Science.gov

Sample records for aerial imagery analysis

  1. Analysis and Exploitation of Automatically Generated Scene Structure from Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Nilosek, David R.

    The recent advancements made in the field of computer vision, along with the ever increasing rate of computational power has opened up opportunities in the field of automated photogrammetry. Many researchers have focused on using these powerful computer vision algorithms to extract three-dimensional point clouds of scenes from multi-view imagery, with the ultimate goal of creating a photo-realistic scene model. However, geographically accurate three-dimensional scene models have the potential to be exploited for much more than just visualization. This work looks at utilizing automatically generated scene structure from near-nadir aerial imagery to identify and classify objects within the structure, through the analysis of spatial-spectral information. The limitation to this type of imagery is imposed due to the common availability of this type of aerial imagery. Popular third-party computer-vision algorithms are used to generate the scene structure. A voxel-based approach for surface estimation is developed using Manhattan-world assumptions. A surface estimation confidence metric is also presented. This approach provides the basis for further analysis of surface materials, incorporating spectral information. Two cases of spectral analysis are examined: when additional hyperspectral imagery of the reconstructed scene is available, and when only R,G,B spectral information can be obtained. A method for registering the surface estimation to hyperspectral imagery, through orthorectification, is developed. Atmospherically corrected hyperspectral imagery is used to assign reflectance values to estimated surface facets for physical simulation with DIRSIG. A spatial-spectral region growing-based segmentation algorithm is developed for the R,G,B limited case, in order to identify possible materials for user attribution. Finally, an analysis of the geographic accuracy of automatically generated three-dimensional structure is performed. An end-to-end, semi-automated, workflow

  2. Texture and scale in object-based analysis of subdecimeter resolution unmanned aerial vehicle (UAV) imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Imagery acquired with unmanned aerial vehicles (UAVs) has great potential for incorporation into natural resource monitoring protocols due to their ability to be deployed quickly and repeatedly and to fly at low altitudes. While the imagery may have high spatial resolution, the spectral resolution i...

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Environmental applications utilizing digital aerial imagery

    SciTech Connect

    Monday, H.M.

    1995-06-01

    This paper discusses the use of satellite imagery, aerial photography, and computerized airborne imagery as applied to environmental mapping, analysis, and monitoring. A project conducted by the City of Irving, Texas involves compliance with national pollutant discharge elimination system (NPDES) requirements stipulated by the Environmental Protection Agency. The purpose of the project was the development and maintenance of a stormwater drainage utility. Digital imagery was collected for a portion of the city to map the City`s porous and impervious surfaces which will then be overlaid with property boundaries in the City`s existing Geographic information System (GIS). This information will allow the City to determine an equitable tax for each land parcel according to the amount of water each parcel is contributing to the stormwater system. Another project involves environmental compliance for warm water discharges created by utility companies. Environmental consultants are using digital airborne imagery to analyze thermal plume affects as well as monitoring power generation facilities. A third project involves wetland restoration. Due to freeway and other forms of construction, plus a major reduction of fresh water supplies, the Southern California coastal wetlands are being seriously threatened. These wetlands, rich spawning grounds for plant and animal life, are home to thousands of waterfowl and shore birds who use this habitat for nesting and feeding grounds. Under the leadership of Southern California Edison (SCE) and CALTRANS (California Department of Transportation), several wetland areas such as the San Dieguito Lagoon (Del Mar, California), the Sweetwater Marsh (San Diego, California), and the Tijuana Estuary (San Diego, California) are being restored and closely monitored using digital airborne imagery.

  8. 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.

  9. 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).

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

    DOE PAGESBeta

    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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. A semantic approach to the efficient integration of interactive and automatic target recognition systems for the analysis of complex infrastructure from aerial imagery

    NASA Astrophysics Data System (ADS)

    Bauer, A.; Peinsipp-Byma, E.

    2008-04-01

    The analysis of complex infrastructure from aerial imagery, for instance a detailed analysis of an airfield, requires the interpreter, besides to be familiar with the sensor's imaging characteristics, to have a detailed understanding of the infrastructure domain. The required domain knowledge includes knowledge about the processes and functions involved in the operation of the infrastructure, the potential objects used to provide those functions and their spatial and functional interrelations. Since it is not possible yet to provide reliable automatic object recognition (AOR) for the analysis of such complex scenes, we developed systems to support a human interpreter with either interactive approaches, able to assist the interpreter with previously acquired expert knowledge about the domain in question, or AOR methods, capable of detecting, recognizing or analyzing certain classes of objects for certain sensors. We believe, to achieve an optimal result at the end of an interpretation process in terms of efficiency and effectivity, it is essential to integrate both interactive and automatic approaches to image interpretation. In this paper we present an approach inspired by the advancing semantic web technology to represent domain knowledge, the capabilities of available AOR modules and the image parameters in an explicit way. This enables us to seamlessly extend an interactive image interpretation environment with AOR modules in a way that we can automatically select suitable AOR methods for the current subtask, focus them on an appropriate area of interest and reintegrate their results into the environment.

