thumb opposition sequence (2,3,4,5; 2…) with two separate runs acquired (MI & rest and EM & rest: block design). No distinction was made between MI and EM until the final stage of processing. This allowed TICA to identify independent-components (IC) that are common or distinct to both tasks with no prior assumptions. Results: TICA defined 52 ICs. Non-significant ICs and those representing artifact were excluded. Components in which the subject scores were significantly different to zero (for either EM or MI) were included. Seven IC remained. There were IC's shared between EM and MI involving the contralateral BA4, PMd, parietal areas and SMA. IC's exclusive to EM involved the contralateral BA4, S1 and ipsilateral cerebellum whereas the IC related exclusively to MI involved ipsilateral BA4 and PMd. Conclusion: In addition to networks specific to each task indicating a degree of independence, we formally demonstrate here for the first time that MI and EM share cortical networks. This significantly strengthens the rationale for using MI to access the motor networks, but the results also highlight important differences. PMID:24062666

  19. Assessing the Impacts of US Landfall Hurricanes in 2012 using Aerial Remote Sensing

    NASA Astrophysics Data System (ADS)

    Bevington, John S.

    2013-04-01

    Remote sensing has become a widely-used technology for assessing and evaluating the extent and severity of impacts of natural disasters worldwide. Optical and radar data collected by air- and space-borne sensors have supported humanitarian and economic decision-making for over a decade. Advances in image spatial resolution and pre-processing speeds have meant images with centimetre spatial resolution are now available for analysis within hours following severe disaster events. This paper offers a retrospective view on recent large-scale responses to two of the major storms from the 2012 Atlantic hurricane season: Hurricane Isaac and post-tropical cyclone ("superstorm") Sandy. Although weak on the Saffir-Simpson hurricane wind scale, these slow-moving storms produced intense rainfall and coastal storm surges in the order of several metres in the Louisiana and Mississippi Gulf Coast (Isaac), and the Atlantic Seaboard (Sandy) of the United States. Data were generated for both events through interpretation of a combination of two types of aerial imagery: high spatial resolution optical imagery captured by fixed aerial sensors deployed by the National Oceanic and Atmospheric Administration (NOAA), and digital single lens reflex (DSLR) images captured by volunteers from the US Civil Air Patrol (CAP). Imagery for these events were collected over a period of days following the storms' landfall in the US, with availability of aerial data far outweighing the sub-metre satellite imagery. The imagery described were collected as vertical views (NOAA) and oblique views (CAP) over the whole affected coastal and major riverine areas. A network of over 150 remote sensing experts systematically and manually processed images through visual interpretation, culminating in hundreds of thousands of individual properties identified as damaged or destroyed by wind or surge. A discussion is presented on the challenges of responding at such a fine level of spatial granularity for coastal

  20. Comparative analysis of transcriptomes in aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing.

    PubMed

    Okada, Taketo; Takahashi, Hironobu; Suzuki, Yutaka; Sugano, Sumio; Noji, Masaaki; Kenmoku, Hiromichi; Toyota, Masao; Kanaya, Shigehiko; Kawahara, Nobuo; Asakawa, Yoshinori; Sekita, Setsuko

    2016-12-01

    Ephedra plants are taxonomically classified as gymnosperms, and are medicinally important as the botanical origin of crude drugs and as bioresources that contain pharmacologically active chemicals. Here we show a comparative analysis of the transcriptomes of aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing by RNA-Seq. De novo assembly of short cDNA sequence reads generated 23,358, 13,373, and 28,579 contigs longer than 200 bases from aerial stems, roots, or both aerial stems and roots, respectively. The presumed functions encoded by these contig sequences were annotated by BLAST (blastx). Subsequently, these contigs were classified based on gene ontology slims, Enzyme Commission numbers, and the InterPro database. Furthermore, comparative gene expression analysis was performed between aerial stems and roots. These transcriptome analyses revealed differences and similarities between the transcriptomes of aerial stems and roots in E. sinica. Deep transcriptome sequencing of Ephedra should open the door to molecular biological studies based on the entire transcriptome, tissue- or organ-specific transcriptomes, or targeted genes of interest. PMID:27625990

  1. Multimodal detection of man-made objects in simulated aerial images

    NASA Astrophysics Data System (ADS)

    Baran, Matthew S.; Tutwiler, Richard L.; Natale, Donald J.; Bassett, Michael S.; Harner, Matthew P.

    2013-05-01

    This paper presents an approach to multi-modal detection of man-made objects from aerial imagery. Detections are made in polarization imagery, hyperspectral imagery, and LIDAR point clouds then fused into a single confidence map. The detections are based on reflective, spectral, and geometric features of man-made objects in airborne images. The polarization imagery detector uses the Stokes parameters and the degree of linear polarization to find highly polarizing objects. The hyperspectral detector matches scene spectra to a library of man-made materials using a combination of the spectral gradient angle and the generalized likelihood ratio test. The LIDAR detector clusters 3D points into objects using principle component analysis and prunes the detections by size and shape. Once the three channels are mapped into detection images, the information can be fused without some of the problems of multi-modal fusion, such as edge reversal. The imagery used in this system was simulated with a first-principles ray tracing image generator known as DIRSIG.

  2. Flow detection via sparse frame analysis for suspicious event recognition in infrared imagery

    NASA Astrophysics Data System (ADS)

    Fernandes, Henrique C.; Batista, Marcos A.; Barcelos, Celia A. Z.; Maldague, Xavier P. V.

    2013-05-01

    It is becoming increasingly evident that intelligent systems are very bene¯cial for society and that the further development of such systems is necessary to continue to improve society's quality of life. One area that has drawn the attention of recent research is the development of automatic surveillance systems. In our work we outline a system capable of monitoring an uncontrolled area (an outside parking lot) using infrared imagery and recognizing suspicious events in this area. The ¯rst step is to identify moving objects and segment them from the scene's background. Our approach is based on a dynamic background-subtraction technique which robustly adapts detection to illumination changes. It is analyzed only regions where movement is occurring, ignoring in°uence of pixels from regions where there is no movement, to segment moving objects. Regions where movement is occurring are identi¯ed using °ow detection via sparse frame analysis. During the tracking process the objects are classi¯ed into two categories: Persons and Vehicles, based on features such as size and velocity. The last step is to recognize suspicious events that may occur in the scene. Since the objects are correctly segmented and classi¯ed it is possible to identify those events using features such as velocity and time spent motionless in one spot. In this paper we recognize the suspicious event suspicion of object(s) theft from inside a parked vehicle at spot X by a person" and results show that the use of °ow detection increases the recognition of this suspicious event from 78:57% to 92:85%.

  3. Spatio-Temporal Analysis of Urban Heat Island and Urban Metabolism by Satellite Imagery over the Phoenix Metropolitan Area

    NASA Astrophysics Data System (ADS)

    Zhao, Q.; Zhan, S.; Kuai, X.; Zhan, Q.

    2015-12-01

    The goal of this research is to combine DMSP-OLS nighttime light data with Landsat imagery and use spatio-temporal analysis methods to evaluate the relationships between urbanization processes and temperature variation in Phoenix metropolitan area. The urbanization process is a combination of both land use change within the existing urban environment as well as urban sprawl that enlarges the urban area through the transformation of rural areas to urban structures. These transformations modify the overall urban climate environment, resulting in higher nighttime temperatures in urban areas compared to the surrounding rural environment. This is a well-known and well-studied phenomenon referred to as the urban heat island effect (UHI). What is unknown is the direct relationship between the urbanization process and the mechanisms of the UHI. To better understand this interaction, this research focuses on using nighttime light satellite imagery to delineate and detect urban extent changes and utilizing existing land use/land cover map or newly classified imagery from Landsat to analyze the internal urban land use variations. These data are combined with summer and winter land surface temperature data extracted from Landsat. We developed a time series of these combined data for Phoenix, AZ from 1992 to 2013 to analyze the relationships among land use change, land surface temperature and urban growth.

  4. Geomorphological diversity of Dong-Sha Atoll based on spectrum and texture analysis in high resolution remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Chen, Jianyu; Mao, Zhihua; He, Xianqiang

    2009-01-01

    Coral reefs are complex marine ecosystems that are constructed and maintained by biological communities that thrive in tropical oceans. The Dong-Sha Atoll is located at the northern continental margin of the South China Sea. It has being abused by destructive activity of human being and natural event during recent decades. Remote sensing offers a powerful tool for studying coral reef geomorphology and is the most cost-effective approach for large-scale reef survey. In this paper, the high-resolution Quickbird2 imageries which covered the full atoll are used to categorize the current distribution of coral reefs geomorphological structure therein with the auxiliary SPOT5 and ASTER imageries. Spectral and texture analysis are used to distinguish the geomorphological diversity during data processing. The Gray Level Co-occurrence Matrices is adopted for texture feature extraction and atoll geomorphology mapping in the high-resolution pan-color image of Quickbird2. Quickbird2 is considered as the most appropriate image source for coral reefs studies. In the Dong-Sha Atoll, various dynamical geomorphologic units are developed according to wave energy zones. There the reef frame types are classified to 3 different types according as its diversity at the image. The radial structure system is the most characteristic and from high resolution imagery we can distinguish the discrepancy between them.

  5. Mapping Urban Ecosystem Services Using High Resolution Aerial Photography

    NASA Astrophysics Data System (ADS)

    Pilant, A. N.; Neale, A.; Wilhelm, D.

    2010-12-01

    Ecosystem services (ES) are the many life-sustaining benefits we receive from nature: e.g., clean air and water, food and fiber, cultural-aesthetic-recreational benefits, pollination and flood control. The ES concept is emerging as a means of integrating complex environmental and economic information to support informed environmental decision making. The US EPA is developing a web-based National Atlas of Ecosystem Services, with a component for urban ecosystems. Currently, the only wall-to-wall, national scale land cover data suitable for this analysis is the National Land Cover Data (NLCD) at 30 m spatial resolution with 5 and 10 year updates. However, aerial photography is acquired at higher spatial resolution (0.5-3 m) and more frequently (1-5 years, typically) for most urban areas. Land cover was mapped in Raleigh, NC using freely available USDA National Agricultural Imagery Program (NAIP) with 1 m ground sample distance to test the suitability of aerial photography for urban ES analysis. Automated feature extraction techniques were used to extract five land cover classes, and an accuracy assessment was performed using standard techniques. Results will be presented that demonstrate applications to mapping ES in urban environments: greenways, corridors, fragmentation, habitat, impervious surfaces, dark and light pavement (urban heat island). Automated feature extraction results mapped over NAIP color aerial photograph. At this scale, we can look at land cover and related ecosystem services at the 2-10 m scale. Small features such as individual trees and sidewalks are visible and mappable. Classified aerial photo of Downtown Raleigh NC Red: impervious surface Dark Green: trees Light Green: grass Tan: soil

  6. An Analysis of the Need Fulfillment Imagery in Children's Folk Tales.

    ERIC Educational Resources Information Center

    Napier, Georgia; Ali, Munir

    A study described the need fulfillment imagery found in selected versions of folk tales for children. The needs identified were physiological, safety, love, achievement, knowledge, change, and aesthetic. Forty individual books published since 1960 under the broad category of folklore and available in the United States were content analyzed.…

  7. An interregional analysis of natural vegetation analogues using ERTS-1 imagery

    NASA Technical Reports Server (NTRS)

    Poulton, C. E.; Welch, R. I.

    1973-01-01

    The identification of ecological analogs of natural vegetation and food crops using ERTS-1 imagery is discussed. Signatures of four natural vegetation analogs have been determined from color photography. Color additive techniques to improve the photointerpretation are examined. Tests were conducted at test sites in Louisiana, California, and Colorado.

  8. Measuring creative imagery abilities

    PubMed Central

    Jankowska, Dorota M.; Karwowski, Maciej

    2015-01-01

    Over the decades, creativity and imagination research developed in parallel, but they surprisingly rarely intersected. This paper introduces a new theoretical model of creative visual imagination, which bridges creativity and imagination research, as well as presents a new psychometric instrument, called the Test of Creative Imagery Abilities (TCIA), developed to measure creative imagery abilities understood in accordance with this model. Creative imagination is understood as constituted by three interrelated components: vividness (the ability to create images characterized by a high level of complexity and detail), originality (the ability to produce unique imagery), and transformativeness (the ability to control imagery). TCIA enables valid and reliable measurement of these three groups of abilities, yielding the general score of imagery abilities and at the same time making profile analysis possible. We present the results of nine studies on a total sample of more than 1700 participants, showing the factor structure of TCIA using confirmatory factor analysis, as well as provide data confirming this instrument's validity and reliability. The availability of TCIA for interested researchers may result in new insights and possibilities of integrating the fields of creativity and imagination science. PMID:26539140

  9. The availability of local aerial photography in southern California. [for solution of urban planning problems

    NASA Technical Reports Server (NTRS)

    Allen, W., III; Sledge, B.; Paul, C. K.; Landini, A. J.

    1974-01-01

    Some of the major photography and photogrammetric suppliers and users located in Southern California are listed. Recent trends in aerial photographic coverage of the Los Angeles basin area are also noted, as well as the uses of that imagery.

  10. Photomorphic analysis techniques: An interim spatial analysis using satellite remote sensor imagery and historical data

    NASA Technical Reports Server (NTRS)

    Keuper, H. R.; Peplies, R. W.; Gillooly, R. P.

    1977-01-01

    The use of machine scanning and/or computer-based techniques to provide greater objectivity in the photomorphic approach was investigated. Photomorphic analysis and its application in regional planning are discussed. Topics included: delineation of photomorphic regions; inadequacies of existing classification systems; tonal and textural characteristics and signature analysis techniques; pattern recognition and Fourier transform analysis; and optical experiments. A bibliography is included.

  11. AERIAL RADIOLOGICAL SURVEYS

    SciTech Connect

    Proctor, A.E.

    1997-06-09

    Measuring terrestrial gamma radiation from airborne platforms has proved to be a useful method for characterizing radiation levels over large areas. Over 300 aerial radiological surveys have been carried out over the past 25 years including U.S. Department of Energy (DOE) sites, commercial nuclear power plants, Formerly Utilized Sites Remedial Action Program/Uranium Mine Tailing Remedial Action Program (FUSRAP/UMTRAP) sites, nuclear weapons test sites, contaminated industrial areas, and nuclear accident sites. This paper describes the aerial measurement technology currently in use by the Remote Sensing Laboratory (RSL) for routine environmental surveys and emergency response activities. Equipment, data-collection and -analysis methods, and examples of survey results are described.

  12. Fault Tolerance Analysis of L1 Adaptive Control System for Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Krishnamoorthy, Kiruthika

    Trajectory tracking is a critical element for the better functionality of autonomous vehicles. The main objective of this research study was to implement and analyze L1 adaptive control laws for autonomous flight under normal and upset flight conditions. The West Virginia University (WVU) Unmanned Aerial Vehicle flight simulation environment was used for this purpose. A comparison study between the L1 adaptive controller and a baseline conventional controller, which relies on position, proportional, and integral compensation, has been performed for a reduced size jet aircraft, the WVU YF-22. Special attention was given to the performance of the proposed control laws in the presence of abnormal conditions. The abnormal conditions considered are locked actuators (stabilator, aileron, and rudder) and excessive turbulence. Several levels of abnormal condition severity have been considered. The performance of the control laws was assessed over different-shape commanded trajectories. A set of comprehensive evaluation metrics was defined and used to analyze the performance of autonomous flight control laws in terms of control activity and trajectory tracking errors. The developed L1 adaptive control laws are supported by theoretical stability guarantees. The simulation results show that L1 adaptive output feedback controller achieves better trajectory tracking with lower level of control actuation as compared to the baseline linear controller under nominal and abnormal conditions.

  13. Integrated analysis of high resolution aeromagnetic and satellite imagery data for hydrocarbon exploration in frontier and mature basins

    SciTech Connect

    Berger, Z.; Nash, C.; Ellis, C.; Witham, B.

    1996-08-01

    Recent improvement in the collection and processing of high resolution aeromagnetic data provides, for the first time, information on the spatial distribution of geological structures in the sedimentary section. The magnetic data, which is presented with a series of color images, can be easily merged and correlated with satellite imagery data, air and space home radar and conventional aerial photography. The integration of these two different reconnaissance tools provides excellent means for structural mapping and early evaluation of hydrocarbon plays in both frontier and mature areas. A series of examples supported by both surface and subsurface controls are used to illustrate the exploration application of these two different data sets. In the frontier fold and thrust belts regions of the North Slope Alaska, the Andes of South America, and the Canadian Foothills, high resolution magnetic images and side-looking air and space borne radar data are effectively used to improve the interpretation of geological structures above the detachment levels. This data was also used to identify the presence of basement involved reactivated structures and related migration pathways. In less deformed and more mature areas, such as the Central Basin Platform of West Texas and the Peace River Arch of the Western Canada Basin, the integration of high resolution magnetic images and Landsat TM data leads to the recognition of new faults and fracture systems and related hydrocarbon plays. The availability of high resolution magnetic surveys and new space borne radar systems such as ERS-1, JERS-1 and RADARSAT should play a significant role in exploration of the heavily vegetated fold belt regions of the tropics as well as the vast plains and plateaus of the South American continent.

  14. Analysis of stratocumulus cloud fields using LANDSAT imagery: Size distributions and spatial separations

    NASA Technical Reports Server (NTRS)

    Welch, R. M.; Sengupta, S. K.; Chen, D. W.

    1990-01-01

    Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.

  15. Estimation of Tree Size Diversity Using Object Oriented Texture Analysis and Aster Imagery

    PubMed Central

    Ozdemir, Ibrahim; Norton, David A.; Ozkan, Ulas Yunus; Mert, Ahmet; Senturk, Ozdemir

    2008-01-01

    This study investigates the potential of object-based texture parameters extracted from 15m spatial resolution ASTER imagery for estimating tree size diversity in a Mediterranean forested landscape in Turkey. Tree size diversity based on tree basal area was determined using the Shannon index and Gini Coefficient at the sampling plot level. Image texture parameters were calculated based on the grey level co-occurrence matrix (GLCM) for various image segmentation levels. Analyses of relationships between tree size diversity and texture parameters found that relationships between the Gini Coefficient and the GLCM values were the most statistically significant, with the highest correlation (r=0.69) being with GLCM Homogeneity values. In contrast, Shannon Index values were weakly correlated with image derived texture parameters. The results suggest that 15m resolution Aster imagery has considerable potential in estimating tree size diversity based on the Gini Coefficient for heterogeneous Mediterranean forests.

  16. Analysis of Photosynthetic Rate and Bio-Optical Components from Ocean Color Imagery

    NASA Technical Reports Server (NTRS)

    Kiefer, Dale A.; Stramski, Dariusz

    1997-01-01

    Our research over the last 5 years indicates that the successful transformation of ocean color imagery into maps of bio-optical properties will require continued development and testing of algorithms. In particular improvements in the accuracy of predicting from ocean color imagery the concentration of the bio-optical components of sea as well as the rate of photosynthesis will require progress in at least three areas: (1) we must improve mathematical models of the growth and physiological acclimation of phytoplankton; (2) we must better understand the sources of variability in the absorption and backscattering properties of phytoplankton and associated microparticles; and (3) we must better understand how the radiance distribution just below the sea surface varies as a function sun and sky conditions and inherent optical properties.

  17. Object detection and classification using image moment functions in the applied to video and imagery analysis

    NASA Astrophysics Data System (ADS)

    Mise, Olegs; Bento, Stephen

    2013-05-01

    This paper proposes an object detection algorithm and a framework based on a combination of Normalized Central Moment Invariant (NCMI) and Normalized Geometric Radial Moment (NGRM). The developed framework allows detecting objects with offline pre-loaded signatures and/or using the tracker data in order to create an online object signature representation. The framework has been successfully applied to the target detection and has demonstrated its performance on real video and imagery scenes. In order to overcome the implementation constraints of the low-powered hardware, the developed framework uses a combination of image moment functions and utilizes a multi-layer neural network. The developed framework has been shown to be robust to false alarms on non-target objects. In addition, optimization for fast calculation of the image moments descriptors is discussed. This paper presents an overview of the developed framework and demonstrates its performance on real video and imagery scenes.

  18. Comparison and analysis of linear alignments from Landsat imagery of diverse geologic terrane

    SciTech Connect

    Frederking, R.L.; Allenbach, R.T.; Jackson, R.B.; Keefer, W.D.; Motamedi, A.R.; Von Der Heyde, W.S.; Wingo, R.D.

    1985-01-01

    Geometric alignments referred to as linears, linear features or lineaments are routinely observed on Landsat imagery. Alignments that cannot be accounted for by cultural, known geologic or other recognized sources are classed as speculative and of dubious geologic significance. These features may in fact be imaginary. Speculative alignments are however, important to exploration because of their frequent association with known hydrocarbon accumulations and/or areas of mineralization. Data pertaining to speculative linear alignments in diverse geologic terrane have been obtained. Alignment frequency rose diagrams are prepared for each area and statistical profiles are developed. Replication of linear alignments suggest that these features are real elements of the imagery and not imaginary lines. Observed orientation modal frequencies are consistent with alignment trends of known structural features in the different areas. Variation in spatial density of alignments appears to be related to lithologic factors.

  19. An evaluation of the use of ERTS-1 satellite imagery for grizzly bear habitat analysis. [Montana

    NASA Technical Reports Server (NTRS)

    Varney, J. R.; Craighead, J. J.; Sumner, J. S.

    1974-01-01

    Improved classification and mapping of grizzly habitat will permit better estimates of population density and distribution, and allow accurate evaluation of the potential effects of changes in land use, hunting regulation, and management policies on existing populations. Methods of identifying favorable habitat from ERTS-1 multispectral scanner imagery were investigated and described. This technique could reduce the time and effort required to classify large wilderness areas in the Western United States.

  20. Aerial Scene Recognition using Efficient Sparse Representation

    SciTech Connect

    Cheriyadat, Anil M

    2012-01-01

    Advanced scene recognition systems for processing large volumes of high-resolution aerial image data are in great demand today. However, automated scene recognition remains a challenging problem. Efficient encoding and representation of spatial and structural patterns in the imagery are key in developing automated scene recognition algorithms. We describe an image representation approach that uses simple and computationally efficient sparse code computation to generate accurate features capable of producing excellent classification performance using linear SVM kernels. Our method exploits unlabeled low-level image feature measurements to learn a set of basis vectors. We project the low-level features onto the basis vectors and use simple soft threshold activation function to derive the sparse features. The proposed technique generates sparse features at a significantly lower computational cost than other methods~\\cite{Yang10, newsam11}, yet it produces comparable or better classification accuracy. We apply our technique to high-resolution aerial image datasets to quantify the aerial scene classification performance. We demonstrate that the dense feature extraction and representation methods are highly effective for automatic large-facility detection on wide area high-resolution aerial imagery.

  1. Cotton crop spectral imaging analysis: a web-based hyperspectral synthetic imagery simulation system

    NASA Astrophysics Data System (ADS)

    Alarcon, Vladimir J.; Sassenrath, Gretchen F.

    2004-11-01

    The development of spectral libraries for specific vegetation species and soils is useful for identifying different physiological or physical-chemical characteristics. Usually, spectral libraries are provided as a data-base add-in of current commercial software used for analyzing hyperspectral imagery. The use of those databases requires installation of the software in the user"s machine for either visualizing or using the spectral libraries. There are also spectral libraries available on the web but the data is static and partitioned by spectrum of vegetation or soil because the size of the files of actual hyperspectral images precludes it"s publication on the web. In this paper, a web-based simulation environment for generating hyperspectral synthetic imagery of cotton plots is presented. The system was developed using Java and is based on a previous synthetic imagery program1. The mathematical and numerical formulation of the model is briefly sketched. The core computing components of the simulation environment were written in C for their computational efficiency. The emerging Java Native Interface (JNI) technique and standard Java techniques were used to design a user-friendly simulator. The simulation system provides interactive user control and real time visualization of the resulting hyperspectral image through standard web browsers. It shows potential for providing web-based hyperspectral libraries, in the form of images, for public use.

  2. Processing Digital Imagery Data

    NASA Technical Reports Server (NTRS)

    Conner, P. K.; Junkin, B. G.; Graham, M. H.; Kalcic, M. T.; Seyfarth, B. R.

    1985-01-01

    Earth Resources Laboratory Applications Software (ELAS) is geobased information system designed for analyzing and processing digital imagery data. ELAS offers user of remotely sensed data wide range of easy to use capabilities in areas of land cover analysis. ELAS system written in FORTRAN and Assembler for batch or interactive processing.

  3. A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping.

    PubMed

    Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

    2016-04-26

    Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply.

  4. A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping

    PubMed Central

    Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

    2016-01-01

    Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply. PMID:27128915

  5. A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping.

    PubMed

    Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

    2016-01-01

    Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply. PMID:27128915

  6. Aerodynamic analysis and simulation of a twin-tail tilt-duct unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Abdollahi, Cyrus

    The tilt-duct vertical takeoff and landing (VTOL) concept has been around since the early 1960s; however, to date the design has never passed the research phase and development phase. Nearly 50 years later, American Dynamics Flight Systems (ADFS) is developing the AD-150, a 2,250lb weight class unmanned aerial vehicle (UAV) configured with rotating ducts on each wingtip. Unlike its predecessor, the Doak VZ-4, the AD-150 features a V tail and wing sweep -- both of which affect the aerodynamic behavior of the aircraft. Because no aircraft of this type has been built and tested, vital aerodynamic research was conducted on the bare airframe behavior (without wingtip ducts). Two weeks of static and dynamic testing were performed on a 3/10th scale model at the University of Maryland's 7' x 10' low speed wind tunnel to facilitate the construction of a nonlinear flight simulator. A total of 70 dynamic tests were performed to obtain damping parameter estimates using the ordinary least squares methodology. Validation, based on agreement between static and dynamic estimates of the pitch and yaw stiffness terms, showed an average percent error of 14.0% and 39.6%, respectively. These inconsistencies were attributed to: large dynamic displacements not encountered during static testing, regressor collinearity, and, while not conclusively proven, differences in static and dynamic boundary layer development. Overall, the damping estimates were consistent and repeatable, with low scatter over a 95% confidence interval. Finally, a basic open loop simulation was executed to demonstrate the instability of the aircraft. As a result, it is recommended that future work be performed to determine trim points and linear models for controls development.

  7. Satellite Imagery Assisted Road-Based Visual Navigation System

    NASA Astrophysics Data System (ADS)

    Volkova, A.; Gibbens, P. W.

    2016-06-01

    There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth* build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented. * The algorithm is independent of the source of satellite imagery and another provider can be used

  8. Oriental - Automatic Geo-Referencing and Ortho-Rectification of Archaeological Aerial Photographs

    NASA Astrophysics Data System (ADS)

    Karel, W.; Doneus, M.; Verhoeve, G.; Bries, C.; Ressl, C.; Pfeifer, N.

    2013-07-01

    This paper presents the newly developed software OrientAL, which aims at providing a fully automated processing chain from aerial photographs to orthophoto maps. It considers the special requirements of archaeological aerial images, including oblique imagery, single images, poor approximate georeferencing, and historic photographs. As a first step the automatic relative orientation of images from an archaeological image archive is presented.

  9. Aerial detection of leaf senescence for a geobotanical study

    NASA Technical Reports Server (NTRS)

    Schwaller, M.; Tkach, S. J.

    1986-01-01

    A geobotanical investigation based on the detection of premature leaf senescence was conducted in an area of predominantly chalcocite mineralization of the Keweenaw Peninsula in Michigan's Upper Peninsula. Spectrophotometric measurements indicated that the region from 600 to 700 nm captures the rise in red reflectance characteristic of senescent leaves. Observations at other wavelengths do not distinguish between senescent and green leaves as clearly and unequivocably as observations at these wavelengths. Small format black and white aerial photographs filtered for the red band (600 to 700 nm) and Thematic Mapper Simulator imagery were collected during the period of fall senescence in the study area. Soil samples were collected from two areas identified by leaf senescence and from two additional sites where the leaf canopy was still green. Geochemical analysis revealed that the sites characterized by premature leaf senescence had a significantly higher median soil copper concentration than the other two areas.

  10. Stream network analysis and geomorphic flood plain mapping from orbital and suborbital remote sensing imagery application to flood hazard studies in central Texas

    NASA Technical Reports Server (NTRS)

    Baker, V. R. (Principal Investigator); Holz, R. K.; Hulke, S. D.; Patton, P. C.; Penteado, M. M.

    1975-01-01

    The author has identified the following significant results. Development of a quantitative hydrogeomorphic approach to flood hazard evaluation was hindered by (1) problems of resolution and definition of the morphometric parameters which have hydrologic significance, and (2) mechanical difficulties in creating the necessary volume of data for meaningful analysis. Measures of network resolution such as drainage density and basin Shreve magnitude indicated that large scale topographic maps offered greater resolution than small scale suborbital imagery and orbital imagery. The disparity in network resolution capabilities between orbital and suborbital imagery formats depends on factors such as rock type, vegetation, and land use. The problem of morphometric data analysis was approached by developing a computer-assisted method for network analysis. The system allows rapid identification of network properties which can then be related to measures of flood response.

  11. Neural and cortical analysis of swallowing and detection of motor imagery of swallow for dysphagia rehabilitation-A review.

    PubMed

    Yang, H; Ang, K K; Wang, C; Phua, K S; Guan, C

    2016-01-01

    Swallowing is an essential function in our daily life; nevertheless, stroke or other neurodegenerative diseases can cause the malfunction of swallowing function, ie, dysphagia. The objectives of this review are to understand the neural and cortical basis of swallowing and tongue, and review the latest techniques on the detection of motor imagery of swallow (MI-SW) and motor imagery of tongue movements (MI-TM), so that a practical system can be developed for the rehabilitation of poststroke dysphagia patients. Specifically, we firstly describe the swallowing process and how the swallowing function is assessed clinically. Secondly, we review the techniques that performed the neural and cortical analysis of swallowing and tongue based on different modalities such as functional magnetic resonance imaging, positron emission tomography, near-infrared spectroscopy (NIRS), and magnetoencephalography. Thirdly, we review the techniques that performed detection and analysis of MI-SW and MI-TM for dysphagia stroke rehabilitation based on electroencephalography (EEG) and NIRS. Finally, discussions on the advantages and limitations of the studies are presented; an example system and future research directions for the rehabilitation of stroke dysphagia patients are suggested. PMID:27590970

  12. Assessment of ERTS-1 imagery as a tool for regional geological analysis in New York State. [Lake Ontario

    NASA Technical Reports Server (NTRS)

    Isachsen, Y. W. (Principal Investigator); Fakundiny, R. H.; Forster, S. W.

    1974-01-01

    The author has identified the following significant results. Linear anomalies dominate the new geological information derived from ERTS-1 imagery, total lengths now exceeding 26,500 km. Maxima on rose diagrams for ERTS-1 anomalies correspond well with those for mapped faults and topographic lineaments. Multi-scale analysis of linears shows that single topographic linears at 1:2,500,000 may become dashed linears at 1:1,000,000 aligned zones of shorter parallel, en echelon, or conjugate linears at 1:5000,000, and shorter linears lacking any conspicuous zonal alignment at 1:250,000. Field work in the Catskills suggests that the prominent new NNE lineaments may be surface manifestations of dip slip faulting in the basement, and that it may become possible to map major joint sets over extensive plateau regions directly on the imagery. Most circular features found were explained away by U-2 airfoto analysis but several remain as anomalies. Visible glacial features include individual drumlins, drumlinoids, eskers, ice-marginal drainage channels, glacial lake shorelines, sand plains, and end moraines.

  13. Current and Future Applications of Multispectral (RGB) Satellite Imagery for Weather Analysis and Forecasting Applications

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew L.; Fuell, Kevin K.; LaFontaine, Frank; McGrath, Kevin; Smith, Matt

    2013-01-01

    Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low ]Earth orbits. The NASA Short ]term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA fs Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channels available from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard METEOSAT ]9. This broader suite includes products that discriminate between air mass types associated with synoptic ]scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES ]R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar ]Orbiting Partnership (S ]NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross ]track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites. New applications from VIIRS extend multispectral composites available from MODIS and SEVIRI while adding new capabilities through incorporation of additional CrIS channels or information from the Near Constant Contrast or gDay ]Night Band h, which provides moonlit reflectance from clouds and detection of fires or city lights. This presentation will

  14. Analysis on the Utility of Satellite Imagery for Detection of Agricultural Facility

    NASA Astrophysics Data System (ADS)

    Kang, J.-M.; Baek, S.-H.; Jung, K.-Y.

    2012-07-01

    Now that the agricultural facilities are being increase owing to development of technology and diversification of agriculture and the ratio of garden crops that are imported a lot and the crops cultivated in facilities are raised in Korea, the number of vinyl greenhouses is tending upward. So, it is important to grasp the distribution of vinyl greenhouses as much as that of rice fields, dry fields and orchards, but it is difficult to collect the information of wide areas economically and correctly. Remote sensing using satellite imagery is able to obtain data of wide area at the same time, quickly and cost-effectively collect, monitor and analyze information from every object on earth. In this study, in order to analyze the utilization of satellite imagery at detection of agricultural facility, image classification was performed about the agricultural facility, vinyl greenhouse using Formosat-2 satellite imagery. The training set of sea, vegetation, building, bare ground and vinyl greenhouse was set to monitor the agricultural facilities of the object area and the training set for the vinyl greenhouses that are main monitoring object was classified and set again into 3 types according the spectral characteristics. The image classification using 4 kinds of supervise classification methods applied by the same training set were carried out to grasp the image classification method which is effective for monitoring agricultural facilities. And, in order to minimize the misclassification appeared in the classification using the spectral information, the accuracy of classification was intended to be raised by adding texture information. The results of classification were analyzed regarding the accuracy comparing with that of naked-eyed detection. As the results of classification, the method of Mahalanobis distance was shown as more efficient than other methods and the accuracy of classification was higher when adding texture information. Hence the more effective

  15. Multi-spectral analysis of ice sheets using co-registered SAR and TM imagery

    NASA Technical Reports Server (NTRS)

    Vornberger, P. L.; Bindschadler, R. A.

    1992-01-01

    Landsat Thematic Mapper and airborne Synthetic Aperture Radar (SAR) imagery acquired over an area of south-western Greenland are coregistered and analyzed. Significant corrections to the SAR data were required to account for range-darkening, non-square pixel dimensions, speckle, and relief distortion. In one area, exposed rock was available for use as co-registration control, while in another area it was absent and supraglacial lakes and streams were used. The coregistered scenes highlight many differences between the optical and radar signatures of ice sheets.

  16. The uses of ERTS-1 imagery in the analysis of landscape change. [agriculture, strip mining forests, urban-suburban growth, and flooding in Tennessee, Kentucky, Mississippi, and Alabama

    NASA Technical Reports Server (NTRS)

    Rehder, J. B. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. The analysis of strip mining from ERTS-1 data has resulted in the mapping of landscape changes for the Cumberland Plateau Test Site. Several mapping experiments utilizing ERTS-1 data have been established for the mapping of state-wide land use regions. The first incorporates 12 frames of ERTS-1 imagery for the generalized thematic mapping of forest cover for the state of Tennessee. In another mapping effort, 14 ERTS-1 images have been analyzed for plowed ground signatures to produce a map of agricultural regions for Tennessee, Kentucky, and the northern portions of Mississippi and Alabama. Generalized urban land use categories and transportation networks have been determined from ERTS-1 imagery for the Knoxville Test Site. Finally, through the analysis of ERTS-1 imagery, short-lived phenomena such as the 1973 spring floods on the Mississippi River in western Tennessee, have been detected, monitored, and mapped.

  17. Advances In very high resolution satellite imagery analysis for Monitoring human settlements

    SciTech Connect

    Vatsavai, Raju; Cheriyadat, Anil M; Bhaduri, Budhendra L

    2014-01-01

    The high rate of urbanization, political conflicts and ensuing internal displacement of population, and increased poverty in the 20th century has resulted in rapid increase of informal settlements. These unplanned, unauthorized, and/or unstructured homes, known as informal settlements, shantytowns, barrios, or slums, pose several challenges to the nations, as these settlements are often located in most hazardous regions and lack basic services. Though several World Bank and United Nations sponsored studies stress the importance of poverty maps in designing better policies and interventions, mapping slums of the world is a daunting and challenging task. In this paper, we summarize our ongoing research on settlement mapping through the utilization of Very high resolution (VHR) remote sensing imagery. Most existing approaches used to classify VHR images are single instance (or pixel-based) learning algorithms, which are inadequate for analyzing VHR imagery, as single pixels do not contain sufficient contextual information (see Figure 1). However, much needed spatial contextual information can be captured via feature extraction and/or through newer machine learning algorithms in order to extract complex spatial patterns that distinguish informal settlements from formal ones. In recent years, we made significant progress in advancing the state of art in both directions. This paper summarizes these results.

  18. Analysis of recent literature concerning relaxation and imagery interventions for cancer pain.

    PubMed

    Wallace, K G

    1997-04-01

    A review of literature concerning relaxation and imagery interventions for cancer pain is necessary because major review articles have excluded nursing research or were written prior to the publication of controlled studies in cancer pain conducted by nurses. This review of published nursing/medical/psychological literature of adults with cancer pain conducted over the past 14 years (1982-95) revealed few controlled studies, weak theoretical frameworks, few complete descriptions of the nature of the pain problem, and lack of control over the interventions. Most had very small sizes and could not demonstrate significant effects. Additionally, the intervention methods and length of the interventions were highly variable. Despite these design shortcomings, relaxation and imagery appear to reduce the sensory experience of pain, have equivocal effects on affective measures, and appear to have no effect on functional status. Suggestions for improvement include the need for more experimental studies, more complete descriptions of pain, improved statistical reporting, controls over adequacy of and compliance to the interventions, use of single interventions, and use of more complex measures of affective outcomes. Additionally, the paper contains a discussion of the problems of measuring selected outcome variables in this type of research.

  19. 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.

  20. An Analysis of Unique Aerial Photographs of Atmospheric Eddies in Marine Stratocumulus Clouds Downwind of Complex Terrain Along the California Coast

    NASA Astrophysics Data System (ADS)

    Muller, B. M.; Herbster, C. G.; Mosher, F. R.

    2013-12-01

    Unique aerial photographs of atmospheric eddies in marine stratocumulus clouds downwind of complex terrain along the California coast are presented and analyzed. While satellite imagery of similar eddies have appeared in the scientific literature since the 1960's, it is believed that these are the first close-up photographs of such eddies, taken from an airplane, to appear in publication. Two photographs by a commercial pilot, flying California coastal routes, are presented: one from July 16, 2006 downwind of Santa Cruz Island, a 740 m peak bordering the Santa Barbara Channel off the California coast; and one from September 12, 2006 near Grover Beach, California, downwind of a headland containing the San Luis Range, a region of complex terrain near San Luis Obispo, California, with ridges ranging approximately from 240 to 550 m elevation. Both eddies occurred in the lee of inversion-penetrating terrain, and were marked by a cyclonic vortex in the clouds with a striking cloud-free 'eye' feature roughly 3 km in diameter. The Santa Cruz Island eddy was 25 km in length and 9-10 km in width, while the Grover Beach eddy was 17 km in length and had a width of 9 km, placing it in the meso-gamma scale of atmospheric features. GOES (Geostationary Operational Environmental Satellite) imagery for both cases was obtained and help to define the lifecycle and motions of the eddies captured in the snapshots. Relevant meteorological observations for the Santa Cruz Island eddy were not located, but in-situ observations from the Diablo Canyon Nuclear Power Plant, California Polytechnic State University (Cal Poly) pier, and the San Luis Obispo County Air Pollution Control District, made possible a more detailed examination of the Grover Beach eddy and its structure. Additionally, we offer speculation on an eddy formation mechanism consistent with the satellite and in-situ observations described in this presentation, and hypotheses from the literature on low Froude number, continuously

  1. Design and Analysis of a Single-Camera Omnistereo Sensor for Quadrotor Micro Aerial Vehicles (MAVs) †

    PubMed Central

    Jaramillo, Carlos; Valenti, Roberto G.; Guo, Ling; Xiao, Jizhong

    2016-01-01

    We describe the design and 3D sensing performance of an omnidirectional stereo (omnistereo) vision system applied to Micro Aerial Vehicles (MAVs). The proposed omnistereo sensor employs a monocular camera that is co-axially aligned with a pair of hyperboloidal mirrors (a vertically-folded catadioptric configuration). We show that this arrangement provides a compact solution for omnidirectional 3D perception while mounted on top of propeller-based MAVs (not capable of large payloads). The theoretical single viewpoint (SVP) constraint helps us derive analytical solutions for the sensor’s projective geometry and generate SVP-compliant panoramic images to compute 3D information from stereo correspondences (in a truly synchronous fashion). We perform an extensive analysis on various system characteristics such as its size, catadioptric spatial resolution, field-of-view. In addition, we pose a probabilistic model for the uncertainty estimation of 3D information from triangulation of back-projected rays. We validate the projection error of the design using both synthetic and real-life images against ground-truth data. Qualitatively, we show 3D point clouds (dense and sparse) resulting out of a single image captured from a real-life experiment. We expect the reproducibility of our sensor as its model parameters can be optimized to satisfy other catadioptric-based omnistereo vision under different circumstances. PMID:26861351

  2. A Meta-analysis of Imagery Rehearsal for Post-trauma Nightmares: Effects on Nightmare Frequency, Sleep Quality, and Posttraumatic Stress

    PubMed Central

    Casement, Melynda D.; Swanson, Leslie M.

    2014-01-01

    This meta-analysis evaluates the efficacy of imagery rehearsal as a treatment for nightmares, general sleep disturbance, and symptoms of post-traumatic stress. Bibliographic databases and cited references were searched to identify clinical trials of imagery rehearsal in individuals with post-trauma nightmares. Thirteen studies met inclusion criteria and reported sleep and post-traumatic stress outcomes in sufficient detail to calculate effect sizes. Results indicate that imagery rehearsal had large effects on nightmare frequency, sleep quality, and PTSD symptoms. These effects were sustained through 6 to 12 month follow-up. Furthermore, interventions that included both imagery rehearsal and cognitive behavioral therapy for insomnia resulted in greater treatment-related improvement in sleep quality than imagery rehearsal alone. Combined treatment did not improve outcomes for PTSD or nightmares. Notably, effect sizes were small in the single study that included an active-treatment control condition. Future research should identify necessary and sufficient components of interventions for trauma-related sleep disturbance and post-traumatic stress (e.g., exposure, cognitive reappraisal, circadian regulation). PMID:22819998

  3. Daytime multispectral scanner aerial surveys of the Oak Ridge Reservation, 1992--1994: Overview of data processing and analysis by the Environmental Restoration Remote Sensing Program, Fiscal year 1995

    SciTech Connect

    Smyre, J.L.; Hodgson, M.E.; Moll, B.W.; King, A.L.; Cheng, Yang

    1995-11-01

    Environmental Restoration (ER) Remote Sensing and Special Surveys Program was in 1992 to apply the benefits of remote sensing technologies to Environmental Restoration Management (ERWM) programs at all of the five United States Department of Energy facilities operated and managed by Martin Marietta Energy Systems, Inc. (now Lockheed Martin Energy Systems)-the three Oak Ridge Reservation (ORR) facilities, the Paducah Gaseous Diffusion Plant (PGDP), the Portsmouth Gaseous Diffusion Plant (PORTS)-and adjacent off-site areas. The Remote Sensing Program includes the management of routine and special surveys at these sites, application of state-of-the-art remote sensing and geophysical technologies, and data transformation, integration, and analyses required to make the information valuable to ER. Remotely-sensed data collected of the ORR include natural color and color infrared (IR) aerial photography, 12-band multispectral scanner imagery, predawn thermal IR sensor imagery, magnetic and electromagnetic geophysical surveys, and gamma radiological data.