  18. Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery

    NASA Astrophysics Data System (ADS)

    Ma, Lei; Cheng, Liang; Li, Manchun; Liu, Yongxue; Ma, Xiaoxue

    2015-04-01

    Unmanned Aerial Vehicle (UAV) has been used increasingly for natural resource applications in recent years due to their greater availability and the miniaturization of sensors. In addition, Geographic Object-Based Image Analysis (GEOBIA) has received more attention as a novel paradigm for remote sensing earth observation data. However, GEOBIA generates some new problems compared with pixel-based methods. In this study, we developed a strategy for the semi-automatic optimization of object-based classification, which involves an area-based accuracy assessment that analyzes the relationship between scale and the training set size. We found that the Overall Accuracy (OA) increased as the training set ratio (proportion of the segmented objects used for training) increased when the Segmentation Scale Parameter (SSP) was fixed. The OA increased more slowly as the training set ratio became larger and a similar rule was obtained according to the pixel-based image analysis. The OA decreased as the SSP increased when the training set ratio was fixed. Consequently, the SSP should not be too large during classification using a small training set ratio. By contrast, a large training set ratio is required if classification is performed using a high SSP. In addition, we suggest that the optimal SSP for each class has a high positive correlation with the mean area obtained by manual interpretation, which can be summarized by a linear correlation equation. We expect that these results will be applicable to UAV imagery classification to determine the optimal SSP for each class.

  19. 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.

  20. Comparison of hyperspectral imagery with aerial photography and multispectral imagery for mapping broom snakeweed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Broom snakeweed [Gutierrezia sarothrae (Pursh.) Britt. and Rusby] is one of the most widespread and abundant rangeland weeds in western North America. The objectives of this study were to evaluate airborne hyperspectral imagery and compare it with aerial color-infrared (CIR) photography and multispe...

  1. 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

  2. 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.

  3. 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.

  4. Supervised Material Classification in Oblique Aerial Imagery Using Gabor Filter Features

    NASA Astrophysics Data System (ADS)

    Harris, Michael L.

    RIT's Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool allows modeling of real world scenes to create synthetic imagery for sensor design and analysis, trade studies, algorithm validation, and training image analysts. To increase model construction speed, and the diversity and size of synthetic scenes which can be generated it is desirable to automatically segment real world imagery into different material types and import a material classmap into DIRSIG. This work contributes a methodology based on standard texture recognition techniques to supervised classification of material types in oblique aerial imagery. Oblique imagery provides many challenges for texture recognition due to illumination changes with view angle, projective distortions, occlusions and self shadowing. It is shown that features derived from a set of rotationally invariant bandpass filters fused with color channel information can provide supervised classification accuracies up to 70% with minimal training data.

  5. 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

  6. 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.

  7. 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

  8. Three-dimensional panoramic terrain reconstruction from aerial imagery

    NASA Astrophysics Data System (ADS)

    Yang, Ahua; Li, Xuejun; Xie, Jianwei; Wei, Yong

    2013-01-01

    A complete solution for effectively, automatically, and accurately reconstructing the three-dimensional (3-D) panoramic terrain from aerial imagery is presented. With enough premeasured and identified georeferences, we first estimate every camera's accurate intrinsic and extrinsic parameters by implementing bundle adjustment, which is introduced in detail. Afterward, the adjacent relationship of imagery is acquired from the cameras' position parameters. In addition, the formulas for corresponding area prediction and image rectification are derived according to the camera parameters. Subsequently, feature-based matching is conducted between adjacent image pairs to provide much more constraints for bundle adjustment. Area-based matching is applied to pairs of horizontal epipolar imagery for dense correspondence to produce dense spatial point cloud. Eventually, the mosaicked digital ortho map and digital elevation model of the whole imaging area are produced automatically by a series of steps including spatial intersection, Tin generation, differential correction, and color blending. Experimental results show that the root mean square (RMS) residual errors of check points in planimetry and altitude are, respectively, 0.039 and 0.170 m, demonstrating the high accuracy of camera orientation. The visualized panoramic 3-D realistic scene validates the feasibility and effectiveness of the proposed solution.

  9. Robust vehicle detection in low-resolution aerial imagery

    NASA Astrophysics Data System (ADS)

    Sahli, Samir; Ouyang, Yueh; Sheng, Yunlong; Lavigne, Daniel A.