  4. Vehicle classification in WAMI imagery using deep network

    NASA Astrophysics Data System (ADS)

    Yi, Meng; Yang, Fan; Blasch, Erik; Sheaff, Carolyn; Liu, Kui; Chen, Genshe; Ling, Haibin

    2016-05-01

    Humans have always had a keen interest in understanding activities and the surrounding environment for mobility, communication, and survival. Thanks to recent progress in photography and breakthroughs in aviation, we are now able to capture tens of megapixels of ground imagery, namely Wide Area Motion Imagery (WAMI), at multiple frames per second from unmanned aerial vehicles (UAVs). WAMI serves as a great source for many applications, including security, urban planning and route planning. These applications require fast and accurate image understanding which is time consuming for humans, due to the large data volume and city-scale area coverage. Therefore, automatic processing and understanding of WAMI imagery has been gaining attention in both industry and the research community. This paper focuses on an essential step in WAMI imagery analysis, namely vehicle classification. That is, deciding whether a certain image patch contains a vehicle or not. We collect a set of positive and negative sample image patches, for training and testing the detector. Positive samples are 64 × 64 image patches centered on annotated vehicles. We generate two sets of negative images. The first set is generated from positive images with some location shift. The second set of negative patches is generated from randomly sampled patches. We also discard those patches if a vehicle accidentally locates at the center. Both positive and negative samples are randomly divided into 9000 training images and 3000 testing images. We propose to train a deep convolution network for classifying these patches. The classifier is based on a pre-trained AlexNet Model in the Caffe library, with an adapted loss function for vehicle classification. The performance of our classifier is compared to several traditional image classifier methods using Support Vector Machine (SVM) and Histogram of Oriented Gradient (HOG) features. While the SVM+HOG method achieves an accuracy of 91.2%, the accuracy of our deep

  5. Utilizing ERTS-A imagery for tectonic analysis through study of Big Horn Mountains region

    NASA Technical Reports Server (NTRS)

    Hoppin, R. A. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. Winter imagery in December 6-10, 1972 and January 11-13, 1972, provides optimum snow cover and depth such that, along with low sun angle, topography and drainage are markedly enhanced. Several features are visible that are poorly, or even not distinguishable on clear scenes without snow. Examples are Bear Butte (igneous plug) and Elkhorn Peak (dome) on scene (1136-17130), northeastern Black Hills, (1172-17130) a linear linking the Cascade anticline and Cretaceous hogbacks near Hot Springs, S. D. south to the Niobrara River, and (1140-17373) the Lake Basin fault zone north of Billings, Montana. Extremely heavy snows in April completely blot out all vegetation and topography in the Bighorn, Wind River, and Beartooth ranges.

  6. Analysis of airborne multi-spectral imagery of an oil spill field trial

    SciTech Connect

    Kalnins, V.J.; Freemantle, J.R.; Brown, C.E.

    1996-12-31

    A field trial was conducted at Canadian Forces Base Petawawa in May 1993 by the Emergencies Science Division of Environment Canada to test the effectiveness of remote sensing systems to detect oil spills. Shallow test pools covered with various thicknesses and types of oil were overflown by a number of sensors. Imagery from one of the sensors used, the Multi-element Electro-optical Imaging Scanner (MEIS), has recently been transcribed from high density digital tape and analyzed. The MEIS sensor was flown on a Falcon 20 jet and collected data at 7 different wavelengths from 518 nm to 873 nm. Preliminary results show that one of the slicks, Hydraulic Fluid, can be readily identified by its distinctive color in the visible region. The oil slicks, at least under these very controlled conditions, presented unique spectral signatures which could be identified using normal image processing classification techniques.

  7. Analysis of coastal change in Marie Byrd Land and Ellsworth Land, West Antarctica, using Landsat imagery

    USGS Publications Warehouse

    Ferrigno, J.G.; Williams, R.S.; Rosanova, C.E.; Lucchitta, B.K.; Swithinbank, C.

    1998-01-01

    The U.S. Geological Survey is using Landsat imagery from the early 1970s and mid- to late 1980s/early 1990s to analyze glaciological features, compile a glacier inventory, measure surface velocities of outlet glaciers, ice streams and ice shelves, determine coastline change and calculate the area and volume of iceberg calving in Antarctica. Ice-surface velocities in Marie Byrd and Ellsworth Lands, West Antarctica, range from the fast-moving Thwaites, Pine Island, Land and DeVicq Glaciers to the slower-moving ice shelves. The average ice-front velocity during the time interval of Landsat imagery, for the faster-moving outlet glaciers, was 2.9 km a-1 for Thwaites Glacier, 2.4 km a-1 for Pine Island Glacier, 2.0 km a-1 for Land Glacier and 1.4 km a-1 for DeVicq Glacier. Evaluation of coastal change from the early 1970s to the early 1990s shows advance of the floating ice front in some coastal areas and recession in others, with an overall small average advance in the entire coastal study area, but no major trend towards advance or retreat. Comparison of average ice-surface velocities with changes in the ice front has yielded estimates of iceberg calving. The total iceberg calving from the Marie Byrd Land and Ellsworth Land coasts during the study period was greater than 8500 km2 (estimated volume of about 2400 km3) or an average of about 550 km2 a-1 (more than 150 km3 a-1). Almost 70% of this discharge is contributed by Thwaites and Pine Island Glaciers.

  8. Aerial radiation surveys

    SciTech Connect

    Jobst, J.

    1980-01-01

    A recent aerial radiation survey of the surroundings of the Vitro mill in Salt Lake City shows that uranium mill tailings have been removed to many locations outside their original boundary. To date, 52 remote sites have been discovered within a 100 square kilometer aerial survey perimeter surrounding the mill; 9 of these were discovered with the recent aerial survey map. Five additional sites, also discovered by aerial survey, contained uranium ore, milling equipment, or radioactive slag. Because of the success of this survey, plans are being made to extend the aerial survey program to other parts of the Salt Lake valley where diversions of Vitro tailings are also known to exist.

  9. The effects of war on land-use/land-cover change: An analysis of Landsat imagery for northeast Bosnia

    NASA Astrophysics Data System (ADS)

    Witmer, Frank D. W.

    The use of satellite technology by military planners has a relatively long history as a tool of warfare, but little research has used satellite technology to study the effects of war. This research addresses this gap by applying satellite remote sensing imagery to study the effects of war on land-use/land-cover change in northeast Bosnia. The war in Bosnia, 1992-1995, resulted in over 100,000 deaths, many more wounded, and the mass displacement of nearly half the population of 4.2 million. When combined with the destruction of much of the transportation infrastructure and housing stock, widespread mine placement, and loss of agricultural machinery, the impacts to both the people and land were dramatic. Though the most severe war impacts are visible at local scales (e.g. destroyed buildings), this study focuses on impacts to agricultural land, a larger scale visible to satellite sensors. Multispectral Landsat Thematic Mapper (TM) data (30m pixels) from before and during the war in addition to recent imagery from 2004/05 were used to detect abandoned agricultural land. The satellite images were co-registered to enable a perpixel analysis of changes based on the statistical properties of the pixels using multiple change detection methods. Ground reference data were collected in May of 2006 at survey sites selected using a stratified random sampling approach based on the derived map of abandoned agricultural land. Fine resolution (60cm) Quickbird imagery was also used to verify the accuracy of the classification. The remote sensing analysis results were then used to test two hypotheses related to war outcomes: (a) land abandonment is due to wartime minefields and (b) land abandonment is greater in pre-war Croat areas and areas where ethnic cleansing was heaviest. The effects of minefields on land abandonment was first tested in a geographic information system (GIS), and then by using multiple regression models that account for spatial autocorrelation among observations

  10. Korean coastal water depth/sediment and land cover mapping (1:25,000) by computer analysis of LANDSAT imagery

    NASA Technical Reports Server (NTRS)

    Park, K. Y.; Miller, L. D.

    1978-01-01

    Computer analysis was applied to single date LANDSAT MSS imagery of a sample coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map. Supervised image processing yielded a test classification map from this sample image containing 12 classes: 5 water depth/sediment classes, 2 shoreline/tidal classes, and 5 coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%. Unsupervised image classification was applied to a subportion of the site analyzed and produced classification maps comparable in results in a spatial sense. The results of this test indicated that it is feasible to produce such quantitative maps for detailed study of dynamic coastal processes given a LANDSAT image data base at sufficiently frequent time intervals.

  11. Building Information Modelling (BIM) and Unmanned Aerial Vehicle (UAV) technologies in infrastructure construction project management and delay and disruption analysis

    NASA Astrophysics Data System (ADS)

    Vacanas, Yiannis; Themistocleous, Kyriacos; Agapiou, Athos; Hadjimitsis, Diofantos

    2015-06-01

    Time in infrastructure construction projects has always been a fundamental issue as early as from the inception of a project, during the construction process and often after the completion and delivery. In a typical construction contract time related matters such as the completion date and possible delays are among the most important issues that are dealt with by the contract provisions. In the event of delay there are usually provisions for extension of time award to the contractor with possible reimbursement for the extra cost and expenses caused by this extension of time to the contract duration. In the case the contractor is not entitled to extension of time, the owner will be possibly entitled to amounts as compensation for the time prohibited from using his development. Even in the event of completion within the time agreed, under certain circumstances a contractor may have claims for reimbursement for extra costs incurred due to induced acceleration measures he had to take in order to mitigate disruption effects caused to the progress of the works by the owner or his representatives. Depending on the size of the project and the agreement amount, these reimbursement sums may be extremely high. Therefore innovative methods with the exploitation of new technologies for effective project management for the avoidance of delays, delay analysis and mitigation measures are essential; moreover, methods for collecting efficiently information during the construction process so that disputes regarding time are avoided or resolved in a quick and fair manner are required. This paper explores the state of art for existing use of Building Information Modelling (BIM) and Unmanned Aerial Vehicles (UAV) technologies in the construction industry in general. Moreover the paper considers the prospect of using BIM technology in conjunction with the use of UAV technology for efficient and accurate as-built data collection and illustration of the works progress during an

  12. Proceedings of the 2004 High Spatial Resolution Commercial Imagery Workshop

    NASA Technical Reports Server (NTRS)

    2006-01-01

    Topics covered include: NASA Applied Sciences Program; USGS Land Remote Sensing: Overview; QuickBird System Status and Product Overview; ORBIMAGE Overview; IKONOS 2004 Calibration and Validation Status; OrbView-3 Spatial Characterization; On-Orbit Modulation Transfer Function (MTF) Measurement of QuickBird; Spatial Resolution Characterization for QuickBird Image Products 2003-2004 Season; Image Quality Evaluation of QuickBird Super Resolution and Revisit of IKONOS: Civil and Commercial Application Project (CCAP); On-Orbit System MTF Measurement; QuickBird Post Launch Geopositional Characterization Update; OrbView-3 Geometric Calibration and Geopositional Accuracy; Geopositional Statistical Methods; QuickBird and OrbView-3 Geopositional Accuracy Assessment; Initial On-Orbit Spatial Resolution Characterization of OrbView-3 Panchromatic Images; Laboratory Measurement of Bidirectional Reflectance of Radiometric Tarps; Stennis Space Center Verification and Validation Capabilities; Joint Agency Commercial Imagery Evaluation (JACIE) Team; Adjacency Effects in High Resolution Imagery; Effect of Pulse Width vs. GSD on MTF Estimation; Camera and Sensor Calibration at the USGS; QuickBird Geometric Verification; Comparison of MODTRAN to Heritage-based Results in Vicarious Calibration at University of Arizona; Using Remotely Sensed Imagery to Determine Impervious Surface in Sioux Falls, South Dakota; Estimating Sub-Pixel Proportions of Sagebrush with a Regression Tree; How Do YOU Use the National Land Cover Dataset?; The National Map Hazards Data Distribution System; Recording a Troubled World; What Does This-Have to Do with This?; When Can a Picture Save a Thousand Homes?; InSAR Studies of Alaska Volcanoes; Earth Observing-1 (EO-1) Data Products; Improving Access to the USGS Aerial Film Collections: High Resolution Scanners; Improving Access to the USGS Aerial Film Collections: Phoenix Digitizing System Product Distribution; System and Product Characterization: Issues Approach

  13. Automatic Analysis and Classification of the Roof Surfaces for the Installation of Solar Panels Using a Multi-Data Source and Multi-Sensor Aerial Platform

    NASA Astrophysics Data System (ADS)

    López, L.; Lagüela, S.; Picon, I.; González-Aguilera, D.

    2015-02-01

    A low-cost multi-sensor aerial platform, aerial trike, equipped with visible and thermographic sensors is used for the acquisition of all the data needed for the automatic analysis and classification of roof surfaces regarding their suitability to harbour solar panels. The geometry of a georeferenced 3D point cloud generated from visible images using photogrammetric and computer vision algorithms, and the temperatures measured on thermographic images are decisive to evaluate the surfaces, slopes, orientations and the existence of obstacles. This way, large areas may be efficiently analysed obtaining as final result the optimal locations for the placement of solar panels as well as the required geometry of the supports for the installation of the panels in those roofs where geometry is not optimal.

  14. Crop identification and acreage measurement utilizing ERTS imagery

    NASA Technical Reports Server (NTRS)

    Vonsteen, D. H. (Principal Investigator)

    1972-01-01

    There are no author-identified significant results in this report. The microdensitometer will be used to analyze data acquired by ERTS-1 imagery. The classification programs and software packages have been acquired and are being prepared for use with the information as it is received. Photo and digital tapes have been acquired for coverage of virtually 100 percent of the test site areas. These areas are located in South Dakota, Idaho, Missouri, and Kansas. Hass 70mm color infrared, infrared, black and white high altitude aerial photography of the test sites is available. Collection of ground truth for updating the data base has been completed and a computer program written to count the number of fields and give total acres by size group for the segments in each test site. Results are given of data analysis performed on digitized data from densitometer measurements of fields of corn, sugar, beets, and alfalfa in Kansas.

  15. An augmentative gaze directing framework for multi-spectral imagery

    NASA Astrophysics Data System (ADS)

    Hsiao, Libby

    Modern digital imaging techniques have made the task of imaging more prolic than ever and the volume of images and data available through multi-spectral imaging methods for exploitation is exceeding that which can be solely processed by human beings. The researchers proposed and developed a novel eye movement contingent framework and display system through adaption of the demonstrated technique of subtle gaze direction by presenting modulations within the displayed image. The system sought to augment visual search task performance of aerial imagery by incorporating multi-spectral image processing algorithms to determine potential regions of interest within an image. The exploratory work conducted was to study the feasibility of visual gaze direction with the specic intent of extending this application to geospatial image analysis without need for overt cueing to areas of potential interest and thereby maintaining the benefits of an undirected and unbiased search by an observer.

  16. Structural geologic interpretations from radar imagery

    USGS Publications Warehouse

    Reeves, Robert G.

    1969-01-01

    Certain structural geologic features may be more readily recognized on sidelooking airborne radar (SLAR) images than on conventional aerial photographs, other remote sensor imagery, or by ground observations. SLAR systems look obliquely to one or both sides and their images resemble aerial photographs taken at low sun angle with the sun directly behind the camera. They differ from air photos in geometry, resolution, and information content. Radar operates at much lower frequencies than the human eye, camera, or infrared sensors, and thus "sees" differently. The lower frequency enables it to penetrate most clouds and some precipitation, haze, dust, and some vegetation. Radar provides its own illumination, which can be closely controlled in intensity and frequency. It is narrow band, or essentially monochromatic. Low relief and subdued features are accentuated when viewed from the proper direction. Runs over the same area in significantly different directions (more than 45° from each other), show that images taken in one direction may emphasize features that are not emphasized on those taken in the other direction; optimum direction is determined by those features which need to be emphasized for study purposes. Lineaments interpreted as faults stand out on radar imagery of central and western Nevada; folded sedimentary rocks cut by faults can be clearly seen on radar imagery of northern Alabama. In these areas, certain structural and stratigraphic features are more pronounced on radar images than on conventional photographs; thus radar imagery materially aids structural interpretation.

  17. The Potential Uses of Commercial Satellite Imagery in the Middle East

    SciTech Connect

    Vannoni, M.G.

    1999-06-08

    It became clear during the workshop that the applicability of commercial satellite imagery to the verification of future regional arms control agreements is limited at this time. Non-traditional security topics such as environmental protection, natural resource management, and the development of infrastructure offer the more promising applications for commercial satellite imagery in the short-term. Many problems and opportunities in these topics are regional, or at least multilateral, in nature. A further advantage is that, unlike arms control and nonproliferation applications, cooperative use of imagery in these topics can be done independently of the formal Middle East Peace Process. The value of commercial satellite imagery to regional arms control and nonproliferation, however, will increase during the next three years as new, more capable satellite systems are launched. Aerial imagery, such as that used in the Open Skies Treaty, can also make significant contributions to both traditional and non-traditional security applications but has the disadvantage of requiring access to national airspace and potentially higher cost. There was general consensus that commercial satellite imagery is under-utilized in the Middle East and resources for remote sensing, both human and institutional, are limited. This relative scarcity, however, provides a natural motivation for collaboration in non-traditional security topics. Collaborations between scientists, businesses, universities, and non-governmental organizations can work at the grass-roots level and yield contributions to confidence building as well as scientific and economic results. Joint analysis projects would benefit the region as well as establish precedents for cooperation.

  18. Hierarchical Object-based Image Analysis approach for classification of sub-meter multispectral imagery in Tanzania

    NASA Astrophysics Data System (ADS)

    Chung, C.; Nagol, J. R.; Tao, X.; Anand, A.; Dempewolf, J.

    2015-12-01

    Increasing agricultural production while at the same time preserving the environment has become a challenging task. There is a need for new approaches for use of multi-scale and multi-source remote sensing data as well as ground based measurements for mapping and monitoring crop and ecosystem state to support decision making by governmental and non-governmental organizations for sustainable agricultural development. High resolution sub-meter imagery plays an important role in such an integrative framework of landscape monitoring. It helps link the ground based data to more easily available coarser resolution data, facilitating calibration and validation of derived remote sensing products. Here we present a hierarchical Object Based Image Analysis (OBIA) approach to classify sub-meter imagery. The primary reason for choosing OBIA is to accommodate pixel sizes smaller than the object or class of interest. Especially in non-homogeneous savannah regions of Tanzania, this is an important concern and the traditional pixel based spectral signature approach often fails. Ortho-rectified, calibrated, pan sharpened 0.5 meter resolution data acquired from DigitalGlobe's WorldView-2 satellite sensor was used for this purpose. Multi-scale hierarchical segmentation was performed using multi-resolution segmentation approach to facilitate the use of texture, neighborhood context, and the relationship between super and sub objects for training and classification. eCognition, a commonly used OBIA software program, was used for this purpose. Both decision tree and random forest approaches for classification were tested. The Kappa index agreement for both algorithms surpassed the 85%. The results demonstrate that using hierarchical OBIA can effectively and accurately discriminate classes at even LCCS-3 legend.

  19. Multi-Temporal Land Use Analysis of AN Ephemeral River Area Using AN Artificial Neural Network Approach on Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Aquilino, M.; Tarantino, E.; Fratino, U.

    2013-01-01

    This paper proposes a change detection analysis method based on multitemporal LANDSAT satellite data, presenting a study performed on the Lama San Giorgio (Bari, Italy) river basin area. Based on its geological and hydrological characteristics, as well as on the number of recent and remote flooding events already occurred, this area seems to be naturally prone to flooding. The historical archive of LANDSAT imagery dating back to the launch of ERTS in 1972 provides a comprehensive and permanent data source for tracking change on the planet‟s land surface. In this study case the imagery acquisition dates of 1987, 2002 and 2011 were selected to cover a time trend of 24 years. Land cover categories were based on classes outlined by the Curve Number method with the aim of characterizing land use according to the level of surface imperviousness. After comparing two land use classification methods, i.e. Maximum Likelihood Classifier (MLC) and Multi-Layer Perceptron (MLP) neural network, the Artificial Neural Networks (ANN) approach was found the best reliable and efficient method in the absence of ground reference data. The ANN approach has a distinct advantage over statistical classification methods in that it is non-parametric and requires little or no a priori knowledge on the distribution model of input data. The results quantify land cover change patterns in the river basin area under study and demonstrate the potential of multitemporal LANDSAT data to provide an accurate and cost-effective means to map and analyse land cover changes over time that can be used as input in land management and policy decision-making.

  20. Geological analysis and evaluation of ERTS-A imagery for the state of New Mexico

    NASA Technical Reports Server (NTRS)

    Kottlowski, F. E. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. Coverage of approximately one-third of the test site had been received by January 31, 1973 and all of the images received were MSS products. Images recorded during the first two months of the ERTS-1 mission were of poor quality, owing largely to high ground reflectance. Later images were of better quality and MSS bands 5 and 7 have proven to be particularly useful. Features noted during visual inspection of 9 1/2 x 9 1/2 prints include major structural forms, vegetation patterns, drainage patterns, and outcrops of geologic formations having marked color contrasts. The Border Hills Structural Zone and the Y-O Structural Zone are prominently reflected in coverage of the Pecos Valley. A study of available maps and remote sensing material covering the Deming-Columbus area indicated that the limit of detection and the resolution of MSS products are not as good as those of aerial photographs, geologic maps, and manned satellite photographs. The limit of detection of high contrast features on MSS prints is approximately 1000 feet or 300 meters for linear features and about 18 acres for roughly circular areas.

  1. Quality Analysis on 3d Buidling Models Reconstructed from Uav Imagery

    NASA Astrophysics Data System (ADS)

    Jarzabek-Rychard, M.; Karpina, M.