    2010-04-01

    We propose a feature-based approach for vehicle detection in aerial imagery with 11.2 cm/pixel resolution. The approach is free of all constraints related to the vehicles appearance. The scale-invariant feature transform (SIFT) is used to extract keypoints in the image. The local structure in the neighbouring of the SIFT keypoints is described by 128 gradient orientation based features. A Support Vector Machine is used to create a model which is able to predict if the SIFT keypoints belong to or not to car structures in the image. The collection of SIFT keypoints with car label are clustered in the geometric space into subsets and each subset is associated to one car. This clustering is based on the Affinity Propagation algorithm modified to take into account specific spatial constraint related to geometry of cars at the given resolution.

  10. 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

  11. 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.

  12. 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...

  13. Characterisation of recently retrieved aerial photographs of Ethiopia (1935-1941) and their fusion with current remotely sensed imagery for retrospective geomorphological analysis

    NASA Astrophysics Data System (ADS)

    Nyssen, Jan; Gebremeskel, Gezahegne; Mohamed, Sultan; Petrie, Gordon; Seghers, Valérie; Meles Hadgu, Kiros; De Maeyer, Philippe; Haile, Mitiku; Frankl, Amaury

    2013-04-01

    8281 assemblages of aerial photographs (APs) acquired by the 7a Sezione Topocartografica during the Italian occupation of Ethiopia (1935-1941) have recently been discovered, scanned and organised. The oldest APs of the country that are known so far were taken in the period 1958-1964. The APs of the 1930s were analysed for their technical characteristics, scale, flight lines, coverage, use in topographic mapping, and potential future uses. The APs over Ethiopia in 1935-1941 are presented as assemblages on approx. 50 cm x 20 cm cardboard tiles, each holding a label, one nadir-pointing photograph flanked by two low-oblique photographs and one high-oblique photograph. The four APs were exposed simultaneously and were taken across the flight line; the high-oblique photograph is presented alternatively at left and at right; there is approx. 60% overlap between subsequent sets of APs. One of Santoni's glass plate multi-cameras was used, with focal length of 178 mm, flight height at 4000-4500 m a.s.l., which results in an approximate scale of 1:11 500 for the central photograph and 1:16 000 to 1:18 000 for the low-oblique APs. The surveyors oriented themselves with maps of Ethiopia at 1:400 000 scale, compiled in 1934. The flights present a dense AP coverage of Northern Ethiopia, where they were acquired in the context of upcoming battles with the Ethiopian army. Several flights preceded the later advance of the Italian army southwards towards the capital Addis Ababa. Further flights took place in central Ethiopia for civilian purposes. As of 1936, the APs were used to prepare highly detailed topographic maps at 1:100 000 scale. These APs (1935-1941) together with APs of 1958-1964, 1994 and recent high-resolution satellite imagery are currently being used in spatially explicit change studies of land cover, land management and (hydro)geomorphology in Ethiopia over a time span of almost 80 years, the first results of which will be presented.

  14. 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

  15. 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.

  16. Physical controls and patterns of recruitment on the Drôme River (SE France): An analysis based on a chronosequence of high resolution aerial imagery

    NASA Astrophysics Data System (ADS)

    Piegay, H.; Stella, J. C.; Raepple, B.

    2014-12-01

    Along with the recent recognition of the role of vegetation in influencing channel hydraulics, and thus fluvial morphology comes the need for scientific research on vegetation recruitment and its control factors. Flood disturbance is known to create a suitable physical template for the establishment of woody pioneers. Sapling recruitment patterns and underlying physical controls were investigated on a 5 km braided reach of the Drôme River in South-eastern France, following the 2003 50-year flood event. The approach was based on the analysis of a chronosequence of high resolution aerial images acquired yearly between 2005 and 2011, complemented by airborne LiDAR data and field observations. The study highlights how physical complexity induced by natural variations in hydro-climatic and consequently hydro-geomorphic conditions facilitates variable patterns of recruitment. The initial post-flood vegetative units, which covered up to 10% of the total active channel area in 2005, was seen to double within six years. The variability of hydro-climatic conditions was reflected in the temporal and spatial patterns of recruitment, with a pronounced peak of vegetation expansion in 2007 and a decreasing trend following higher flows in 2009. Recruitment was further seen to be sustained in a variety of geomorphic units, which showed different probabilities and patterns of recruitment. Active channels were the prominent geomorphic unit in terms of total biomass development, while in-channel wood units showed the highest probability for recruitment. Vegetation recruitment understanding is becoming crucial for predicting fluvial system evolution in different hydroclimatic contexts. Applied, these findings may contribute to improve efforts made in the field of flood risk management, as well as restoration planning.

  17. 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

  18. 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.

  19. 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.

  20. Very large scale aerial (VLSA) imagery for assessing postfire bitterbrush recovery.

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Monitoring spotted knapweed with very-large-scale-aerial imagery in sagebrush-dominated rangelands.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spotted knapweed (Centaurea stoebe L.) invades and destroys productive rangelands. Monitoring weed infestations across extensive and remote landscapes can be difficult and costly. We evaluated the efficacy of very-large-scale-aerial (VLSA) imagery for detection and quantification of spotted knapwee...

  2. 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...

  3. 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

  4. 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

  5. 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%.

  6. 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.

  7. Using aerial video to train the supervised classification of Landsat TM imagery for coral reef habitats mapping.

    PubMed

    Bello-Pineda, J; Liceaga-Correa, M A; Hernández-Núñez, H; Ponce-Hernández, R

    2005-06-01

    Management of coral reef resources is a challenging task, in many cases, because of the scarcity or inexistence of accurate sources of information and maps. Remote sensing is a not intrusive, but powerful tool, which has been successfully used for the assessment and mapping of natural resources in coral reef areas. In this study we utilized GIS to combine Landsat TM imagery, aerial photography, aerial video and a digital bathymetric model, to assess and to map submerged habitats for Alacranes reef, Yucatán, México. Our main goal was testing the potential of aerial video as the source of data to produce training areas for the supervised classification of Landsat TM imagery. Submerged habitats were ecologically characterized by using a hierarchical classification of field data. Habitats were identified on an overlaid image, consisting of the three types of remote sensing products and the bathymetric model. Pixels representing those habitats were selected as training areas by using GIS tools. Training areas were used to classify the Landsat TM bands 1, 2 and 3 and the bathymetric model by using a maximum likelihood algorithm. The resulting thematic map was compared against field data classification to improve habitats definition. Contextual editing and reclassification were used to obtain the final thematic map with an overall accuracy of 77%. Analysis of aerial video by a specialist in coral reef ecology was found to be a suitable source of information to produce training areas for the supervised classification of Landsat TM imagery in coral reefs at a coarse scale. PMID:15952517

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Accuracy Comparison of Digital Surface Models Created by Unmanned Aerial Systems Imagery and Terrestrial Laser Scanner

    NASA Astrophysics Data System (ADS)

    Naumann, M.; Geist, M.; Bill, R.; Niemeyer, F.; Grenzdörffer, G.

    2013-08-01

    The main focus of the paper is a comparative study in which we have investigated, whether automatically generated digital surface models (DSM) obtained from unmanned aerial systems (UAS) imagery are comparable with DSM obtained from terrestrial laser scanning (TLS). The research is conducted at a pilot dike for coastal engineering. The effort and the achievable accuracy of both DSMs are compared. The error budgets of these two methods are investigated and the models obtained in each case compared against each other.

  14. 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.

  15. 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.

  16. 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...

  17. Automatic georeferencing of imagery from high-resolution, low-altitude, low-cost aerial platforms

    NASA Astrophysics Data System (ADS)

    Geniviva, Amanda; Faulring, Jason; Salvaggio, Carl

    2014-06-01

    Existing nadir-viewing aerial image databases such as that available on Google Earth contain data from a variety of sources at varying spatial resolutions. Low-cost, low-altitude, high-resolution aerial systems such as unmanned aerial vehicles and balloon- borne systems can provide ancillary data sets providing higher resolution, oblique­ looking data to enhance the data available to the user. This imagery is difficult to georeference due to the different projective geometry present in these data. Even if this data is accompanied by metadata from global positioning system (GPS) and inertial measurement unit (IMU) sensors, the accuracy obtained from low-cost versions of these sensors is limited. Combining automatic image registration techniques with the information provided by the IMU and onboard GPS, it is possible to improve the positioning accuracy of these oblique data sets on the ground plane using existing orthorectified imagery available from sources such as Google Earth. Using both the affine scale-invariant feature transform (ASIFT) and maximally stable extremal regions (MSER), feature detectors aid in automatically detecting correspondences between the obliquely collected images and the base map. These correspondences are used to georeference the high-resolution, oblique image data collected from these low-cost aerial platforms providing the user with an enhanced visualization experience.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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

  4. 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.