    2016-06-01

    Recent developments in UAV technology and structure from motion techniques have effected that UAVs are becoming standard platforms for 3D data collection. Because of their flexibility and ability to reach inaccessible urban parts, drones appear as optimal solution for urban applications. Building reconstruction from the data collected with UAV has the important potential to reduce labour cost for fast update of already reconstructed 3D cities. However, especially for updating of existing scenes derived from different sensors (e.g. airborne laser scanning), a proper quality assessment is necessary. The objective of this paper is thus to evaluate the potential of UAV imagery as an information source for automatic 3D building modeling at LOD2. The investigation process is conducted threefold: (1) comparing generated SfM point cloud to ALS data; (2) computing internal consistency measures of the reconstruction process; (3) analysing the deviation of Check Points identified on building roofs and measured with a tacheometer. In order to gain deep insight in the modeling performance, various quality indicators are computed and analysed. The assessment performed according to the ground truth shows that the building models acquired with UAV-photogrammetry have the accuracy of less than 18 cm for the plannimetric position and about 15 cm for the height component.

  2. Analysis of ERTS-1 imagery and its application to evaluation of Wyoming's natural resources

    NASA Technical Reports Server (NTRS)

    Marrs, R. W.

    1973-01-01

    The author has identified the following significant results. A summary of the significant results of the studies completed during the July-August, 1973 period includes: (1) ERTS-1 image brightness contrasts can be related to important contrasts in rangeland and forest vegetation communities of the Laramie Basin. (2) Stereoscopic viewing is essential for correct structural interpretation in outcrop patterns in some areas. (3) Complex fracture patterns which may have exerted a controlling influence on intrusive activity in the Absaroka Mountains can be mapped from ERTS. (4) Volcanic lithologies of the Yellowstone region are often differentiated on the basis of their textures, and cannot be successfully mapped by photogeologic interpretation of ERTS-1 imagery. Ground spectral readings confirm a general lack of contrast between these lithologies in the four ERTS-1 MSS bands. (5) Major dune fields can be recognized and defined from ERTS-1 image interpretations and recognition of differences in stabilizing plant communities (some of which may be mappable from ERTS-1) yields information about migration history of the dune fields.

  3. Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery.

    PubMed

    Li, Jing; Zipper, Carl E; Donovan, Patricia F; Wynne, Randolph H; Oliphant, Adam J

    2015-09-01

    Surface mining disturbances have attracted attention globally due to extensive influence on topography, land use, ecosystems, and human populations in mineral-rich regions. We analyzed a time series of Landsat satellite imagery to produce a 28-year disturbance history for surface coal mining in a segment of eastern USA's central Appalachian coalfield, southwestern Virginia. The method was developed and applied as a three-step sequence: vegetation index selection, persistent vegetation identification, and mined-land delineation by year of disturbance. The overall classification accuracy and kappa coefficient were 0.9350 and 0.9252, respectively. Most surface coal mines were identified correctly by location and by time of initial disturbance. More than 8 % of southwestern Virginia's >4000-km(2) coalfield area was disturbed by surface coal mining over the 28-year period. Approximately 19.5 % of the Appalachian coalfield surface within the most intensively mined county (Wise County) has been disturbed by mining. Mining disturbances expanded steadily and progressively over the study period. Information generated can be applied to gain further insight concerning mining influences on ecosystems and other essential environmental features.

  4. Analysis of Coastal Sediment Plume Dynamics in Puerto Rico using MODIS/Terra 250-m Imagery

    NASA Astrophysics Data System (ADS)

    Otis, D. B.; Muller-Karger, F. E.; Mendez-Lazaro, P.; McCarthy, M.; Chen, F. R.

    2014-12-01

    Anomalous events of suspended sediments can degrade water quality in nearshore ecosystems by reducing light penetration, inhibiting primary production, and delivering pollutants associated with the sediment particles. Coral reefs, for example, are subject to stress by anomalous sediment loads. The island of Puerto Rico has a diverse topography, with steep mountain slopes, episodic high-intensity rainfall events, and weathered soils that lead to episodes of high sediment volumes being delivered to the coastal zone by rivers. We developed a time series of turbidity observations based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for use in the coastal areas of Puerto Rico. The product uses remote-sensing reflectance (Rrs) of Band 1 (645 nm) at a spatial resolution of 250 m. These estimates were compared to in-situ turbidity measurements collected in San Juan Bay. Sediment plumes from the major rivers of Puerto Rico were assessed quantitatively and compared with time-series of meteorological and other parameters, including precipitation, river discharge, and wind velocity. The spatial extent of plumes, the timing and duration of plume events, and their potential impact on coral reefs are examined. Results show that plume events are episodic and short-lived, but that they may affect coral reefs located several kilometers offshore.

  5. Chosen Aspects of the Production of the Basic Map Using Uav Imagery

    NASA Astrophysics Data System (ADS)

    Kedzierski, M.; Fryskowska, A.; Wierzbicki, D.; Nerc, P.

    2016-06-01

    For several years there has been an increasing interest in the use of unmanned aerial vehicles in acquiring image data from a low altitude. Considering the cost-effectiveness of the flight time of UAVs vs. conventional airplanes, the use of the former is advantageous when generating large scale accurate ortophotos. Through the development of UAV imagery, we can update large-scale basic maps. These maps are cartographic products which are used for registration, economic, and strategic planning. On the basis of these maps other cartographic maps are produced, for example maps used building planning. The article presents an assessesment of the usefulness of orthophotos based on UAV imagery to upgrade the basic map. In the research a compact, non-metric camera, mounted on a fixed wing powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. The processing and analysis of orthorectification were carried out with the INPHO UASMaster programme. Due to the effect of UAV instability on low-altitude imagery, the use of non-metric digital cameras and the low-accuracy GPS-INS sensors, the geometry of images is visibly lower were compared to conventional digital aerial photos (large values of phi and kappa angles). Therefore, typically, low-altitude images require large along- and across-track direction overlap - usually above 70 %. As a result of the research orthoimages were obtained with a resolution of 0.06 meters and a horizontal accuracy of 0.10m. Digitized basic maps were used as the reference data. The accuracy of orthoimages vs. basic maps was estimated based on the study and on the available reference sources. As a result, it was found that the geometric accuracy and interpretative advantages of the final orthoimages allow the updating of basic maps. It is estimated that such an update of basic maps based on UAV imagery reduces processing time by approx. 40%.

  6. Searching for hidden houses: optical satellite imagery in archaeological prospection of the early Neolithic settlements in the Kujawy region, Poland

    NASA Astrophysics Data System (ADS)

    RÄ czkowski, Włodzimierz; Rucinski, Dominik

    2015-06-01

    Archaeologists have been applying remote sensing methods for over hundred years. New technological opportunities still appear and they may offer new data on remains from the Past. Effectiveness of remote sensing methods differs at scales. Aerial photographs play very important role at the regional scale of prospection. The question appears on usefulness of optical satellite imagery in the field dominated by aerial photography until now. Survey based on aerial recording of early farming settlements in Central Europe proofs the value and effectiveness of the method in this field. On the other hand whilst analyzing aerial photographs one might doubt about a spatial structure of the settlement, whether the whole space of the settlement has been recorded or not. Most of traces of houses can be recognized as cropmarks, however it applies only to specific geomorphological structures. It raises the question: did people in the past select those specific geomorphological structures for settling or whether existing soil and geomorphological conditions mask archaeological traces? An attempt to recognize the impact of local soils and geomorphological conditions on a possibility of identification of archaeological features is one of the tasks in the project ArchEO - archaeological applications of Earth Observation techniques. In the vicinity of Kaczkowo village in Kujawy Region (Poland) a cluster of traces of the early Neolithic farmers is located. This area has been a subject of aerial survey for several years. Yet the question on a completeness of recognition of the settlement pattern is still open. In the project we attempt to assess to what extent optical satellite imagery and a wide range of processing techniques (vegetation indices, color composites, spectral transformations, edge detection etc.) might allow an identification of the remains of settlements, especially in the neighborhood of already known clusters of Neolithic houses. It might help in defining the range of

  7. Auditory Imagery: Empirical Findings

    ERIC Educational Resources Information Center

    Hubbard, Timothy L.

    2010-01-01

    The empirical literature on auditory imagery is reviewed. Data on (a) imagery for auditory features (pitch, timbre, loudness), (b) imagery for complex nonverbal auditory stimuli (musical contour, melody, harmony, tempo, notational audiation, environmental sounds), (c) imagery for verbal stimuli (speech, text, in dreams, interior monologue), (d)…

  8. 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.

  9. Active, passive, and motor imagery paradigms: component analysis to assess neurovascular coupling.

    PubMed

    Salinet, Angela S M; Robinson, Thompson G; Panerai, Ronney B

    2013-05-15

    The association between neural activity and cerebral blood flow (CBF) has been used to assess neurovascular coupling (NVC) in health and diseases states, but little attention has been given to the contribution of simultaneous changes in peripheral covariates. We used an innovative approach to assess the contributions of arterial blood pressure (BP), PaCO2, and the stimulus itself to changes in CBF velocities (CBFv) during active (MA), passive (MP), and motor imagery (MI) paradigms. Continuous recordings of CBFv, beat-to-beat BP, heart rate, and breath-by-breath end-tidal CO2 (EtCO2) were performed in 17 right-handed subjects before, during, and after motor-cognitive paradigms performed with the right arm. A multivariate autoregressive-moving average model was used to calculate the separate contributions of BP, EtCO2, and the neural activation stimulus (represented by a metronome on-off signal) to the CBFv response during paradigms. Differences were found in the bilateral CBFv responses to MI compared with MA and MP, due to the contributions of stimulation (P < 0.05). BP was the dominant contributor to the initial peaked CBFv response in all paradigms with no significant differences between paradigms, while the contribution of the stimulus explained the plateau phase and extended duration of the CBFv responses. Separating the neural activation contribution from the influences of other covariates, it was possible to detect differences between three paradigms often used to assess disease-related NVC. Apparently similar CBFv responses to different motor-cognitive paradigms can be misleading due to the contributions from peripheral covariates and could lead to inaccurate assessment of NVC, particularly during MI.

  10. Comparison Analysis: Granger Causality and New Causality and Their Applications to Motor Imagery.

    PubMed

    Hu, Sanqing; Wang, Hui; Zhang, Jianhai; Kong, Wanzeng; Cao, Yu; Kozma, Robert

    2016-07-01

    In this paper we first point out a fatal drawback that the widely used Granger causality (GC) needs to estimate the autoregressive model, which is equivalent to taking a series of backward recursive operations which are infeasible in many irreversible chemical reaction models. Thus, new causality (NC) proposed by Hu et al. (2011) is theoretically shown to be more sensitive to reveal true causality than GC. We then apply GC and NC to motor imagery (MI) which is an important mental process in cognitive neuroscience and psychology and has received growing attention for a long time. We study causality flow during MI using scalp electroencephalograms from nine subjects in Brain-computer interface competition IV held in 2008. We are interested in three regions: Cz (central area of the cerebral cortex), C3 (left area of the cerebral cortex), and C4 (right area of the cerebral cortex) which are considered to be optimal locations for recognizing MI states in the literature. Our results show that: 1) there is strong directional connectivity from Cz to C3/C4 during left- and right-hand MIs based on GC and NC; 2) during left-hand MI, there is directional connectivity from C4 to C3 based on GC and NC; 3) during right-hand MI, there is strong directional connectivity from C3 to C4 which is much clearly revealed by NC than by GC, i.e., NC largely improves the classification rate; and 4) NC is demonstrated to be much more sensitive to reveal causal influence between different brain regions than GC.

  11. Geobotanical and lineament analysis of sandsat satellite imagery for hydrocarbon microseeps

    SciTech Connect

    Warner, T.A.

    1997-10-01

    Both geobotanical and structural interpretations of remotely sensed data tend to be plagued by random associations. However, a combination of these methods has the potential to provide a methodology for excluding many false associations. To test this approach, a test site in West Virginia has been studied using remotely sensed and field data. The historic Volcano Oil Field, in Wood, Pleasants and Ritchie Counties was known as an area of hydrocarbon seeps in the last century. Although pressures in the reservoir are much reduced today, hydrocarbons remain in the reservoir. An examination of a multi-seasonal Landsat Thematic Mapper imagery has shown little difference between the forests overlying the hydrocarbon reservoirs compared to the background areas, with the exception of an image in the very early fall. This image has been enhanced using an nPDF spectral transformation that maximizes the contrast between the anomalous and background areas. A field survey of soil gas chemistry showed that hydrocarbon concentration is generally higher over the anomalous region. In addition, soil gas hydrocarbon concentration increases with proximity to linear features that cross the strike of the overall structure of the reservoir. Linear features that parallel the strike, however, do not have any discernible influence on gas concentration. Field spectral measurements were made periodically through the summer and early fall to investigate the origin of the spectral reflectance anomaly. Measurements were made with a full-range spectro-radiometer (400 nm to 2500 nm) on a number of different species, both on and off the spectral anomaly. The results lend support to the finding that in the early fall spectral reflectance increases in the near infrared and mid infrared in the spectrally anomalous regions.

  12. Aerial imagery and structure-from-motion based DEM reconstruction of region-sized areas (Sierra Arana, Spain and Namur Province, Belgium) using an high-altitude drifting balloon platform.

    NASA Astrophysics Data System (ADS)

    Burlet, Christian; María Mateos, Rosa; Azañón, Jose Miguel; Perez, José Vicente; Vanbrabant, Yves

    2015-04-01

    different elevations. A 1m/pixel ground resolution set covering an area of about 200km² and mapping the eastern part of the Sierra Arana (Andalucía, Spain) includes a kartsic field directly to the south-east of the ridge and the cliffs of the "Riscos del Moro". A 4m/pixel ground resolution set covering an area of about 900km² includes the landslide active Diezma region (Andalucía, Spain) and the water reserve of Francisco Abellan lake. The third set has a 3m/pixel ground resolution, covers about 100km² and maps the Famennian rocks formations, known as part of "La Calestienne", outcropping near Beauraing and Rochefort in the Namur Province (Belgium). The DEM and orthophoto's have been referenced using ground control points from satellite imagery (Spain, Belgium) and DPGS (Belgium). The quality of produced DEM were then evaluated by comparing the level and accuracy of details and surface artefacts between available topographic data (SRTM- 30m/pixel, topographic maps) and the three Stratochip sets. This evaluation showed that the models were in good correlation with existing data, and can be readily be used in geomorphology, structural and natural hazard studies.

  13. 11. Photocopy of aerial photograph (original aerial located in the ...

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

    11. Photocopy of aerial photograph (original aerial located in the U.S. Forest Service, Toiyabe National Forest, Carson District Office). AERIAL VIEW OF THE GENOA PEAK ROAD, SPUR. - Genoa Peak Road, Spur, Glenbrook, Douglas County, NV

  14. Hyperspectral imagery and segmentation

    NASA Astrophysics Data System (ADS)

    Wellman, Mark C.; Nasrabadi, Nasser M.

    2002-07-01

    Hyperspectral imagery (HSI), a passive infrared imaging technique which creates images of fine resolution across the spectrum is currently being considered for Army tactical applications. An important tactical application of infra-red (IR) hyperspectral imagery is the detection of low contrast targets, including those targets that may employ camouflage, concealment and deception (CCD) techniques [1,2]. Spectral reflectivity characteristics were used for efficient segmentation between different materials such as painted metal, vegetation and soil for visible to near IR bands in the range of 0.46-1.0 microns as shown previously by Kwon et al [3]. We are currently investigating the HSI where the wavelength spans from 7.5-13.7 microns. The energy in this range of wavelengths is almost entirely emitted rather than reflected, therefore, the gray level of a pixel is a function of the temperature and emissivity of the object. This is beneficial since light level and reflection will not need to be considered in the segmentation. We will present results of a step-wise segmentation analysis on the long-wave infrared (LWIR) hyperspectrum utilizing various classifier architectures applied to both the full-band, broad-band and narrow-band features derived from the Spatially Enhanced Broadband Array Spectrograph System (SEBASS) data base. Stepwise segmentation demonstrates some of the difficulties in the multi-class case. These results give an indication of the added capability the hyperspectral imagery and associated algorithms will bring to bear on the target acquisition problem.

  15. Environmental application of aerial reconnaissance to search for open dumps

    NASA Astrophysics Data System (ADS)

    Getz, Thomas J.; Randolph, J. C.; Echelberger, Wayne F.

    1983-11-01

    Three approaches to using aerial photography are evaluated for searching for open dumps in the state of Indiana. Photography with hand-held cameras from a small airplane proved more effective and flexible than either photo-interpretation of existing air photos or subcontracting to a federal agency for new aerial photography. The rationale for our choice of aerial reconnaissance, other uses of low-level aerial surveillance, the utility of small-format camera aerial photography for environmental analysis, and methods used for locating open dumps are discussed.

  16. Burn severity estimation using GeoEye imagery, object-based image analysis (OBIA), and Composite Burn Index (CBI) measurements

    NASA Astrophysics Data System (ADS)

    Dragozi, E.; Gitas, Ioannis Z.; Stavrakoudis, Dimitris G.; Minakou, C.

    2015-06-01

    Forest fires greatly influence the stability and functions of the forest ecosystems. The ever increasing need for accurate and detailed information regarding post-fire effects (burn severity) has led to several studies on the matter. In this study the combined use of Very High Resolution (VHR) satellite data (GeoEye), Objectbased image analysis (OBIA) and Composite Burn Index (CBI) measurements in estimating burn severity, at two different time points (2011 and 2012) is assessed. The accuracy of the produced maps was assessed and changes in burn severity between the two dates were detected using the post classification comparison approach. It was found that the produced burn severity map for 2011 was approximately 10% more accurate than that of 2012. This was mainly attributed to the increased heterogeneity of the study area in the second year, which led to an increased number of mixed class objects and consequently made it more difficult to spectrally discriminate between the severity classes. Following the post-classification analysis, the severity class changes were mainly attributed to the trees' ability to survive severe fire damage and sprout new leaves. Moreover, the results of the study suggest that when classifying CBI-based burn severity using VHR imagery it would be preferable to use images captured soon after the fire.

  17. Use of satellite radiometric imagery data for improvement in the analysis of divergent wind in the tropics

    NASA Technical Reports Server (NTRS)

    Kasahara, Akira; Balgovind, Ramesh C.; Katz, Bert B.

    1988-01-01

    A scheme is proposed to incorporate satellite radiometric imagery data into the specification of initial conditions for the National Meteorological Center (NMC) operational global prediction model in order to improve the analysis of the divergent wind field in the tropics. The basic assumptions are that outgoing longwave radiation (OLR) data can provide 1) the division between convective (upward motion) and clear sky (downward motion) areas, and 2) the height of convection cells. The intensity of ascending motion in the convective areas is estimated based on OLR data. The intensity of descending motion is evaluated from the thermodynamic energy balance between radiative cooling and adiabatic warming, since the local time change of temperature is small in the tropics. Once the vertical motion field is determined, the horizontal divergence field can be calculated from the mass continuity equation. Then a divergent wind field is determined. The total wind is the sum of the new divergent wind and the rotational part, which is assumed to be unchanged. The proposed scheme is tested using the NMC analysis dataset of 21 January 1985 with satisfactory results.

  18. Remote sensing for precision agriculture: Within-field spatial variability analysis and mapping with aerial digital multispectral images

    NASA Astrophysics Data System (ADS)

    Gopalapillai, Sreekala

    2000-10-01

    Advances in remote sensing technology and biological sensors provided the motivation for this study on the applications of aerial multispectral remote sensing in precision agriculture. The feasibility of using high-resolution multispectral remote sensing for precision farming applications such as soil type delineation, identification of crop nitrogen levels, and modeling and mapping of weed density distribution and yield potential within a crop field was explored in this study. Some of the issues such as image calibration for variable lighting conditions and soil background influence were also addressed. Intensity normalization and band ratio methods were found to be adequate image calibration methods to compensate for variable illumination and soil background influence. Several within-field variability factors such as growth stage, field conditions, nutrient availability, crop cultivar, and plant population were found to be dominant in different periods. Unsupervised clustering of color infrared (CIR) image of a field soil was able to identify soil mapping units with an average accuracy of 76%. Spectral reflectance from a crop field was highly correlated to the chlorophyll reading. A regression model developed to predict nitrogen stress in corn identified nitrogen-stressed areas from nitrogen-sufficient areas with a high accuracy (R2 = 0.93). Weed density was highly correlated to the spectral reflectance from a field. One month after planting was found to be a good time to map spatial weed density. The optimum range of resolution for weed mapping was 4 m to 4.5 m for the remote sensing system and the experimental field used in this study. Analysis of spatial yield with respect to spectral reflectance showed that the visible and NIR reflectance were negatively correlated to yield and crop population in heavily weed-infested areas. The yield potential was highly correlated to image indices, especially to normalized brightness. The ANN model developed for one of the

  19. Meteoroid and debris special investigation group; status of 3-D crater analysis from binocular imagery

    NASA Technical Reports Server (NTRS)

    Sapp, Clyde A.; See, Thomas H.; Zolensky, Michael E.

    1992-01-01

    During the 3 month deintegration of the LDEF, the M&D SIG generated approximately 5000 digital color stereo image pairs of impact related features from all space exposed surfaces. Currently, these images are being processed at JSC to yield more accurate feature information. Work is currently underway to determine the minimum number of data points necessary to parametrically define impact crater morphologies in order to minimize the man-hour intensive task of tie point selection. Initial attempts at deriving accurate crater depth and diameter measurements from binocular imagery were based on the assumption that the crater geometries were best defined by paraboloid. We made no assumptions regarding the crater depth/diameter ratios but instead allowed each crater to define its own coefficients by performing a least-squares fit based on user-selected tiepoints. Initial test cases resulted in larger errors than desired, so it was decided to test our basic assumptions that the crater geometries could be parametrically defined as paraboloids. The method for testing this assumption was to carefully slice test craters (experimentally produced in an appropriate aluminum alloy) vertically through the center resulting in a readily visible cross-section of the crater geometry. Initially, five separate craters were cross-sectioned in this fashion. A digital image of each cross-section was then created, and the 2-D crater geometry was then hand-digitized to create a table of XY position for each crater. A 2nd order polynomial (parabolic) was fitted to the data using a least-squares approach. The differences between the fit equation and the actual data were fairly significant, and easily large enough to account for the errors found in the 3-D fits. The differences between the curve fit and the actual data were consistent between the caters. This consistency suggested that the differences were due to the fact that a parabola did not sufficiently define the generic crater geometry

  20. Analysis of Seasat orbital radar imagery for geologic mapping in the appalachian Valley and Ridge province, Tennessee-Kentucky-Virginia

    NASA Technical Reports Server (NTRS)

    Ford, J. P.