  5. L-shaped corner detector for rooftop extraction from satellite/aerial imagery

    NASA Astrophysics Data System (ADS)

    Tan, Hui Li; Fan, Jiayuan; Lu, Shijian

    2015-10-01

    Rooftop extraction from satellite/aerial imagery is an important geospatial problem with many practical applications. However, rooftop extraction remains a challenging problem due to the diverse characteristics and appearances of the buildings, as well as the quality of the satellite/aerial images. Many existing rooftop extraction methods use rooftop corners as a basic component. Nonetheless, existing rooftop corner detectors either suffer from high missed detection or introduce high false alarm. Based on the observation that rooftop corners are typically of L-shape, we propose an L-shaped corner detector for automatic rooftop extraction from high resolution satellite/aerial imagery. The proposed detector considers information in a spatial circle around each pixel to construct a feature map which captures the probability of L-shaped corner at every pixel. Our experimental results on a rooftop database of over 200 buildings demonstrate its effectiveness for detecting rooftop corners. Furthermore, our proposed detector is complementary to many existing rooftop extraction approaches which require reliable rooftop corners as their inputs. For instance, it can be used in the quadrilateral footprint extraction methods or in driving level-set-based segmentation techniques.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  15. 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

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. Mapping Broom Snakeweed Through Image Analysis of Color-infrared Photography and Digital Imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A study was conducted on a south Texas rangeland area to evaluate aerial color-infrared (CIR) photography and CIR digital imagery combined with unsupervised image analysis techniques to map broom snakeweed [Gutierrezia sarothrae (Pursh.) Britt. and Rusby]. Accuracy assessments performed on compute...

  3. 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.

  4. Technical development for automatic aerial triangulation of high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Xiong, Zhen

    Because they contain abundant spatial information, high resolution satellite images are widely used in a variety of applications. Aerial triangulation is one of the most important technologies to obtain accurate spatial information from those images. Thus aerial triangulation is always an important research topic in the photogrammetric community and automatic aerial triangulation is a common goal of such PhD research activities. To date, many techniques have been developed to improve the efficiency and accuracy of aerial triangulation. However, for processing high resolution satellite images, automatic aerial triangulation still faces many challenges, including tie point extraction and sensor model refinement. The main purpose of this research is to develop and test new tie point extraction, sensor model refinement and bundle block adjustment methods for improving the automation and accuracy of aerial triangulation. The accuracy of tie points directly determines the success of aerial triangulation. Generally both the corner point and the gravity center point of a rectangular or circular object can be used as tie points, but the resulting outcomes can vary greatly in aerial triangulation. However, this difference has not drawn much attention from researchers yet. Thus, most of the tie point extraction algorithms only extract various corners. In order to quantify the difference between corner and center tie points for image registration, this research analyzed the error introduced by using corner or center tie points in different cases. Through quantitative analysis and experiments, the author reached the conclusion that the 'center' points, when used as tie points, can improve the accuracy of image registration by at least 40 percent over that for the 'corner' points. Extracting a large number of tie points is the prerequisite of automatic aerial triangulation. Interest point matching can extract tie points automatically. To date numerous interest point matching

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. Observations of coastal systems using low-cost, high-resolution, balloon and kite-based aerial imagery

    NASA Astrophysics Data System (ADS)

    Griffith, A.; Young, R.

    2012-04-01

    Remote-sensed aerial imagery has been one of the primary methods for tracking shoreline change, but the low availability of high-quality data that is temporally relevant to the area of interest is often too expensive for small scale studies, if the data even exist. The Program for the Study of Developed Shorelines (PSDS) at Western Carolina University has been using balloon and kite mounted cameras for two years to make observations of highly dynamic, near shore systems in the southeastern United States. Through a partnership with GrassrootsMapping.org, our program was introduced to the system of aerial photography which collects images for under 200 USD at resolutions of 5-10 cm/pixel. The system is field transportable and can collect imagery on an as-needed basis, instead of scheduling aerial over flights or waiting for Google Earth imagery to be updated. Successful research trips to Beaufort County, South Carolina have identified buildings and infrastructure that are at risk of inundation from sea-level rise. The region experiences daily tidal fluctuations in excess of 2 m, allowing imagery to be captured at a variety of tidal cycles. The method has identified wetlands adjacent to developed areas lacking a buffer area allowing them to expand as sea levels rise. Due to the high resolution of the images, changes over shorter time intervals can be observed, such as the transition from high marsh to low marsh, as sea levels rise. After the 2010 Deepwater Horizon oil spill, PSDS staff mapped the oil spill on several trips to the Gulf of Mexico. Repeated visits to the same area have yielded a time series of images with greater frequency than more expensive methods. Finally, offshore sand movements at tidal inlets have been observed in detail on beaches in southern Georgia.

  14. 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

  15. 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

  16. GPR investigation of karst guided by comparison with outcrop and unmanned aerial vehicle imagery

    NASA Astrophysics Data System (ADS)

    Fernandes, Antonio L.; Medeiros, Walter E.; Bezerra, Francisco H. R.; Oliveira, Josibel G.; Cazarin, Caroline L.

    2015-01-01

    The increasing importance of carbonate rocks as aquifers, oil reservoirs, and for urban problems is demanding detailed characterization of karst systems, a demand that can be partially satisfied with GPR imaging. However, the goal of imaging and interpreting karstified carbonate rocks is notoriously difficult due to the complex nature of the geometry of the dissolution and the GPR intrinsic limitations. One way forward is the direct comparison of GPR images with similar outcropping rocks. A joint study involving a 200 MHz GPR survey, unmanned aerial vehicle imagery (UAV), and outcrop characterization is presented aiming to improve the interpretation of sedimentary structures, fractures and karst structures in GPR images. The study area is a 500 m wide and 1000 m long carbonate outcrop of the Jandaíra Formation in Potiguar basin, Brazil, where sedimentary, fracture, and karst features can be directly investigated in both vertical and horizontal plan views. The key elements to interpret GPR images of karstified carbonate rocks are: (1) primary sedimentary structures appear in radargrams as unaltered imaged strata but care must be taken to interpret complex primary sedimentary features, such as those associated with bioturbation; (2) subvertical fractures might appear as consistent discontinuities in the imaged strata, forming complex structures such as negative flowers along strike-slip faults; (3) dissolution may create voids along subhorizontal layers, which appear in radargrams as relatively long amplitude shadow zones; and (4) dissolution may also create voids along subvertical fractures, appearing in radargrams as amplitude shadow zones with relatively large vertical dimensions, which are bounded by fractures.

  17. 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.

  18. Using very-large-scale aerial imagery for rangeland monitoring and assessment: Some statistical considerations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The availability of very-high-resolution (VHR) imagery and techniques for processing those data into indicators of ecosystem function has opened the door for VHR imagery to be used in rangeland monitoring and assessment. However, VHR imagery can be expensive and, like any survey measurement, studies...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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%.

  4. 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.

  5. 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

  6. Agreement between measurements of shrub cover using ground-based methods and Very Large Scale Aerial (VLSA)imagery-measured shrub cover.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    New sampling methods are needed for measuring rangeland cover that are more efficient than conventional methods. Very large scale aerial (VLSA) imagery has been suggested as a tool for improving cover sampling efficiency. Because of aircraft pitch and roll, camera misalignment, and errors in the n...

  7. Remote sensing based detection of forested wetlands: An evaluation of LiDAR, aerial imagery, and their data fusion

    NASA Astrophysics Data System (ADS)

    Suiter, Ashley Elizabeth

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

  8. Automatic geolocation of targets tracked by aerial imaging platforms using satellite imagery

    NASA Astrophysics Data System (ADS)

    Shukla, P. K.; Goel, S.; Singh, P.; Lohani, B.

    2014-11-01

    Tracking of targets from aerial platforms is an important activity in several applications, especially surveillance. Knowled ge of geolocation of these targets adds additional significant and useful information to the application. This paper determines the geolocation of a target being tracked from an aerial platform using the technique of image registration. Current approaches utilize a POS to determine the location of the aerial platform and then use the same for geolocation of the targets using the principle of photogrammetry. The constraints of cost and low-payload restrict the applicability of this approach using UAV platforms. This paper proposes a methodology for determining the geolocation of a target tracked from an aerial platform in a partially GPS devoid environment. The method utilises automatic feature based registration technique of a georeferenced satellite image with an ae rial image which is already stored in UAV's database to retrieve the geolocation of the target. Since it is easier to register subsequent aerial images due to similar viewing parameters, the subsequent overlapping images are registered together sequentially thus resulting in the registration of each of the images with georeferenced satellite image thus leading to geolocation of the target under interest. Using the proposed approach, the target can be tracked in all the frames in which it is visible. The proposed concept is verified experimentally and the results are found satisfactory. Using the proposed method, a user can obtain location of target of interest as well features on ground without requiring any POS on-board the aerial platform. The proposed approach has applications in surveillance for target tracking, target geolocation as well as in disaster management projects like search and rescue operations.

  9. [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

  10. 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.

  11. 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

  12. Multispectral Analysis of NMR Imagery

    NASA Technical Reports Server (NTRS)

    Butterfield, R. L.; Vannier, M. W. And Associates; Jordan, D.

    1985-01-01

    Conference paper discusses initial efforts to adapt multispectral satellite-image analysis to nuclear magnetic resonance (NMR) scans of human body. Flexibility of these techniques makes it possible to present NMR data in variety of formats, including pseudocolor composite images of pathological internal features. Techniques do not have to be greatly modified from form in which used to produce satellite maps of such Earth features as water, rock, or foliage.

  13. 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.

  14. 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....

  15. 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.