    1980-01-01

    The terrain-surface features of the Appalachian Valley and Ridge province were analyzed using Seasat synthetic aperture radar imagery. Particular attention was given to determining the efficiency and capability of this microwave imaging system for geologic mapping.

  1. Evaluation of ERTS-1 imagery in mapping and managing soil and range resources in the Sand Hills Region of Nebraska

    NASA Technical Reports Server (NTRS)

    Seevers, P. M.; Drew, J. V.

    1973-01-01

    Interpretations of high altitude photography of test sites in the Sandhills of Nebraska permitted identification of subirrigated range sites as well as complexes of choppy sands and sands range sites, units composing approximately 85% of the Sandhills rangeland. These range sites form the basic units necessary for the interpretation of range condition classes used in grazing management. Analysis of ERTS-1 imagery acquired during August, September and October, 1972 indicated potential for the identification of gross differences in forage density within given range sites identified on early season aerial photography.

  2. 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.

  3. Aerial photographic reproductions

    USGS Publications Warehouse

    ,

    1975-01-01

    The National Cartographic Information Center of the U.S. Geological Survey maintains records of aerial photographic coverage of the United States and its Territories, based on reports from other Federal agencies as well as State governmental agencies and commercial companies. From these records, the Center furnishes data to prospective purchasers on available photography and the agency holding the aerial film.

  4. Unmanned aerial systems for forest reclamation monitoring: throwing balloons in the air

    NASA Astrophysics Data System (ADS)

    Andrade, Rita; Vaz, Eric; Panagopoulos, Thomas; Guerrero, Carlos

    2014-05-01

    Wildfires are a recurrent phenomenon in Mediterranean landscapes, deteriorating environment and ecosystems, calling out for adequate land management. Monitoring burned areas enhances our abilities to reclaim them. Remote sensing has become an increasingly important tool for environmental assessment and land management. It is fast, non-intrusive, and provides continuous spatial coverage. This paper reviews remote sensing methods, based on space-borne, airborne or ground-based multispectral imagery, for monitoring the biophysical properties of forest areas for site specific management. The usage of satellite imagery for land use management has been frequent in the last decades, it is of great use to determine plants health and crop conditions, allowing a synergy between the complexity of environment, anthropogenic landscapes and multi-temporal understanding of spatial dynamics. Aerial photography increments on spatial resolution, nevertheless it is heavily dependent on airborne availability as well as cost. Both these methods are required for wide areas management and policy planning. Comprising an active and high resolution imagery source, that can be brought at a specific instance, reducing cost while maintaining locational flexibility is of utmost importance for local management. In this sense, unmanned aerial vehicles provide maximum flexibility with image collection, they can incorporate thermal and multispectral sensors, however payload and engine operation time limit flight time. Balloon remote sensing is becoming increasingly sought after for site specific management, catering rapid digital analysis, permitting greater control of the spatial resolution as well as of datasets collection in a given time. Different wavelength sensors may be used to map spectral variations in plant growth, monitor water and nutrient stress, assess yield and plant vitality during different stages of development. Proximity could be an asset when monitoring forest plants vitality

  5. Review of the SAFARI 2000 RC-10 Aerial Photography

    NASA Technical Reports Server (NTRS)

    Myers, Jeff; Shelton, Gary; Annegarn, Harrold; Peterson, David L. (Technical Monitor)

    2001-01-01

    This presentation will review the aerial photography collected by the NASA ER-2 aircraft during the SAFARI (Southern African Regional Science Initiative) year 2000 campaign. It will include specifications on the camera and film, and will show examples of the imagery. It will also detail the extent of coverage, and the procedures to obtain film products from the South African government. Also included will be some sample applications of aerial photography for various environmental applications, and its use in augmenting other SAFARI data sets.

  6. Fusion of LIDAR Data and Multispectral Imagery for Effective Building Detection Based on Graph and Connected Component Analysis

    NASA Astrophysics Data System (ADS)

    Gilani, S. A. N.; Awrangjeb, M.; Lu, G.

    2015-03-01

    Building detection in complex scenes is a non-trivial exercise due to building shape variability, irregular terrain, shadows, and occlusion by highly dense vegetation. In this research, we present a graph based algorithm, which combines multispectral imagery and airborne LiDAR information to completely delineate the building boundaries in urban and densely vegetated area. In the first phase, LiDAR data is divided into two groups: ground and non-ground data, using ground height from a bare-earth DEM. A mask, known as the primary building mask, is generated from the non-ground LiDAR points where the black region represents the elevated area (buildings and trees), while the white region describes the ground (earth). The second phase begins with the process of Connected Component Analysis (CCA) where the number of objects present in the test scene are identified followed by initial boundary detection and labelling. Additionally, a graph from the connected components is generated, where each black pixel corresponds to a node. An edge of a unit distance is defined between a black pixel and a neighbouring black pixel, if any. An edge does not exist from a black pixel to a neighbouring white pixel, if any. This phenomenon produces a disconnected components graph, where each component represents a prospective building or a dense vegetation (a contiguous block of black pixels from the primary mask). In the third phase, a clustering process clusters the segmented lines, extracted from multispectral imagery, around the graph components, if possible. In the fourth step, NDVI, image entropy, and LiDAR data are utilised to discriminate between vegetation, buildings, and isolated building's occluded parts. Finally, the initially extracted building boundary is extended pixel-wise using NDVI, entropy, and LiDAR data to completely delineate the building and to maximise the boundary reach towards building edges. The proposed technique is evaluated using two Australian data sets

  7. Optimal Band Ratio Analysis of WORLDVIEW-3 Imagery for Bathymetry of Shallow Rivers (case Study: Sarca River, Italy)

    NASA Astrophysics Data System (ADS)

    Niroumand-Jadidi, M.; Vitti, A.

    2016-06-01

    The Optimal Band Ratio Analysis (OBRA) could be considered as an efficient technique for bathymetry from optical imagery due to its robustness on substrate variability. This point receives more attention for very shallow rivers where different substrate types can contribute remarkably into total at-sensor radiance. The OBRA examines the total possible pairs of spectral bands in order to identify the optimal two-band ratio that its log transformation yields a strong linear relation with field measured water depths. This paper aims at investigating the effectiveness of additional spectral bands of newly launched WorldView-3 (WV-3) imagery in the visible and NIR spectrum through OBRA for retrieving water depths in shallow rivers. In this regard, the OBRA is performed on a WV-3 image as well as a GeoEye image of a small Alpine river in Italy. In-situ depths are gathered in two river reaches using a precise GPS device. In each testing scenario, 50% of the field data is used for calibration of the model and the remained as independent check points for accuracy assessment. In general, the effect of changes in water depth is highly pronounced in longer wavelengths (i.e. NIR) due to high and rapid absorption of light in this spectrum as long as it is not saturated. As the studied river is shallow, NIR portion of the spectrum has not been reduced so much not to reach the riverbed; making use of the observed radiance over this spectral range as denominator has shown a strong correlation through OBRA. More specifically, tightly focused channels of red-edge, NIR-1 and NIR-2 provide a wealth of choices for OBRA rather than a single NIR band of conventional 4-band images (e.g. GeoEye). This advantage of WV-3 images is outstanding as well for choosing the optimal numerator of the ratio model. Coastal-blue and yellow bands of WV-3 are identified as proper numerators while only green band of the GeoEye image contributed to a reliable correlation of image derived values and field

  8. Aerial robotic data acquisition system

    SciTech Connect

    Hofstetter, K.J.; Hayes, D.W.; Pendergast, M.M.; Corban, J.E.

    1993-12-31

    A small, unmanned aerial vehicle (UAV), equipped with sensors for physical and chemical measurements of remote environments, is described. A miniature helicopter airframe is used as a platform for sensor testing and development. The sensor output is integrated with the flight control system for real-time, interactive, data acquisition and analysis. Pre-programmed flight missions will be flown with several sensors to demonstrate the cost-effective surveillance capabilities of this new technology.

  9. Geomatics techniques applied to time series of aerial images for multitemporal geomorphological analysis of the Miage Glacier (Mont Blanc).

    NASA Astrophysics Data System (ADS)

    Perotti, Luigi; Carletti, Roberto; Giardino, Marco; Mortara, Giovanni

    2010-05-01

    The Miage glacier is the major one in the Italian side of the Mont Blanc Massif, the third by area and the first by longitudinal extent among Italian glaciers. It is a typical debris covered glacier, since the end of the L.I.A. The debris coverage reduces ablation, allowing a relative stability of the glacier terminus, which is characterized by a wide and articulated moraine apparatus. For its conservative landforms, the Miage Glacier has a great importance for the analysis of the geomorphological response to recent climatic changes. Thanks to an organized existing archive of multitemporal aerial images (1935 to present) a photogrammetric approach has been applied to detect recent geomorphological changes in the Miage glacial basin. The research team provided: a) to digitize all the available images (still in analogic form) through photogrammetric scanners (very low image distortions devices) taking care of correctly defining the resolution of the acquisition compared to the scale mapping images are suitable for; b) to import digitized images into an appropriate digital photogrammetry software environment; c) to manage images in order, where possible, to carried out the stereo models orientation necessary for 3D navigation and plotting of critical geometric features of the glacier. Recognized geometric feature, referring to different periods, can be transferred to vector layers and imported in a GIS for further comparisons and investigations; d) to produce multi-temporal Digital Elevation Models for glacier volume changes; e) to perform orthoprojection of such images to obtain multitemporal orthoimages useful for areal an planar terrain evaluation and thematic analysis; f) to evaluate both planimetric positioning and height determination accuracies reachable through the photogrammetric process. Users have to known reliability of the measures they can do over such products. This can drive them to define the applicable field of this approach and this can help them to

  10. Quantification of coastline and key morphology changes over time in Northern Florida Bay, using high resolution shape analysis and aerial photographs

    SciTech Connect

    El-awawdeh, R.T.; Full, W.E.

    1996-10-01

    The study area includes fifty-one keys (islands) located in the north-central portion of the Florida Bay, south of the Everglades coastline and the coastline itself using aerial photography. These keys consisted of Quaternary unconsolidated fine-grained, calcareous mud overlaying Pleistocene rocks of the Miami Limestone. This region is sensitive to environmental changes caused by variations in the amount of fresh water flushing through the Everglades, by human influences such as channel dredging, and by strong storms. The primary purpose of this study is to identify and quantify morphologic changes in the keys and along the coastline over the last fifty to sixty years and to relate theses changes to the aforementioned processes. Well defined key-shape changes were found and quantified using aerial photographs of Deer, Cluett and Pelican Keys. These changes defined using three different shape analysis methods: Fourier two-dimensional shape analysis, Fractals in closed form, and the Zahn-Roskies algorithm in closed form. For the coastlines, Fractals in open form and the Zahn-Roskies in open form quantified shape differences. The observed changes were likely related to changes in sediment deposition throughout the bay due caused by environmental changes related to alterations of the bay`s natural drainage by artificial channel formation and storm deposition. The coastline remained essentially the same except for some minor changes around Alligator Bay attributed to mangrove expansion and sediment buildup due to storms. 19 refs., 5 figs.

  11. Interpretation of high-resolution imagery for detecting vegetation cover composition change after fuels reduction treatments in woodlands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The use of very high resolution (VHR; ground sampling distances < ~5cm) aerial imagery to estimate site vegetation cover and to detect changes from management has been well documented. However, as the purpose of monitoring is to document change over time, the ability to detect changes from imagery a...

  12. An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery

    NASA Astrophysics Data System (ADS)

    Burn, Douglas M.; Udevitz, Mark S.; Speckman, Suzann G.; Benter, R. Bradley

    2009-10-01

    In recent years, application of remote sensing to marine mammal surveys has been a promising area of investigation for wildlife managers and researchers. In April 2006, the United States and Russia conducted an aerial survey of Pacific walrus ( Odobenus rosmarus divergens) using thermal infrared sensors to detect groups of animals resting on pack ice in the Bering Sea. The goal of this survey was to estimate the size of the Pacific walrus population. An initial analysis of the U.S. data using previously-established methods resulted in lower detectability of walrus groups in the imagery and higher variability in calibration models than was expected based on pilot studies. This paper describes an improved procedure for detection and enumeration of walrus groups in airborne thermal imagery. Thermal images were first subdivided into smaller 200 × 200 pixel "tiles." We calculated three statistics to represent characteristics of walrus signatures from the temperature histogram for each tile. Tiles that exhibited one or more of these characteristics were examined further to determine if walrus signatures were present. We used cluster analysis on tiles that contained walrus signatures to determine which pixels belonged to each group. We then calculated a thermal index value for each walrus group in the imagery and used generalized linear models to estimate detection functions (the probability of a group having a positive index value) and calibration functions (the size of a group as a function of its index value) based on counts from matched digital aerial photographs. The new method described here improved our ability to detect walrus groups at both 2 m and 4 m spatial resolution. In addition, the resulting calibration models have lower variance than the original method. We anticipate that the use of this new procedure will greatly improve the quality of the population estimate derived from these data. This procedure may also have broader applicability to thermal

  13. An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery

    USGS Publications Warehouse

    Burn, Douglas M.; Udevitz, Mark S.; Speckman, Suzann G.; Benter, R. Bradley

    2009-01-01

    In recent years, application of remote sensing to marine mammal surveys has been a promising area of investigation for wildlife managers and researchers. In April 2006, the United States and Russia conducted an aerial survey of Pacific walrus (Odobenus rosmarus divergens) using thermal infrared sensors to detect groups of animals resting on pack ice in the Bering Sea. The goal of this survey was to estimate the size of the Pacific walrus population. An initial analysis of the U.S. data using previously-established methods resulted in lower detectability of walrus groups in the imagery and higher variability in calibration models than was expected based on pilot studies. This paper describes an improved procedure for detection and enumeration of walrus groups in airborne thermal imagery. Thermal images were first subdivided into smaller 200 x 200 pixel "tiles." We calculated three statistics to represent characteristics of walrus signatures from the temperature histogram for each the. Tiles that exhibited one or more of these characteristics were examined further to determine if walrus signatures were present. We used cluster analysis on tiles that contained walrus signatures to determine which pixels belonged to each group. We then calculated a thermal index value for each walrus group in the imagery and used generalized linear models to estimate detection functions (the probability of a group having a positive index value) and calibration functions (the size of a group as a function of its index value) based on counts from matched digital aerial photographs. The new method described here improved our ability to detect walrus groups at both 2 m and 4 m spatial resolution. In addition, the resulting calibration models have lower variance than the original method. We anticipate that the use of this new procedure will greatly improve the quality of the population estimate derived from these data. This procedure may also have broader applicability to thermal infrared

  14. Efficient pedestrian detection from aerial vehicles with object proposals and deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Minnehan, Breton; Savakis, Andreas

    2016-05-01

    As Unmanned Aerial Systems grow in numbers, pedestrian detection from aerial platforms is becoming a topic of increasing importance. By providing greater contextual information and a reduced potential for occlusion, the aerial vantage point provided by Unmanned Aerial Systems is highly advantageous for many surveillance applications, such as target detection, tracking, and action recognition. However, due to the greater distance between the camera and scene, targets of interest in aerial imagery are generally smaller and have less detail. Deep Convolutional Neural Networks (CNN's) have demonstrated excellent object classification performance and in this paper we adopt them to the problem of pedestrian detection from aerial platforms. We train a CNN with five layers consisting of three convolution-pooling layers and two fully connected layers. We also address the computational inefficiencies of the sliding window method for object detection. In the sliding window configuration, a very large number of candidate patches are generated from each frame, while only a small number of them contain pedestrians. We utilize the Edge Box object proposal generation method to screen candidate patches based on an "objectness" criterion, so that only regions that are likely to contain objects are processed. This method significantly reduces the number of image patches processed by the neural network and makes our classification method very efficient. The resulting two-stage system is a good candidate for real-time implementation onboard modern aerial vehicles. Furthermore, testing on three datasets confirmed that our system offers high detection accuracy for terrestrial pedestrian detection in aerial imagery.

  15. Instantaneous Shoreline Extraction Utilizing Integrated Spectrum and Shadow Analysis From LiDAR Data and High-resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Lee, I.-Chieh

    manually connected, for its length was less than 3% of the total shoreline length in our dataset. Secondly, the parameters for satellite image classification needed to be manually determined. The need for manpower was significantly less compared to the ground surveying or aerial photogrammetry. The first phase of shoreline extraction was to utilize Normalized Difference Vegetation Index (NDVI), Mean-Shift segmentation on the coordinate (X, Y, Z), and attributes (multispectral bands from satellite images) of the LiDAR points to classify each LiDAR point into land or water surface. Boundary of the land points were then traced to create the shoreline. The second phase of shoreline extraction solely from satellite images utilized spectrum, NDVI, and shadow analysis to classify the satellite images into classes. These classes were then refined by mean-shift segmentation on the panchromatic band. By tracing the boundary of the water surface, the shoreline can be created. Since these two shorelines may represent different shoreline instances in time, evaluating the changes of shoreline was the first to be done. Then an independent scenario analysis and a procedure are performed for the shoreline of each of the three conditions: in the process of erosion, in the process of accession, and remaining the same. With these three conditions, we could analysis the actual terrain type and correct the classification errors to obtain a more accurate shoreline. Meanwhile, methods of evaluating the quality of shorelines had also been discussed. The experiment showed that there were three indicators could best represent the quality of the shoreline. These indicators were: (1) shoreline accuracy, (2) land area difference between extracted shoreline and ground truth shoreline, and (3) bias factor from shoreline quality metrics.

  16. Estimating wetland vegetation abundance from Landsat-8 operational land imager imagery: a comparison between linear spectral mixture analysis and multinomial logit modeling methods

    NASA Astrophysics Data System (ADS)

    Zhang, Min; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Liu, Ke

    2016-01-01

    Mapping vegetation abundance by using remote sensing data is an efficient means for detecting changes of an eco-environment. With Landsat-8 operational land imager (OLI) imagery acquired on July 31, 2013, both linear spectral mixture analysis (LSMA) and multinomial logit model (MNLM) methods were applied to estimate and assess the vegetation abundance in the Wild Duck Lake Wetland in Beijing, China. To improve mapping vegetation abundance and increase the number of endmembers in spectral mixture analysis, normalized difference vegetation index was extracted from OLI imagery along with the seven reflective bands of OLI data for estimating the vegetation abundance. Five endmembers were selected, which include terrestrial plants, aquatic plants, bare soil, high albedo, and low albedo. The vegetation abundance mapping results from Landsat OLI data were finally evaluated by utilizing a WorldView-2 multispectral imagery. Similar spatial patterns of vegetation abundance produced by both fully constrained LSMA algorithm and MNLM methods were observed: higher vegetation abundance levels were distributed in agricultural and riparian areas while lower levels in urban/built-up areas. The experimental results also indicate that the MNLM model outperformed the LSMA algorithm with smaller root mean square error (0.0152 versus 0.0252) and higher coefficient of determination (0.7856 versus 0.7214) as the MNLM model could handle the nonlinear reflection phenomenon better than the LSMA with mixed pixels.

  17. The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Patterson, Maria T.; Anderson, Nicholas; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert L.; Handy, Matthew; Ly, Vuong; Mandl, Daniel J.; Pederson, Shane; Pivarski, James; Powell, Ray; Spring, Jonathan; Wells, Walt; Xia, John

    2016-01-01

    Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for

  18. Comparative Meta-Analysis of Prazosin and Imagery Rehearsal Therapy for Nightmare Frequency, Sleep Quality, and Posttraumatic Stress

    PubMed Central

    Seda, Gilbert; Sanchez-Ortuno, Maria M.; Welsh, Carolyn H.; Halbower, Ann C.; Edinger, Jack D.

    2015-01-01

    Study Objective: In this meta-analysis, we compare the short-term efficacy of prazosin vs. IRT on nightmares, sleep quality, and posttraumatic stress symptoms (PTSS). Methods: Reference databases were searched for randomized controlled trials using IRT or prazosin for nightmares, sleep disturbance, and/or PTSS. Effect sizes were calculated by subtracting the mean posttest score in the control group from the mean posttest score in the treatment group, and dividing the result by the pooled standard deviation of both groups. Mixed effects models were performed to evaluate effects of treatment characteristics, as well as sample characteristics (veteran vs. civilian) on treatment efficacy. Results: Four studies used prazosin, 10 used IRT alone or in combination with another psychological treatment, and 1 included a group receiving prazosin and another group receiving IRT. Overall effect sizes of both treatments were of moderate magnitude for nightmare frequency, sleep quality, and PTSS (p < 0.01). Effect size was not significantly different with type of treatment (psychological vs. pharmacological) on nightmare frequency (p = 0.79), sleep quality (p = 0.65), or PTSS, (p = 0.52). IRT combined with CBT for insomnia showed more improvement in sleep quality compared to prazosin (p = 0.03), IRT alone (p = 0.03), or IRT combined with another psychological intervention, (p < 0.01). Conclusion: Although IRT interventions and prazosin yield comparable acute effects for the treatment of nightmares, adding CBT for insomnia to IRT seems to enhance treatment outcomes pertaining to sleep quality and PTSS. More randomized clinical trials with long-term follow-up are warranted. Commentary: A commentary on this article appears in this issue on page 9. Citation: Seda G, Sanchez-Ortuno MM, Welsh CH, Halbower AC, Edinger JD. Comparative meta-analysis of prazosin and imagery rehearsal therapy for nightmare frequency, sleep quality, and posttraumatic stress. J Clin Sleep Med 2015;11(1):11

  19. Analysis of EEG Signals Related to Artists and Nonartists during Visual Perception, Mental Imagery, and Rest Using Approximate Entropy

    PubMed Central

    Shourie, Nasrin; Firoozabadi, Mohammad; Badie, Kambiz

    2014-01-01

    In this paper, differences between multichannel EEG signals of artists and nonartists were analyzed during visual perception and mental imagery of some paintings and at resting condition using approximate entropy (ApEn). It was found that ApEn is significantly higher for artists during the visual perception and the mental imagery in the frontal lobe, suggesting that artists process more information during these conditions. It was also observed that ApEn decreases for the two groups during the visual perception due to increasing mental load; however, their variation patterns are different. This difference may be used for measuring progress in novice artists. In addition, it was found that ApEn is significantly lower during the visual perception than the mental imagery in some of the channels, suggesting that visual perception task requires more cerebral efforts. PMID:25133180

  20. 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.