  16. Semi-automated analysis of high-resolution aerial images to quantify docks in glacial lakes

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

    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 K^) 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. Analysis of Operation PLUMBBOB nuclear test smoky aerial radiological data

    SciTech Connect

    Steadman, C.R. Jr.; Kennedy, N.C.; Quinn, V.E.

    1984-03-01

    This report describes the Weather Service Nuclear Support Office (WSNSO) analysis of the aerial radiological data collected following the SMOKY nuclear test of Operation PLUMBBOB. The methods of converting these aerial data to exposure rates compatible with those measured by ground-level monitors are discussed. A fallout pattern, based upon the resulting aerial exposure-rate values, is presented for the downwind area where no ground-level exposure-rate measurements were made. This WSNSO extended fallout pattern is compared with a similar analysis prepared in the late 1950s. An evaluation of the enhanced fallout areas shown in the extended pattern is made. The appendices contain discussions of the aerial data collection and analysis procedures, and contain tabulated radiological data used in the extended fallout pattern analysis. 7 references, 6 figures, 3 tables.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. Motion Component Supported Boosted Classifier for CAR Detection in Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Tuermer, S.; Leitloff, J.; Reinartz, P.; Stilla, U.

    2011-04-01

    Research of automatic vehicle detection in aerial images has been done with a lot of innovation and constantly rising success for years. However information was mostly taken from a single image only. Our aim is using the additional information which is offered by the temporal component, precisely the difference of the previous and the consecutive image. On closer viewing the moving objects are mainly vehicles and therefore we provide a method which is able to limit the search space of the detector to changed areas. The actual detector is generated of HoG features which are composed and linearly weighted by AdaBoost. Finally the method is tested on a motorway section including an exit and congested traffic near Munich, Germany.

  4. 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.

  5. The influence of the in situ camera calibration for direct georeferencing of aerial imagery

    NASA Astrophysics Data System (ADS)

    Mitishita, E.; Barrios, R.; Centeno, J.

    2014-11-01

    The direct determination of exterior orientation parameters (EOPs) of aerial images via GNSS/INS technologies is an essential prerequisite in photogrammetric mapping nowadays. Although direct sensor orientation technologies provide a high degree of automation in the process due to the GNSS/INS technologies, the accuracies of the obtained results depend on the quality of a group of parameters that models accurately the conditions of the system at the moment the job is performed. One sub-group of parameters (lever arm offsets and boresight misalignments) models the position and orientation of the sensors with respect to the IMU body frame due to the impossibility of having all sensors on the same position and orientation in the airborne platform. Another sub-group of parameters models the internal characteristics of the sensor (IOP). A system calibration procedure has been recommended by worldwide studies to obtain accurate parameters (mounting and sensor characteristics) for applications of the direct sensor orientation. Commonly, mounting and sensor characteristics are not stable; they can vary in different flight conditions. The system calibration requires a geometric arrangement of the flight and/or control points to decouple correlated parameters, which are not available in the conventional photogrammetric flight. Considering this difficulty, this study investigates the feasibility of the in situ camera calibration to improve the accuracy of the direct georeferencing of aerial images. The camera calibration uses a minimum image block, extracted from the conventional photogrammetric flight, and control point arrangement. A digital Vexcel UltraCam XP camera connected to POS AV TM system was used to get two photogrammetric image blocks. The blocks have different flight directions and opposite flight line. In situ calibration procedures to compute different sets of IOPs are performed and their results are analyzed and used in photogrammetric experiments. The IOPs

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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...

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Detection of Single Standing Dead Trees from Aerial Color Infrared Imagery by Segmentation with Shape and Intensity Priors

    NASA Astrophysics Data System (ADS)

    Polewski, P.; Yao, W.; Heurich, M.; Krzystek, P.; Stilla, U.

    2015-03-01

    Standing dead trees, known as snags, are an essential factor in maintaining biodiversity in forest ecosystems. Combined with their role as carbon sinks, this makes for a compelling reason to study their spatial distribution. This paper presents an integrated method to detect and delineate individual dead tree crowns from color infrared aerial imagery. Our approach consists of two steps which incorporate statistical information about prior distributions of both the image intensities and the shapes of the target objects. In the first step, we perform a Gaussian Mixture Model clustering in the pixel color space with priors on the cluster means, obtaining up to 3 components corresponding to dead trees, living trees, and shadows. We then refine the dead tree regions using a level set segmentation method enriched with a generative model of the dead trees' shape distribution as well as a discriminative model of their pixel intensity distribution. The iterative application of the statistical shape template yields the set of delineated dead crowns. The prior information enforces the consistency of the template's shape variation with the shape manifold defined by manually labeled training examples, which makes it possible to separate crowns located in close proximity and prevents the formation of large crown clusters. Also, the statistical information built into the segmentation gives rise to an implicit detection scheme, because the shape template evolves towards an empty contour if not enough evidence for the object is present in the image. We test our method on 3 sample plots from the Bavarian Forest National Park with reference data obtained by manually marking individual dead tree polygons in the images. Our results are scenario-dependent and range from a correctness/completeness of 0.71/0.81 up to 0.77/1, with an average center-of-gravity displacement of 3-5 pixels between the detected and reference polygons.