  1. CORRELATION ANALYSIS OF HYPERSPECTRAL IMAGERY FOR MULTISPECTRAL WAVELENGTH SELECTION FOR DETECTION OF DEFECTS ON APPLES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Visible/near-infrared reflectance spectra extracted from hyperspectral images of apples were used to determine wavelength pairs that can be used to distinguish defect regions from normal regions on the apple surface. The optimal wavelengths were selected based on correlation analysis between the wa...

  2. Dialectical Imagery and Postmodern Research

    ERIC Educational Resources Information Center

    Davison, Kevin G.

    2006-01-01

    This article suggests utilizing dialectical imagery, as understood by German social philosopher Walter Benjamin, as an additional qualitative data analysis strategy for research into the postmodern condition. The use of images mined from research data may offer epistemological transformative possibilities that will assist in the demystification of…

  3. Vividness of Object and Spatial Imagery.

    PubMed

    Blazhenkova, Olesya

    2016-04-01

    Vividness is one of the fundamental characteristics of visual mental imagery. The first research goal was to examine whether vividness that refer to imagery of pictorial object (color, texture, or shape) versus spatial (three dimensional structure, location, or mechanism) properties constitute separate vividness dimensions. The second goal was to develop a vividness questionnaire separately assessing dimensions of imagery vividness. In Study 1, 111 students (M age = 21.8 years, SD = 1.3) evaluated the vividness of imagery evoked by nine object and nine spatial items from the pilot version of the new Vividness of Object and Spatial Imagery (VOSI) questionnaire, completed a self-report assessment of object and spatial imagery, and rated their aptitudes in art and science. Analysis indicated that imagery vividness comprised object and spatial dimensions. Object vividness items were positively associated with the self-report measure and ratings of artistic abilities, whereas spatial vividness items were positively associated with self-report measure and ratings of science abilities. In Study 2, an independent sample of 205 students (M age = 21 years, SD = 1.7) completed the second version of the VOSI, art and science aptitude ratings, and a number of self-report and performance measures assessing object and spatial imagery. Object and spatial imagery vividness items loaded on factors with 28 retained items; this two-factor vividness model fit the data better than a unidimensional vividness model. The questionnaire had satisfactory Cronbach's α for object vividness scale (.88) and for spatial vividness scale (.85). Correlational analyses supported convergent and discriminative validity of the VOSI. While object imagery vividness and spatial imagery vividness share some underlying vividness variance, they are dissociated into separate dimensions. PMID:27166329

  4. Updating Maps Using High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Alrajhi, Muhamad; Shahzad Janjua, Khurram; Afroz Khan, Mohammad; Alobeid, Abdalla

    2016-06-01

    Kingdom of Saudi Arabia is one of the most dynamic countries of the world. We have witnessed a very rapid urban development's which are altering Kingdom's landscape on daily basis. In recent years a substantial increase in urban populations is observed which results in the formation of large cities. Considering this fast paced growth, it has become necessary to monitor these changes, in consideration with challenges faced by aerial photography projects. It has been observed that data obtained through aerial photography has a lifecycle of 5-years because of delay caused by extreme weather conditions and dust storms which acts as hindrances or barriers during aerial imagery acquisition, which has increased the costs of aerial survey projects. All of these circumstances require that we must consider some alternatives that can provide us easy and better ways of image acquisition in short span of time for achieving reliable accuracy and cost effectiveness. The approach of this study is to conduct an extensive comparison between different resolutions of data sets which include: Orthophoto of (10 cm) GSD, Stereo images of (50 cm) GSD and Stereo images of (1 m) GSD, for map updating. Different approaches have been applied for digitizing buildings, roads, tracks, airport, roof level changes, filling stations, buildings under construction, property boundaries, mosques buildings and parking places.

  5. Study of time-lapse processing for dynamic hydrologic conditions. [electronic satellite image analysis console for Earth Resources Technology Satellites imagery

    NASA Technical Reports Server (NTRS)

    Serebreny, S. M.; Evans, W. E.; Wiegman, E. J.

    1974-01-01

    The usefulness of dynamic display techniques in exploiting the repetitive nature of ERTS imagery was investigated. A specially designed Electronic Satellite Image Analysis Console (ESIAC) was developed and employed to process data for seven ERTS principal investigators studying dynamic hydrological conditions for diverse applications. These applications include measurement of snowfield extent and sediment plumes from estuary discharge, Playa Lake inventory, and monitoring of phreatophyte and other vegetation changes. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The most unique feature of the system is the capability to time lapse the imagery and analytic displays of the imagery. Data products included quantitative measurements of distances and areas, binary thematic maps based on monospectral or multispectral decisions, radiance profiles, and movie loops. Applications of animation for uses other than creating time-lapse sequences are identified. Input to the ESIAC can be either digital or via photographic transparencies.

  6. Automated Spatio-Temporal Analysis of Remotely Sensed Imagery for Water Resources Management

    NASA Astrophysics Data System (ADS)

    Bahr, Thomas

    2016-04-01

    Since 2012, the state of California faces an extreme drought, which impacts water supply in many ways. Advanced remote sensing is an important technology to better assess water resources, monitor drought conditions and water supplies, plan for drought response and mitigation, and measure drought impacts. In the present case study latest time series analysis capabilities are used to examine surface water in reservoirs located along the western flank of the Sierra Nevada region of California. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. A time series from Landsat images (L-5 TM, L-7 ETM+, L-8 OLI) of the AOI was obtained for 1999 to 2015 (October acquisitions). Downloaded from the USGS EarthExplorer web site, they already were georeferenced to a UTM Zone 10N (WGS-84) coordinate system. ENVITasks were used to pre-process the Landsat images as follows: • Triangulation based gap-filling for the SLC-off Landsat-7 ETM+ images. • Spatial subsetting to the same geographic extent. • Radiometric correction to top-of-atmosphere (TOA) reflectance. • Atmospheric correction using QUAC®, which determines atmospheric correction parameters directly from the observed pixel spectra in a scene, without ancillary information. Spatio-temporal analysis was executed with the following tasks: • Creation of Modified Normalized Difference Water Index images (MNDWI, Xu 2006) to enhance open water features while suppressing noise from built-up land, vegetation, and soil. • Threshold based classification of the water index images to extract the water features. • Classification aggregation as a post-classification cleanup process. • Export of the respective water classes to vector layers for further evaluation in a GIS. • Animation of the classification series and export to

  7. Automated Analysis of Radar Imagery of Venus: Handling Lack of Ground Truth

    NASA Technical Reports Server (NTRS)

    Burl, M.; Fayyad, U.; Perona, P.; Smyth, P.

    1994-01-01

    Lack of verifiable ground truth is a common problem in remote sensing image analysis. For example, consider the synthetic aperture radar (SAR) image data of Venus obtained by the Magellan spacecraft. Planetary scientists are interested in automatically cataloging the locations of all the small volcanoes in this data set; however, the problem is very difficult and cannot be performed with perfect reliability even by human experts. Thus, training and evaluating the performance of an automatic algorithm on this data set must be handled carefully. We discuss the use of weighted free-response receiver-operating characteristics (wFROC) for evaluating detection performance when the ground truth is subjective.

  8. Detecting the socioeconomic conditions of urban neighborhoods through wavelet analysis of remotely sensed imagery

    NASA Astrophysics Data System (ADS)

    Zhou, Guiyun

    Wavelet analysis is an efficient approach to studying textural patterns at different scales. Artificial neural networks can learn very complex patterns in the data and could be an efficient classifier. However, whether wavelet analysis, in combination with artificial neural networks or other classifiers, can be used to detect the social-economic conditions of urban neighborhood is a key research question that needs further study. The hypotheses of this study were: (1) neural networks yielded higher classification accuracy than linear discriminant analysis and the minimum-distance classifier based on wavelet measures of urban land covers; (2) wavelet textural measures could be used to efficiently discriminate among urban neighborhoods of different social-economic conditions; (3) image resolution had great influences on the discrimination of urban neighborhoods; and (4) window size had great influences on the discrimination of urban neighborhoods. In addition, two technical problems related to the application of textural approach, including the edge effect and image segmentation problem, were examined. The results show that the new approach developed to reducing edge effects consistently achieved higher accuracy than the traditional moving-window approach. The post-segmentation integration scheme in the region-based splitting-and-merging segmentation procedures reflected all the segmented clusters identified by two or more textural measures and was helpful in identifying homogeneous regions in an image. Regarding the four hypotheses, (1) The minimum-distance classifier performed the worst. Neural networks were found to generally yield slightly better results than discriminant analysis but the difference was not statistically significant. The first hypothesis was shown to be invalid. (2) With a window size of 85m by 85m, an overall accuracy of 93.00% was achieved using band 2 and an overall accuracy of 96.83% was achieved using combination of band 2 and band 3. (3

  9. Polar Bears from Space: Assessing Satellite Imagery as a Tool to Track Arctic Wildlife

    PubMed Central

    Stapleton, Seth; LaRue, Michelle; Lecomte, Nicolas; Atkinson, Stephen; Garshelis, David; Porter, Claire; Atwood, Todd

    2014-01-01

    Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark–recapture models. This estimate (: 94; 95% Confidence Interval: 92–105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (: 102; 95% CI: 69–152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics. PMID:25006979

  10. Polar bears from space: assessing satellite imagery as a tool to track Arctic wildlife.

    PubMed

    Stapleton, Seth; LaRue, Michelle; Lecomte, Nicolas; Atkinson, Stephen; Garshelis, David; Porter, Claire; Atwood, Todd

    2014-01-01

    Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark-recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics. PMID:25006979

  11. Polar bears from space: assessing satellite imagery as a tool to track Arctic wildlife

    USGS Publications Warehouse

    Stapleton, Seth P.; LaRue, Michelle A.; Lecomte, Nicolas; Atkinson, Stephen N.; Garshelis, David L.; Porter, Claire; Atwood, Todd C.

    2014-01-01

    Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark- recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

  12. Polar bears from space: assessing satellite imagery as a tool to track Arctic wildlife.

    PubMed

    Stapleton, Seth; LaRue, Michelle; Lecomte, Nicolas; Atkinson, Stephen; Garshelis, David; Porter, Claire; Atwood, Todd

    2014-01-01

    Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark-recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

  13. Point Cloud Generation from sUAS-Mounted iPhone Imagery: Performance Analysis

    NASA Astrophysics Data System (ADS)

    Ladai, A. D.; Miller, J.

    2014-11-01

    The rapidly growing use of sUAS technology and fast sensor developments continuously inspire mapping professionals to experiment with low-cost airborne systems. Smartphones has all the sensors used in modern airborne surveying systems, including GPS, IMU, camera, etc. Of course, the performance level of the sensors differs by orders, yet it is intriguing to assess the potential of using inexpensive sensors installed on sUAS systems for topographic applications. This paper focuses on the quality analysis of point clouds generated based on overlapping images acquired by an iPhone 5s mounted on a sUAS platform. To support the investigation, test data was acquired over an area with complex topography and varying vegetation. In addition, extensive ground control, including GCPs and transects were collected with GSP and traditional geodetic surveying methods. The statistical and visual analysis is based on a comparison of the UAS data and reference dataset. The results with the evaluation provide a realistic measure of data acquisition system performance. The paper also gives a recommendation for data processing workflow to achieve the best quality of the final products: the digital terrain model and orthophoto mosaic. After a successful data collection the main question is always the reliability and the accuracy of the georeferenced data.

  14. Blind spectral unmixing based on sparse component analysis for hyperspectral remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Zhong, Yanfei; Wang, Xinyu; Zhao, Lin; Feng, Ruyi; Zhang, Liangpei; Xu, Yanyan

    2016-09-01

    Recently, many blind source separation (BSS)-based techniques have been applied to hyperspectral unmixing. In this paper, a new blind spectral unmixing method based on sparse component analysis (BSUSCA) is proposed to solve the problem of highly mixed data. The BSUSCA algorithm consists of an alternative scheme based on two-block alternating optimization, by which we can simultaneously obtain the endmember signatures and their corresponding fractional abundances. According to the spatial distribution of the endmembers, the sparse properties of the fractional abundances are considered in the proposed algorithm. A sparse component analysis (SCA)-based mixing matrix estimation method is applied to update the endmember signatures, and the abundance estimation problem is solved by the alternating direction method of multipliers (ADMM). SCA is utilized for the unmixing due to its various advantages, including the unique solution and robust modeling assumption. The robustness of the proposed algorithm is verified through simulated experimental study. The experimental results using both simulated data and real hyperspectral remote sensing images confirm the high efficiency and precision of the proposed algorithm.

  15. 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

  16. High-biomass sorghum yield estimate with aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Abstract. To reach the goals laid out by the U.S. Government for displacing fossil fuels with biofuels, agricultural production of dedicated biomass crops is required. High-biomass sorghum is advantageous across wide regions because it requires less water per unit dry biomass and can produce very hi...

  17. Inferring Species Richness and Turnover by Statistical Multiresolution Texture Analysis of Satellite Imagery

    PubMed Central

    Convertino, Matteo; Mangoubi, Rami S.; Linkov, Igor; Lowry, Nathan C.; Desai, Mukund

    2012-01-01

    Background The quantification of species-richness and species-turnover is essential to effective monitoring of ecosystems. Wetland ecosystems are particularly in need of such monitoring due to their sensitivity to rainfall, water management and other external factors that affect hydrology, soil, and species patterns. A key challenge for environmental scientists is determining the linkage between natural and human stressors, and the effect of that linkage at the species level in space and time. We propose pixel intensity based Shannon entropy for estimating species-richness, and introduce a method based on statistical wavelet multiresolution texture analysis to quantitatively assess interseasonal and interannual species turnover. Methodology/Principal Findings We model satellite images of regions of interest as textures. We define a texture in an image as a spatial domain where the variations in pixel intensity across the image are both stochastic and multiscale. To compare two textures quantitatively, we first obtain a multiresolution wavelet decomposition of each. Either an appropriate probability density function (pdf) model for the coefficients at each subband is selected, and its parameters estimated, or, a non-parametric approach using histograms is adopted. We choose the former, where the wavelet coefficients of the multiresolution decomposition at each subband are modeled as samples from the generalized Gaussian pdf. We then obtain the joint pdf for the coefficients for all subbands, assuming independence across subbands; an approximation that simplifies the computational burden significantly without sacrificing the ability to statistically distinguish textures. We measure the difference between two textures' representative pdf's via the Kullback-Leibler divergence (KL). Species turnover, or diversity, is estimated using both this KL divergence and the difference in Shannon entropy. Additionally, we predict species richness, or diversity, based on the

  18. Geologic analysis and evaluation of ERTS-A imagery for the State of New Mexico

    NASA Technical Reports Server (NTRS)

    Kottlowski, F. E. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. Many circular to elliptical features have been identified on the ERTS-1 images, only some of which can be accounted for by existing data. A small number of circular features are adjacent to existing ore deposits, but such relationships should not be emphasized unless other supporting data exists. Circular features may be tectonically or geomorphically controlled, or a combination of the two. A limited number are man-made. A preliminary listing of features which may have circular expression are listed. Photographic examples of identified and unidentified circular features will be included in the final report along with a thorough discussion and analysis. Comparisons will be made with existing gravity and magnetic data.

  19. Motivation and Vision: An Analysis of Future L2 Self Images, Sensory Styles, and Imagery Capacity across Two Target Languages

    ERIC Educational Resources Information Center

    Dörnyei, Zoltán; Chan, Letty

    2013-01-01

    Recent theorizing on second language (L2) motivation has proposed viewing motivation as a function of the language learners' vision of their desired future language selves. This would suggest that the intensity of motivation is partly dependent on the learners' capability to generate mental imagery. In order to test this hypothesis, this…

  20. Alcohol imagery on New Zealand television

    PubMed Central

    McGee, Rob; Ketchel, Juanita; Reeder, Anthony I

    2007-01-01

    Background To examine the extent and nature of alcohol imagery on New Zealand (NZ) television, a content analysis of 98 hours of prime-time television programs and advertising was carried out over 7 consecutive days' viewing in June/July 2004. The main outcome measures were number of scenes in programs, trailers and advertisements depicting alcohol imagery; the extent of critical versus neutral and promotional imagery; and the mean number of scenes with alcohol per hour, and characteristics of scenes in which alcohol featured. Results There were 648 separate depictions of alcohol imagery across the week, with an average of one scene every nine minutes. Scenes depicting uncritical imagery outnumbered scenes showing possible adverse health consequences of drinking by 12 to 1. Conclusion The evidence points to a large amount of alcohol imagery incidental to storylines in programming on NZ television. Alcohol is also used in many advertisements to market non-alcohol goods and services. More attention needs to be paid to the extent of alcohol imagery on television from the industry, the government and public health practitioners. Health education with young people could raise critical awareness of the way alcohol imagery is presented on television. PMID:17270053

  1. Evaluation of Bare Ground on Rangelands using Unmanned Aerial Vehicles

    SciTech Connect

    Robert P. Breckenridge; Maxine Dakins

    2011-01-01

    Attention is currently being given to methods that assess the ecological condition of rangelands throughout the United States. There are a number of different indicators that assess ecological condition of rangelands. Bare Ground is being considered by a number of agencies and resource specialists as a lead indicator that can be evaluated over a broad area. Traditional methods of measuring bare ground rely on field technicians collecting data along a line transect or from a plot. Unmanned aerial vehicles (UAVs) provide an alternative to collecting field data, can monitor a large area in a relative short period of time, and in many cases can enhance safety and time required to collect data. In this study, both fixed wing and helicopter UAVs were used to measure bare ground in a sagebrush steppe ecosystem. The data were collected with digital imagery and read using the image analysis software SamplePoint. The approach was tested over seven different plots and compared against traditional field methods to evaluate accuracy for assessing bare ground. The field plots were located on the Idaho National Laboratory (INL) site west of Idaho Falls, Idaho in locations where there is very little disturbance by humans and the area is grazed only by wildlife. The comparison of fixed-wing and helicopter UAV technology against field estimates shows good agreement for the measurement of bare ground. This study shows that if a high degree of detail and data accuracy is desired, then a helicopter UAV may be a good platform. If the data collection objective is to assess broad-scale landscape level changes, then the collection of imagery with a fixed-wing system is probably more appropriate.

  2. Twenty years of Belgian North Sea aerial surveillance: a quantitative analysis of results confirms effectiveness of international oil pollution legislation.

    PubMed

    Lagring, Ruth; Degraer, Steven; de Montpellier, Géraldine; Jacques, Thierry; Van Roy, Ward; Schallier, Ronny

    2012-03-01

    Over the years many policy measures have been taken to prevent illegal oil discharges from ships, like the MARPOL 73/78 Convention (1983) and the Bonn Agreement (1969/1983). However, the number of discharges remained high, leading to chronic oiling of seabirds and sensitive coastlines, therefore further measures were taken. The aim of this study is to quantify the effectiveness of two key legislative regulations: the IMO-designation of the North Sea as MARPOL Special Area which took effect in 1999, and the adoption of the EU Directive on Port Reception Facilities in 2000. Under study is the heavily navigated Belgian Surveillance Area, monitored since 1991, characterised by shallow waters with ecologically important sandbanks. The aerial surveillance data from 1991 to 2010 show a stepwise decrease in ship-source oil pollution. Three time periods can be distinguished with two turning points coinciding with the actual implementation of these key legislative measures, confirming their effectiveness.

  3. Antioxidant capacity and amino acid analysis of Caralluma adscendens (Roxb.) Haw var. fimbriata (wall.) Grav. & Mayur. aerial parts.

    PubMed

    Maheshu, Vellingiri; Priyadarsini, Deivamarudhachalam Teepica; Sasikumar, Jagathala Mahalingam

    2014-10-01

    Caralluma adscendens (Roxb.) Haw var. fimbriata (wall.) Grav. & Mayur. is a traditional food consumed as vegetable or pickle in arid regions of India and eaten during famines. In Indian traditional medicine, the plant is used to treat diabetes, inflammation and etc. The aim of this study was to evaluate the antioxidant properties (DPPH, TEAC, TAA, FRAP, OH˙ and NO˙ radical scavenging activities) of the different extracts from aerial parts. The levels of total phenolics and flavonoids of the extracts were also determined. The extracts were found to have different levels of antioxidant properties in the test models used. Methanol and water extracts had good total phenolic and flavonoid contents showed potent antioxidant and free radical scavenging activities. The antioxidant activity was correlated well with the amount of total phenolics present in the extracts. The extracts and its components may be used as an additive in food preparations and nutraceuticals. PMID:25328180

  4. Abundance quantification by independent component analysis of hyperspectral imagery for oil spill coverage calculation

    NASA Astrophysics Data System (ADS)

    Han, Zhongzhi; Wan, Jianhua; Zhang, Jie; Zhang, Hande

    2016-08-01

    The estimation of oil spill coverage is an important part of monitoring of oil spills at sea. The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size. We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm. For each independent component we added two constraint conditions: non-negativity and constant sum. We use priority weighting by higher-order statistics, and then the spectral angle match method to overcome the order nondeterminacy. By these steps, endmembers can be extracted and abundance quantified simultaneously. To examine the coverage of a real oil spill and correct our estimate, a simulation experiment and a real experiment were designed using the algorithm described above. The result indicated that, for the simulation data, the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6. We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011. The total oil spill area was 0.224 km2, and the oil spill rate was 22.89%. The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates. It also allows the accurate estimation of the oil spill area.

  5. Classification of mangroves vegetation species using texture analysis on Rapideye satellite imagery

    NASA Astrophysics Data System (ADS)

    Roslani, M. A.; Mustapha, M. A.; Lihan, T.; Juliana, W. A. Wan

    2013-11-01

    Mangroves are unique ecosystem structures that are typically made up of salt tolerant species of vegetation that can be found in tropical and subtropical climate country. Mangrove ecosystem plays important role and also is known as highly productive ecosystem with high diversity of flora and fauna. However, these ecosystems have been declining over time due to the various kinds of direct and indirect pressures. Thus, there is an increasing need to monitor and assess this ecosystem for better conservation and management efforts. The multispectral RapidEye satellite image was used to identify the mangrove vegetation species within the Matang Mangrove Forest Reserve in Perak, Malaysia using texture analysis. Classification was implemented using the maximum likelihood classifier (MLC) method. Total of eleven main mangrove species were found in the satellite image of the study site which includes Rhizophora mucronata, Rhizophora apiculata, Bruguiera parviflora, Bruguiera cylindrica, Bruguiera gymnorrhiza, Avicennia alba, Avicennia officinalis, Sonneratia alba, Sonneratia caseolaris, Sonneratia ovata and Xylocarpus granatum. The classification results showed that the textured image produced high overall classification assessment recorded at 84% and kappa statistic of 0.8016. Meanwhile, the non-textured image produces 80% of overall accuracy and kappa statistic of 0.7061. The classification result indicated the capability of high resolution satellite image to classify the mangrove species and inclusion of texture information in the classification increased the classification accuracy.

  6. Mapping and Change Analysis in Mangrove Forest by Using Landsat Imagery

    NASA Astrophysics Data System (ADS)

    Dan, T. T.; Chen, C. F.; Chiang, S. H.; Ogawa, S.

    2016-06-01

    Mangrove is located in the tropical and subtropical regions and brings good services for native people. Mangrove in the world has been lost with a rapid rate. Therefore, monitoring a spatiotemporal distribution of mangrove is thus critical for natural resource management. This research objectives were: (i) to map the current extent of mangrove in the West and Central Africa and in the Sundarbans delta, and (ii) to identify change of mangrove using Landsat data. The data were processed through four main steps: (1) data pre-processing including atmospheric correction and image normalization, (2) image classification using supervised classification approach, (3) accuracy assessment for the classification results, and (4) change detection analysis. Validation was made by comparing the classification results with the ground reference data, which yielded satisfactory agreement with overall accuracy 84.1% and Kappa coefficient of 0.74 in the West and Central Africa and 83.0% and 0.73 in the Sundarbans, respectively. The result shows that mangrove areas have changed significantly. In the West and Central Africa, mangrove loss from 1988 to 2014 was approximately 16.9%, and only 2.5% was recovered or newly planted at the same time, while the overall change of mangrove in the Sundarbans increased approximately by 900 km2 of total mangrove area. Mangrove declined due to deforestation, natural catastrophes deforestation and mangrove rehabilitation programs. The overall efforts in this study demonstrated the effectiveness of the proposed method used for investigating spatiotemporal changes of mangrove and the results could provide planners with invaluable quantitative information for sustainable management of mangrove ecosystems in these regions.

  7. Experimental observation and assessment of ice conditions with a fixed-wing unmanned aerial vehicle over Yellow River, China

    NASA Astrophysics Data System (ADS)

    Lin, Jiayuan; Shu, Li; Zuo, Hang; Zhang, Baosen

    2012-01-01

    Due to its unique geographical location and regional climate, the Yellow River and its tributaries are prone to ice jams almost every spring. Ice jams can cause levees to burst, leading to severe flooding, property damage, and human casualties. Hence, there is an urgent need to carry out observations of ice conditions and make risk assessments of ice jam occurrence. Field observation is the most reliable technique, but it is usually too expensive and time-consuming, which has led to the evaluation of applied remote sensing for data capture and analysis. Owing to the factors of timeliness, image resolution, human safety, and cost, satellite or manned aerial remote sensing cannot fully meet the requirements of ice condition observation. An unmanned aerial vehicle (UAV) remote sensing system is proposed for the collection of river ice imagery, providing the benefits of low cost, flexible launch and landing logistics, safety, and appropriate hyperspatial image resolution. One Inner Mongolian segment of the Yellow River was chosen as a test area to demonstrate key technologies and specific procedures of observation and assessment of ice conditions using the UAV system. The specific UAV remote sensing system and its components are introduced along with the procedures of UAV operation and imagery acquisition. Image preprocessing techniques and ice information extraction are described in detail followed by analysis and risk assessment of the ice conditions based on the resulting panoramic imagery. Results prove the feasibility and effectiveness of applying the fixed-wing UAV system to rapid observation and risk assessment of ice jam formation over the Yellow River under harsh weather conditions including low temperatures and strong winds.

  8. A Comparative Accuracy Analysis of Classification Methods in Determination of Cultivated Lands with Spot 5 Satellite Imagery

    NASA Astrophysics Data System (ADS)

    kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2013-12-01

    A Comparative Accuracy Analysis of Classification Methods in Determination of Cultivated Lands with Spot 5 Satellite Imagery Ugur ALGANCI1, Sinasi KAYA1,2, Elif SERTEL1,2,Berk USTUNDAG3 1 ITU, Center for Satellite Communication and Remote Sensing, 34469, Maslak-Istanbul,Turkey 2 ITU, Department of Geomatics, 34469, Maslak-Istanbul, Turkey 3 ITU, Agricultural and Environmental Informatics Research Center,34469, Maslak-Istanbul,Turkey alganci@itu.edu.tr, kayasina@itu.edu.tr, sertele@itu.edu.tr, berk@berk.tc ABSTRACT Cultivated land determination and their area estimation are important tasks for agricultural management. Derived information is mostly used in agricultural policies and precision agriculture, in specifically; yield estimation, irrigation and fertilization management and farmers declaration verification etc. The use of satellite image in crop type identification and area estimate is common for two decades due to its capability of monitoring large areas, rapid data acquisition and spectral response to crop properties. With launch of high and very high spatial resolution optical satellites in the last decade, such kind of analysis have gained importance as they provide information at big scale. With increasing spatial resolution of satellite images, image classification methods to derive the information form them have become important with increase of the spectral heterogeneity within land objects. In this research, pixel based classification with maximum likelihood algorithm and object based classification with nearest neighbor algorithm were applied to 2012 dated 2.5 m resolution SPOT 5 satellite images in order to investigate the accuracy of these methods in determination of cotton and corn planted lands and their area estimation. Study area was selected in Sanliurfa Province located on Southeastern Turkey that contributes to Turkey's agricultural production in a major way. Classification results were compared in terms of crop type identification using

  9. 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.

  10. Processing Satellite Imagery To Detect Waste Tire Piles

    NASA Technical Reports Server (NTRS)

    Skiles, Joseph; Schmidt, Cynthia; Wuinlan, Becky; Huybrechts, Catherine

    2007-01-01

    A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed

  11. Vehicle classification in WAMI imagery using deep network

    NASA Astrophysics Data System (ADS)

    Yi, Meng; Yang, Fan; Blasch, Erik; Sheaff, Carolyn; Liu, Kui; Chen, Genshe; Ling, Haibin

    2016-05-01

    Humans have always had a keen interest in understanding activities and the surrounding environment for mobility, communication, and survival. Thanks to recent progress in photography and breakthroughs in aviation, we are now able to capture tens of megapixels of ground imagery, namely Wide Area Motion Imagery (WAMI), at multiple frames per second from unmanned aerial vehicles (UAVs). WAMI serves as a great source for many applications, including security, urban planning and route planning. These applications require fast and accurate image understanding which is time consuming for humans, due to the large data volume and city-scale area coverage. Therefore, automatic processing and understanding of WAMI imagery has been gaining attention in both industry and the research community. This paper focuses on an essential step in WAMI imagery analysis, namely vehicle classification. That is, deciding whether a certain image patch contains a vehicle or not. We collect a set of positive and negative sample image patches, for training and testing the detector. Positive samples are 64 × 64 image patches centered on annotated vehicles. We generate two sets of negative images. The first set is generated from positive images with some location shift. The second set of negative patches is generated from randomly sampled patches. We also discard those patches if a vehicle accidentally locates at the center. Both positive and negative samples are randomly divided into 9000 training images and 3000 testing images. We propose to train a deep convolution network for classifying these patches. The classifier is based on a pre-trained AlexNet Model in the Caffe library, with an adapted loss function for vehicle classification. The performance of our classifier is compared to several traditional image classifier methods using Support Vector Machine (SVM) and Histogram of Oriented Gradient (HOG) features. While the SVM+HOG method achieves an accuracy of 91.2%, the accuracy of our

  12. Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

    NASA Astrophysics Data System (ADS)

    Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

    2014-10-01

    The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure

  13. Mapping species across multiple dates of hyperspectral imagery using Iterative Endmember Selection and Multiple Endmember Spectral Mixture Analysis

    NASA Astrophysics Data System (ADS)

    Dudley, Kenneth L.

    Vegetation phenology results in seasonal changes in spectral reflectance. Phenology is often underutilized in hyperspectral vegetation mapping due to a lack of repeat imagery of the same region over time. Vegetation classification at the species level could benefit from introducing phenological information to spectral libraries. New missions, such as the proposed Hysperspectral Infrared Imager (HyspIRI) mission, could potentially provide easy access to multi-temporal datasets. The availability of these data will require new approaches to building spectral libraries for species classification. This paper explores the use of Iterative Endmember Selection (IES), an automated method for selecting endmembers from an image-derived spectral library, to create single-date and multi-temporal endmember libraries. Multiple Endmember Spectral Mixture Analysis (MESMA) was used to classify vegetation species and land cover, applying single-date and multi-temporal libraries to Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data acquired on five dates in the same year. Three applications of endmember libraries were tested for their ability to classify single date AVIRIS images: 1) single-date libraries that matched the image date (same-date libraries), 2) single-date libraries that were not matched to the image date (mismatched-date libraries), and 3) a combined multi-temporal library containing spectra from all dates applied to all image dates. Results indicate that multi-temporal, seasonally-mixed spectral libraries achieved similar overall classification accuracy compared to single-date libraries, and in some cases, resulted in improved classification accuracy. Several species had increased Producer's or User accuracy using a multi-temporal library, while others had reduced accuracy compared to same-date classifications. The image dates of selected endmembers from the multi-temporal library were examined to determine if this information could improve our understanding

  14. Improved seagrass mapping using linear spectral unmixing of aerial photographs

    NASA Astrophysics Data System (ADS)

    Uhrin, Amy V.; Townsend, Philip A.

    2016-03-01

    Mapping of seagrass is challenging, particularly in areas where seagrass cover ranges from extensive, continuous meadows to aggregations of patchy mounds often no more than a meter across. Manual delineation of seagrass habitat polygons through visual photointerpretation of high resolution aerial imagery remains the most widely adopted approach for mapping seagrass extent but polygons often include unvegetated gaps. Although mapped polygon data exist for many estuaries, these are likely insufficient to accurately characterize spatial pattern or estimate area actually occupied by seagrass. We evaluated whether a linear spectral unmixing (LSU) classifier applied to manually-delineated seagrass polygons clipped from digital aerial images could improve mapping of seagrass in North Carolina. Representative seagrass endmembers were chosen directly from images and used to unmix image-clipped polygons, resulting in fraction planes (maps) of the proportion of seagrass present in each image pixel. Thresholding was used to generate seagrass maps for each pixel proportion from 0 (no thresholding, all pixel proportions included) to 1 (only pixels having 100% seagrass) in 0.1 increments. The optimal pixel proportion for identifying seagrass was assessed using Euclidean distance calculated from Receiver Operating Characteristic (ROC) curves and overall thematic accuracy calculated from confusion matrices. We assessed overall classifier performance using Kappa statistics and Area Under the (ROC) Curve (AUC). We compared seagrass area calculated from each threshold map to the total area of the corresponding manually-delineated polygon. LSU effectively classified seagrass and performed better than a random classification as indicated by high values for both Kappa statistics (0.72-98) and AUC (0.80-0.99). The LSU classifier effectively distinguished between seagrass and bare substrate resulting in fine-scale seagrass maps with overall thematic accuracies that exceeded our expected

  15. Reference LIDAR Surfaces for Enhanced Aerial Triangulation and Camera Calibration

    NASA Astrophysics Data System (ADS)

    Gneeniss, A. S.; Mills, J. P.; Miller, P. E.

    2013-04-01

    Due to the complementary characteristics of lidar and photogrammetry, the integration of data derived from these techniques continues to receive attention from the relevant research communities. The research presented in this paper draws on this by adopting lidar data as a control surface from which aerial triangulation and camera system calibration can be performed. The research methodology implements automatic registration between the reference lidar DTM and dense photogrammetric point clouds which are derived using Integrated Sensing Orientation (ISO). This utilises a robust least squares surface matching algorithm, which is iterated to improve results by increasing the photogrammetric point quality through self-calibrating bundle adjustment. After a successful registration, well distributed lidar control points (LCPs) are automatically extracted from the transformed photogrammetric point clouds using predefined criteria. Finally, self-calibrating bundle block adjustment using different configurations of LCPs is performed to refine camera interior orientation (IO) parameters. The methodology has been assessed using imagery from a Vexcel UltraCamX large format camera. Analysis and the performance of the camera and its impact on the registration accuracy was performed. Furthermore, refinement of camera IO parameters was also applied using the derived LCPs. Tests also included investigations into the influence of the number and weight of LCPs in the accuracy of the bundle adjustment. Results from the UltraCamX block were compared with reference calibration results using ground control points in the test area, with good agreement found between the two approaches.

  16. The use of ERTS/LANDSAT imagery in relation to airborne remote sensing for terrain analysis in Western Queensland, Australia

    NASA Technical Reports Server (NTRS)

    Cole, M. M. (Principal Investigator); Owen-Jones, E. S.

    1976-01-01

    The author has identified the following significant results. LANDSAT 1 and 2 imagery contrast the geology of the Cloncurry-Dobbyn and the Gregory River-Mt. Isa areas very clearly. Known major structural features and lithological units are clearly displayed while, hitherto unknown lineaments were revealed. Throughout this area, similar rock types produce similar spectral signatures, e.g. quartzites produce light signatures, iron rich rocks produce dark signatures. More geological data are discernible at the 1:50,000 scale than on the 1:250,000 scale. Ore horizons may be identified at the 1:50,000 scale, particularly where they are associated with iron rich rocks. On the level plains north of Cloncurry, distinctive spectral signatures produced by the combined reflectances of plant cover, soils, and geology, distinguish different types of superficial deposits. Existing and former channels of the Cloncurry and Williams Rivers are distinguished at the 1:50,000 scale on both the LANDSAT 1 and 2 imagery. On the Cloncurry Plains, fence lines are discernible on the 1:50,000 LANDSAT 2 imagery.

  17. 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.

  18. Application of ERTS-1 Imagery to Flood Inundation Mapping

    NASA Technical Reports Server (NTRS)

    Hallberg, G. R.; Hoyer, B. E.; Rango, A.

    1973-01-01

    Ground data and a variety of low-altitude multispectral imagery were acquired for the East Nishnabotna River on September 14 and 15. This successful effort concluded that a near-visible infrared sensor could map inundated areas in late summer for at least three days after flood recession. ERTS-1 multispectral scanner subsystem (MSS) imagery of the area was obtained on September 18 and 19. Analysis of MSS imagery by IGSRSL, USGS, and NASA reinforced the conclusions of the low-altitude study while increasing the time period critical for imagery acquisition to at least 7 days following flood recession. The capability of satellite imagery to map late summer flooding at a scale of 1:250,000 is exhibited by the agreement of interpreted flood boundaries obtained from ERTS-1 imagery to boundaries mapped by low-altitude imagery and ground methods.

  19. 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

  20. Application of airborne thermal imagery to surveys of Pacific walrus

    USGS Publications Warehouse

    Burn, D.M.; Webber, M.A.; Udevitz, M.S.

    2006-01-01

    We conducted tests of airborne thermal imagery of Pacific walrus to determine if this technology can be used to detect walrus groups on sea ice and estimate the number of walruses present in each group. In April 2002 we collected thermal imagery of 37 walrus groups in the Bering Sea at spatial resolutions ranging from 1-4 m. We also collected high-resolution digital aerial photographs of the same groups. Walruses were considerably warmer than the background environment of ice, snow, and seawater and were easily detected in thermal imagery. We found a significant linear relation between walrus group size and the amount of heat measured by the thermal sensor at all 4 spatial resolutions tested. This relation can be used in a double-sampling framework to estimate total walrus numbers from a thermal survey of a sample of units within an area and photographs from a subsample of the thermally detected groups. Previous methods used in visual aerial surveys of Pacific walrus have sampled only a small percentage of available habitat, resulting in population estimates with low precision. Results of this study indicate that an aerial survey using a thermal sensor can cover as much as 4 times the area per hour of flight time with greater reliability than visual observation.

  1. Aerial Perspective Artistry

    ERIC Educational Resources Information Center

    Wolfe, Linda

    2010-01-01

    This article presents a lesson centering on aerial perspective artistry of students and offers suggestions on how art teachers should carry this project out. This project serves to develop students' visual perception by studying reproductions by famous artists. This lesson allows one to imagine being lured into a landscape capable of captivating…

  2. Aerial of the VAB

    NASA Technical Reports Server (NTRS)

    2000-01-01

    Even in this aerial view at KSC, the Vehicle Assembly Building is imposing. In front of it is the Launch Control Center. In the background is the Rotation/Processing Facility, next to the Banana Creek. In the foreground is the Saturn Causeway that leads to Launch Pads 39A and 39B.

  3. Aerial photographic reproductions

    USGS Publications Warehouse

    U.S. Geological Survey

    1971-01-01

    Geological Survey vertical aerial photography is obtained primarily for topographic and geologic mapping. Reproductions from this photography are usually satisfactory for general use. Because reproductions are not stocked, but are custom processed for each order, they cannot be returned for credit or refund.

  4. Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011.

    PubMed

    Shields, Timothy; Pinchoff, Jessie; Lubinda, Jailos; Hamapumbu, Harry; Searle, Kelly; Kobayashi, Tamaki; Thuma, Philip E; Moss, William J; Curriero, Frank C

    2016-05-31

    Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

  5. A comparison of Spectral Angle Mapper and Artificial Neural Network classifiers combined with Landsat TM imagery analysis for obtaining burnt area mapping.

    PubMed

    Petropoulos, George P; Vadrevu, Krishna Prasad; Xanthopoulos, Gavriil; Karantounias, George; Scholze, Marko

    2010-01-01

    Satellite remote sensing, with its unique synoptic coverage capabilities, can provide accurate and immediately valuable information on fire analysis and post-fire assessment, including estimation of burnt areas. In this study the potential for burnt area mapping of the combined use of Artificial Neural Network (ANN) and Spectral Angle Mapper (SAM) classifiers with Landsat TM satellite imagery was evaluated in a Mediterranean setting. As a case study one of the most catastrophic forest fires, which occurred near the capital of Greece during the summer of 2007, was used. The accuracy of the two algorithms in delineating the burnt area from the Landsat TM imagery, acquired shortly after the fire suppression, was determined by the classification accuracy results of the produced thematic maps. In addition, the derived burnt area estimates from the two classifiers were compared with independent estimates available for the study region, obtained from the analysis of higher spatial resolution satellite data. In terms of the overall classification accuracy, ANN outperformed (overall accuracy 90.29%, Kappa coefficient 0.878) the SAM classifier (overall accuracy 83.82%, Kappa coefficient 0.795). Total burnt area estimates from the two classifiers were found also to be in close agreement with the other available estimates for the study region, with a mean absolute percentage difference of ≈ 1% for ANN and ≈ 6.5% for SAM. The study demonstrates the potential of the examined here algorithms in detecting burnt areas in a typical Mediterranean setting.

  6. A Comparison of Spectral Angle Mapper and Artificial Neural Network Classifiers Combined with Landsat TM Imagery Analysis for Obtaining Burnt Area Mapping

    PubMed Central

    Petropoulos, George P.; Vadrevu, Krishna Prasad; Xanthopoulos, Gavriil; Karantounias, George; Scholze, Marko

    2010-01-01

    Satellite remote sensing, with its unique synoptic coverage capabilities, can provide accurate and immediately valuable information on fire analysis and post-fire assessment, including estimation of burnt areas. In this study the potential for burnt area mapping of the combined use of Artificial Neural Network (ANN) and Spectral Angle Mapper (SAM) classifiers with Landsat TM satellite imagery was evaluated in a Mediterranean setting. As a case study one of the most catastrophic forest fires, which occurred near the capital of Greece during the summer of 2007, was used. The accuracy of the two algorithms in delineating the burnt area from the Landsat TM imagery, acquired shortly after the fire suppression, was determined by the classification accuracy results of the produced thematic maps. In addition, the derived burnt area estimates from the two classifiers were compared with independent estimates available for the study region, obtained from the analysis of higher spatial resolution satellite data. In terms of the overall classification accuracy, ANN outperformed (overall accuracy 90.29%, Kappa coefficient 0.878) the SAM classifier (overall accuracy 83.82%, Kappa coefficient 0.795). Total burnt area estimates from the two classifiers were found also to be in close agreement with the other available estimates for the study region, with a mean absolute percentage difference of ∼1% for ANN and ∼6.5% for SAM. The study demonstrates the potential of the examined here algorithms in detecting burnt areas in a typical Mediterranean setting. PMID:22294909

  7. Processing of SeaMARC swath sonar imagery

    SciTech Connect

    Pratson, L.; Malinverno, A.; Edwards, M.; Ryan, W. )

    1990-05-01

    Side-scan swath sonar systems have become an increasingly important means of mapping the sea floor. Two such systems are the deep-towed, high-resolution SeaMARC I sonar, which has a variable swath width of up to 5 km, and the shallow-towed, lower-resolution SeaMARC II sonar, which has a swath width of 10 km. The sea-floor imagery of acoustic backscatter output by the SeaMARC sonars is analogous to aerial photographs and airborne side-looking radar images of continental topography. Geologic interpretation of the sea-floor imagery is greatly facilitated by image processing. Image processing of the digital backscatter data involves removal of noise by median filtering, spatial filtering to remove sonar scans of anomalous intensity, across-track corrections to remove beam patterns caused by nonuniform response of the sonar transducers to changes in incident angle, and contrast enhancement by histogram equalization to maximize the available dynamic range. Correct geologic interpretation requires submarine structural fabrics to be displayed in their proper locations and orientations. Geographic projection of sea-floor imagery is achieved by merging the enhanced imagery with the sonar vehicle navigation and correcting for vehicle attitude. Co-registration of bathymetry with sonar imagery introduces sea-floor relief and permits the imagery to be displayed in three-dimensional perspectives, furthering the ability of the marine geologist to infer the processes shaping formerly hidden subsea terrains.

  8. A Spherical Aerial Terrestrial Robot

    NASA Astrophysics Data System (ADS)

    Dudley, Christopher J.

    This thesis focuses on the design of a novel, ultra-lightweight spherical aerial terrestrial robot (ATR). The ATR has the ability to fly through the air or roll on the ground, for applications that include search and rescue, mapping, surveillance, environmental sensing, and entertainment. The design centers around a micro-quadcopter encased in a lightweight spherical exoskeleton that can rotate about the quadcopter. The spherical exoskeleton offers agile ground locomotion while maintaining characteristics of a basic aerial robot in flying mode. A model of the system dynamics for both modes of locomotion is presented and utilized in simulations to generate potential trajectories for aerial and terrestrial locomotion. Details of the quadcopter and exoskeleton design and fabrication are discussed, including the robot's turning characteristic over ground and the spring-steel exoskeleton with carbon fiber axle. The capabilities of the ATR are experimentally tested and are in good agreement with model-simulated performance. An energy analysis is presented to validate the overall efficiency of the robot in both modes of locomotion. Experimentally-supported estimates show that the ATR can roll along the ground for over 12 minutes and cover the distance of 1.7 km, or it can fly for 4.82 minutes and travel 469 m, on a single 350 mAh battery. Compared to a traditional flying-only robot, the ATR traveling over the same distance in rolling mode is 2.63-times more efficient, and in flying mode the system is only 39 percent less efficient. Experimental results also demonstrate the ATR's transition from rolling to flying mode.

  9. Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management

    NASA Astrophysics Data System (ADS)

    Rango, Albert; Laliberte, Andrea; Herrick, Jeffrey E.; Winters, Craig; Havstad, Kris; Steele, Caiti; Browning, Dawn

    2009-08-01

    Rangeland comprises as much as 70% of the Earth's land surface area. Much of this vast space is in very remote areas that are expensive and often impossible to access on the ground. Unmanned Aerial Vehicles (UAVs) have great potential for rangeland management. UAVs have several advantages over satellites and piloted aircraft: they can be deployed quickly and repeatedly; they are less costly and safer than piloted aircraft; they are flexible in terms of flying height and timing of missions; and they can obtain imagery at sub-decimeter resolution. This hyperspatial imagery allows for quantification of plant cover, composition, and structure at multiple spatial scales. Our experiments have shown that this capability, from an off-the-shelf mini-UAV, is directly applicable to operational agency needs for measuring and monitoring. For use by operational agencies to carry out their mandated responsibilities, various requirements must be met: an affordable and reliable platform; a capability for autonomous, low altitude flights; takeoff and landing in small areas surrounded by rugged terrain; and an easily applied data analysis methodology. A number of image processing and orthorectification challenges have been or are currently being addressed, but the potential to depict the land surface commensurate with field data perspectives across broader spatial extents is unrivaled.

  10. A qualitative evaluation of Landsat imagery of Australian rangelands

    USGS Publications Warehouse

    Graetz, R.D.; Carneggie, David M.; Hacker, R.; Lendon, C.; Wilcox, D.G.

    1976-01-01

    The capability of multidate, multispectral ERTS-1 imagery of three different rangeland areas within Australia was evaluated for its usefulness in preparing inventories of rangeland types, assessing on a broad scale range condition within these rangeland types, and assessing the response of rangelands to rainfall events over large areas. For the three divergent rangeland test areas, centered on Broken W, Alice Springs and Kalgoorlie, detailed interpretation of the imagery only partially satisfied the information requirements set. It was most useful in the Broken Hill area where fenceline contrasts in range condition were readily visible. At this and the other sites an overstorey of trees made interpretation difficult. Whilst the low resolution characteristics and the lack of stereoscopic coverage hindered interpretation it was felt that this type of imagery with its vast coverage, present low cost and potential for repeated sampling is a useful addition to conventional aerial photography for all rangeland types.

  11. Automatic target detection in UAV imagery using image formation conditions

    NASA Astrophysics Data System (ADS)

    Lin, Huibao; Si, Jennie; Abousleman, Glen P.

    2003-09-01

    This paper is about automatic target detection (ATD) in unmanned aerial vehicle (UAV) imagery. Extracting reliable features under all conditions from a 2D projection of a target in UAV imagery is a difficult problem. However, since the target size information is usually invariant to the image formation proces, we propose an algorithm for automatically estimating the size of a 3D target by using its 2D projection. The size information in turn becomes an important feature to be used in a knowledge-driven, multi-resolution-based algorithm for automatically detecting targets in UAV imagery. Experimental results show that our proposed ATD algorithm provides outstanding detection performance, while significantly reducing the false alarm rate and the computational complexity.

  12. Forestry, geology and hydrological investigations from ERTS-1 imagery in two areas of Ecuador, South America

    NASA Technical Reports Server (NTRS)

    Moreno, N. V. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. In the Oriente area, well-drained forests containing commercially valuable hardwoods can be recognized confidently and delineated quickly on the ERTS imagery. In the tropical rainforest, ERTS can provide an abundance of inferential information about large scale geologic structures. ERTS imagery is better than normal aerial photography for recognizing linears. The imagery is particularly useful for updating maps of the distributary system of the Guagas River Basin and of any other river with a similarly rapid changing channel pattern.

  13. Automatic Building Extraction and Roof Reconstruction in 3k Imagery Based on Line Segments

    NASA Astrophysics Data System (ADS)

    Köhn, A.; Tian, J.; Kurz, F.

    2016-06-01

    We propose an image processing workflow to extract rectangular building footprints using georeferenced stereo-imagery and a derivative digital surface model (DSM) product. The approach applies a line segment detection procedure to the imagery and subsequently verifies identified line segments individually to create a footprint on the basis of the DSM. The footprint is further optimized by morphological filtering. Towards the realization of 3D models, we decompose the produced footprint and generate a 3D point cloud from DSM height information. By utilizing the robust RANSAC plane fitting algorithm, the roof structure can be correctly reconstructed. In an experimental part, the proposed approach has been performed on 3K aerial imagery.

  14. Evolution of a highly dilatant fault zone in the grabens of Canyonlands National Park, Utah/USA - integrating field work, ground penetrating radar and airborne imagery analysis

    NASA Astrophysics Data System (ADS)

    Kettermann, M.; Grützner, C.; van Gent, H. W.; Urai, J. L.; Reicherter, K.; Mertens, J.

    2015-03-01

    The grabens of the Canyonlands National Park are a young and active system of sub-parallel, arcuate grabens, whose evolution is the result of salt movement in the subsurface and a slight regional tilt of the faulted strata. We present results of ground penetrating radar surveys in combination with field observations and analysis of high resolution airborne imagery. GPR data show intense faulting of the Quaternary sediments at the flat graben floors, implying a more complex fault structure than visible at the surface. Direct measurements of heave and throw at several locations to infer fault dips at depth, combined with observations of primary joint surfaces in the upper 100 m suggest a model of the highly dilatant fault geometry in profile. Sinkholes observed in the field as well as in airborne imagery give insights in local massive dilatancy and show where water and sediments are transported underground. Based on correlations of paleosols observed in outcrops and GPR profiles, we argue that the grabens in Canyonlands National Park are either older than previously assumed, or that sedimentation rates were much higher in the Pleistocene.

  15. Evolution of a highly dilatant fault zone in the grabens of Canyonlands National Park, Utah, USA - integrating fieldwork, ground-penetrating radar and airborne imagery analysis

    NASA Astrophysics Data System (ADS)

    Kettermann, M.; Grützner, C.; van Gent, H. W.; Urai, J. L.; Reicherter, K.; Mertens, J.

    2015-07-01

    The grabens of Canyonlands National Park are a young and active system of sub-parallel, arcuate grabens, whose evolution is the result of salt movement in the subsurface and a slight regional tilt of the faulted strata. We present results of ground-penetrating radar (GPR) surveys in combination with field observations and analysis of high-resolution airborne imagery. GPR data show intense faulting of the Quaternary sediments at the flat graben floors, implying a more complex fault structure than visible at the surface. Direct measurements of heave and throw at several locations to infer fault dips at depth, combined with observations of primary joint surfaces in the upper 100 m, suggest a highly dilatant fault geometry. Sinkholes observed in the field as well as in airborne imagery give insights in local dilatancy and show where water and sediments are transported underground. Based on correlations of paleosols observed in outcrops and GPR profiles, we argue that either the grabens in Canyonlands National Park are older than previously assumed or that sedimentation rates were much higher in the Pleistocene.

  16. Tree Crown Mapping in Managed Woodlands (Parklands) of Semi-Arid West Africa Using WorldView-2 Imagery and Geographic Object Based Image Analysis

    PubMed Central

    Karlson, Martin; Reese, Heather; Ostwald, Madelene

    2014-01-01

    Detailed information on tree cover structure is critical for research and monitoring programs targeting African woodlands, including agroforestry parklands. High spatial resolution satellite imagery represents a potentially effective alternative to field-based surveys, but requires the development of accurate methods to automate information extraction. This study presents a method for tree crown mapping based on Geographic Object Based Image Analysis (GEOBIA) that use spectral and geometric information to detect and delineate individual tree crowns and crown clusters. The method was implemented on a WorldView-2 image acquired over the parklands of Saponé, Burkina Faso, and rigorously evaluated against field reference data. The overall detection rate was 85.4% for individual tree crowns and crown clusters, with lower accuracies in areas with high tree density and dense understory vegetation. The overall delineation error (expressed as the difference between area of delineated object and crown area measured in the field) was 45.6% for individual tree crowns and 61.5% for crown clusters. Delineation accuracies were higher for medium (35–100 m2) and large (≥100 m2) trees compared to small (<35 m2) trees. The results indicate potential of GEOBIA and WorldView-2 imagery for tree crown mapping in parkland landscapes and similar woodland areas. PMID:25460815

  17. Auditory imagery: empirical findings.

    PubMed

    Hubbard, Timothy L

    2010-03-01

    The empirical literature on auditory imagery is reviewed. Data on (a) imagery for auditory features (pitch, timbre, loudness), (b) imagery for complex nonverbal auditory stimuli (musical contour, melody, harmony, tempo, notational audiation, environmental sounds), (c) imagery for verbal stimuli (speech, text, in dreams, interior monologue), (d) auditory imagery's relationship to perception and memory (detection, encoding, recall, mnemonic properties, phonological loop), and (e) individual differences in auditory imagery (in vividness, musical ability and experience, synesthesia, musical hallucinosis, schizophrenia, amusia) are considered. It is concluded that auditory imagery (a) preserves many structural and temporal properties of auditory stimuli, (b) can facilitate auditory discrimination but interfere with auditory detection, (c) involves many of the same brain areas as auditory perception, (d) is often but not necessarily influenced by subvocalization, (e) involves semantically interpreted information and expectancies, (f) involves depictive components and descriptive components, (g) can function as a mnemonic but is distinct from rehearsal, and (h) is related to musical ability and experience (although the mechanisms of that relationship are not clear). PMID:20192565

  18. Auditory imagery: empirical findings.

    PubMed

    Hubbard, Timothy L

    2010-03-01

    The empirical literature on auditory imagery is reviewed. Data on (a) imagery for auditory features (pitch, timbre, loudness), (b) imagery for complex nonverbal auditory stimuli (musical contour, melody, harmony, tempo, notational audiation, environmental sounds), (c) imagery for verbal stimuli (speech, text, in dreams, interior monologue), (d) auditory imagery's relationship to perception and memory (detection, encoding, recall, mnemonic properties, phonological loop), and (e) individual differences in auditory imagery (in vividness, musical ability and experience, synesthesia, musical hallucinosis, schizophrenia, amusia) are considered. It is concluded that auditory imagery (a) preserves many structural and temporal properties of auditory stimuli, (b) can facilitate auditory discrimination but interfere with auditory detection, (c) involves many of the same brain areas as auditory perception, (d) is often but not necessarily influenced by subvocalization, (e) involves semantically interpreted information and expectancies, (f) involves depictive components and descriptive components, (g) can function as a mnemonic but is distinct from rehearsal, and (h) is related to musical ability and experience (although the mechanisms of that relationship are not clear).

  19. Tobacco imagery on New Zealand television 2002–2004

    PubMed Central

    McGee, Rob; Ketchel, Juanita

    2006-01-01

    Considerable emphasis has been placed on the importance of tobacco imagery in the movies as one of the “drivers” of smoking among young people. Findings are presented from a content analysis of 98 hours of prime‐time programming on New Zealand television 2004, identifying 152 scenes with tobacco imagery, and selected characteristics of those scenes. About one in four programmes contained tobacco imagery, most of which might be regarded as “neutral or positive”. This amounted to about two scenes containing such imagery for every hour of programming. A comparison with our earlier content analysis of programming in 2002 indicated little change in the level of tobacco imagery. The effect of this imagery in contributing to young viewers taking up smoking, and sustaining the addiction among those already smoking, deserves more research attention. PMID:16998178

  20. Quantifying gully erosion contribution from morphodynamic analysis of historical aerial photographs in a large catchment SW Spain

    NASA Astrophysics Data System (ADS)

    Hayas, Antonio; Giráldez, Juan V.; Laguna, Ana; Peña, Peña; Vanwalleghem, Tom

    2015-04-01

    Gully erosion is widely recognized as an important erosion process and source of sediment, especially in Mediterranean basins. Recent advances in monitoring techniques, such as ground-based LiDAR, drone-bounded cameras or photoreconstruction, allow quantifying gully erosion rates with unprecedented accuracy. However, many studies only focus on gully growth during a short period. In agricultural areas, farmers frequently erase gullies artificially. Over longer time scales, this results in an important dynamic of gully growth and infilling. Also, given the significant temporal variability of precipitation, land use and the proper gully erosion processes, gully growth is non-linear over time. This study therefore aims at analyzing gully morphodynamics over a long time scale (1957-2011) in a large catchment in order to quantify gully erosion processes and its contribution to overall sediment dynamics. The 20 km2 study area is located in SW Spain. The extension of the gully network was digitized by photographic interpretation based on aerial photographs from 1957, 1981, 1985, 1999, 2002, 2005, 2007, 2009 and 2011. Gully width was measured at representative control points for each of these years. During this period, the dominant land use changed considerably from herbaceous crops to olive orchards. A field campaign was conducted in 2014 to measure current gully width and depth. Total gully volume and uncertainty was determined by Monte Carlo-based simulations of gully cross-sectional area for unmeasured sections. The extension of the gully network both increased and decreased in the study period. Gully density varied between 1.93 km km-2 in 1957, with a minimum of 1.37 km km-2 in 1981 and a maximum of 5.40 km km-2 in 2011. Gully width estimated in selected points from the orthophotos range between 0.9 m and 59.2 m, and showed a good lognormal fit. Field campaigns results in a collection of cross-section measures with gullies widths between 1.87 and 28.5 m and depths from

  1. Long and short-term spatial processes analysis of an acacia tree population using a single aerial photograph with near infra-red band

    NASA Astrophysics Data System (ADS)

    Isaacson, Sivan; Blumberg, Dan G.; Rachmilevitch, Shimon; Ephrath, Jhonathan E.

    2014-05-01

    Hyper-arid zones are characterized by highly sparse vegetation cover. Monitoring vegetation dynamics in hyper-arid zones is important because any reduction in the vegetation cover in these areas can lead to a considerable reduction in the carrying capacity of the ecological system. Remote sensing expands the spatial and temporal database and is thus a powerful tool for long-term monitoring in arid zones, where access is limited and long-term ground data are rarely available. The main goal of this research was to study both the long-term and short-term spatial processes affecting the acacia population, by using information from a single, three bands color infrared (CIR) aerial photograph (green, red and near infrared). CIR images enable us to obtain information about photosynthetically active biomass by using vegetation indices such as NDVI. A map of individual acacia trees that was extracted from a CIR aerial photograph of Wadi Ktora allowed us to examine the distribution pattern of the trees size and foliage health status (NDVI). Tree size distribution was used as an indicator of long-term (decades) geo-hydrologic spatial processes effecting the acacia population. The tree health status distribution was used as an indicator for short-term (months to a few years) geo-hydrologic spatial processes, such as the paths of recent flashfloods events. Comparison of the tree size distribution and NDVI values distribution enabled us to differentiate between long-term and short-term processes that brought the population to its present state. The spatial analysis revealed that both the tree size and NDVI distribution patterns were significantly clustered, suggesting that the processes responsible for tree size and tree health status do have a spatial expression. Furthermore, each of the attributes has a different distribution and unique clustering location. We suggest that the lack of spatial correlation between tree size and health status is a result of spatial

  2. Time-series analysis of multi-resolution optical imagery for quantifying forest cover loss in Sumatra and Kalimantan, Indonesia

    NASA Astrophysics Data System (ADS)

    Broich, Mark; Hansen, Matthew C.; Potapov, Peter; Adusei, Bernard; Lindquist, Erik; Stehman, Stephen V.

    2011-04-01

    Monitoring loss of humid tropical forests via remotely sensed imagery is critical for a number of environmental monitoring objectives, including carbon accounting, biodiversity, and climate modeling science applications. Landsat imagery, provided free of charge by the U.S. Geological Survey Center for Earth Resources Observation and Science (USGS/EROS), enables consistent and timely forest cover loss updates from regional to biome scales. The Indonesian islands of Sumatra and Kalimantan are a center of significant forest cover change within the humid tropics with implications for carbon dynamics, biodiversity maintenance and local livelihoods. Sumatra and Kalimantan feature poor observational coverage compared to other centers of humid tropical forest change, such as Mato Grosso, Brazil, due to the lack of ongoing acquisitions from nearby ground stations and the persistence of cloud cover obscuring the land surface. At the same time, forest change in Indonesia is transient and does not always result in deforestation, as cleared forests are rapidly replaced by timber plantations and oil palm estates. Epochal composites, where single best observations are selected over a given time interval and used to quantify change, are one option for monitoring forest change in cloudy regions. However, the frequency of forest cover change in Indonesia confounds the ability of image composite pairs to quantify all change. Transient change occurring between composite periods is often missed and the length of time required for creating a cloud-free composite often obscures change occurring within the composite period itself. In this paper, we analyzed all Landsat 7 imagery with <50% cloud cover and data and products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to quantify forest cover loss for Sumatra and Kalimantan from 2000 to 2005. We demonstrated that time-series approaches examining all good land observations are more accurate in mapping forest cover change in

  3. Bi-Temporal Analysis of High-Resolution Satellite Imagery in Support of a Forest Conservation Program in Western Uganda

    NASA Astrophysics Data System (ADS)

    Thomas, N.; Lambin, E.; Audy, R.; Biryahwaho, B.; de Laat, J.; Jayachandran, S.

    2014-12-01

    Recent studies in land use sustainability have shown the conservation value of even small forest fragments in tropical smallholder agricultural regions. Forest patches provide important ecosystem services, wildlife habitat, and support human livelihoods. Our study incorporates multiple dates of high-resolution Quickbird imagery to map forest disturbance and regrowth in a smallholder agricultural landscape in western Uganda. This work is in support of a payments for ecosystem services (PES) project which uses a randomized controlled trial to assess the efficacy of PES for enhancing forest conservation. The research presented here details the remote sensing phase of this project. We developed an object-based methodology for detecting forest change from high-resolution imagery that calculates per class image reflectance and change statistics to determine persistent forest, non-forest, forest gain, and forest loss classes. The large study area (~ 2,400 km2) necessitated using a combination of 10 different image pairs of varying seasonality, sun angle, and viewing angle. We discuss the impact of these factors on mapping results. Reflectance data was used in conjunction with texture measures and knowledge-driven modeling to derive forest change maps. First, baseline Quickbird images were mapped into tree cover and non-tree categories based on segmented image objects and field inventory data, applied through a classification and regression tree (CART) classifier. Then a bi-temporal segmentation layer was generated and a series of object metrics from both image dates were extracted. A sample set of persistent forest objects that remained undisturbed was derived from the tree cover map and the red band (B3) change values. We calculated a variety of statistical indices for these persistent tree cover objects from the post- survey imagery to create maps of both forest cover loss and forest cover gain. These results are compared to visually assessed image objects in addition

  4. Favourable uranium-phosphate exploration trends guided by the application of statistical factor analysis technique on the aerial gamma spectrometric data in Syrian desert (Area-1), Syria

    NASA Astrophysics Data System (ADS)

    Asfahani, J.; Al-Hent, R.; Aissa, M.

    2016-02-01

    A scored lithological map including 10 radiometric units is established through applying factor analysis approach to aerial spectrometric data of Area-1, Syrian desert, which includes Ur, eU, eTh, K%, eU/eTh, eU/K%, and eTh/K%. A model of four rotated factors F1, F2, F3, and F4 is adapted for representing 234,829 data measured points in Area-1, where 86% of total data variance is interpreted. A geological scored pseudo-section derived from the lithological scored map is established and analyzed in order to show the possible stratigraphic and structural traps for uranium occurrences associated with phosphate deposits in the studied Area-1. These identified traps presented in this paper need detailed investigation and must be necessarily followed and checked by ground validations and sub