  18. 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.

  19. 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.

  20. 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.

  1. Assessing the relationship between urban parameters and the LST derived by satellite and aerial imageries in a GIS environment: the case of Bari (Italy).

    NASA Astrophysics Data System (ADS)

    Caprioli, Mauro; Ceppi, Claudia; Falchi, Ugo; Mancini, Francesco; Scarano, Mario

    2014-05-01

    The use of thermal remote sensing to estimate the phenomenon of urban heat islands (UHI) and development of climate anomalies in urban context represents a consolidated approach. In the current scientific literature a widespread case studies were focused on the estimation of the relationship between features related to the urban environment and the Land Surface Temperatures (LST). The latter is a basic starting observation in the investigation on the UHI phenomenon . However, the evaluation of these relationships is rather difficult. This is due to deficiencies in the detailed knowledge of parameters able to describe geometric and qualitative properties of land covers. These properties are very often not repeatable and not easily transferable in other contexts. In addition, many of the relevant parameters are difficult to be determined at the required spatial resolution and analyses are affected by a lack in the amount of quantitative parameters used. In addition to the LST, several useful indicators are introduced by the literature in the investigation of such phenomena. The objective of this work is to study the relationship between the LST and a set of variables that characterize the anthropic and natural domains of the urban areas, such as urban morphology, the Normalized Differenced Vegetation Index (NDVI), the Sky View Factor (SVF) and other morphometric parameters implemented within a GIS environment. The study case is the city of Bari (Southern Italy) where several recognizable morphologies exhibit a different thermal behavior. The LST parameter was derived from a collection of satellite ASTER images collected within a period spanning from July 2001 and July 2006, whereas aerial thermal imageries were acquired on September 2013. The basic data used for the determination of the descriptive parameters of the urban environmental are derived from digital maps(Geographic Information System of the Apulia Region), Digital Elevation Model and Land Use. The analysis

  2. 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

  3. Analysis of cyberattacks on unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Shull, Andrew M.

    With the increasing power and convenience offered by the use of embedded systems in control applications, such systems will undoubtedly continue to be developed and deployed. Recently, however, a focus on data-centric systems and developing network-enabled control systems has emerged, allowing for greater performance, safety, and resource allocation in systems such as smart power grids and unmanned military aircraft. However, this increase in connectivity also introduces vulnerabilities into these systems, potentially providing access to malicious parties seeking to disrupt the operation of those systems or to cause damage. Given the high potential cost of a failure in these systems in terms of property, sensitive information, and human safety, steps need to be taken to secure these systems. In order to analyze the vulnerabilities of unmanned aerial systems (UASs) specifically, a simulation testbed is developed to perform high-fidelity simulations of UAS operations using both software models and the actual vehicle hardware. Then, potential attacks against the control system and their corresponding intents are identified and introduced into these simulations. Failure conditions are defined, and extensive simulation of attacks in different combinations and magnitudes are performed in both software and hardware in order to identify particularly successful attacks, including attacks that are difficult to detect. From these results, vulnerabilities of the system can be determined so that appropriate remedies can be designed. Additionally, stealthy false data injection attacks against linear feedback systems are considered. The identification of these attacks is formed as an optimization problem constrained by the ability of monitoring systems to detect the attack. The optimal attack input is then determined for an example application so that the worst case system performance can be identified and, if needed, improved.

  4. 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.

  5. Feature selection methods for object-based classification of sub-decimeter resolution digital aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Due to the availability of numerous spectral, spatial, and contextual features, the determination of optimal features and class separabilities can be a time consuming process in object-based image analysis (OBIA). While several feature selection methods have been developed to assist OBIA, a robust c...

  6. Data fusion of extremely high resolution aerial imagery and LiDAR data for automated railroad centre line reconstruction

    NASA Astrophysics Data System (ADS)

    Beger, Reinhard; Gedrange, Claudia; Hecht, Robert; Neubert, Marco

    2011-12-01

    The quality of remotely sensed data in regards of accuracy and resolution has considerably improved in recent years. Very small objects are detectable by means of imaging and laser scanning, yet there are only few studies to use such data for large scale mapping of railroad infrastructure.In this paper, an approach is presented that integrates extremely high resolution ortho-imagery and dense airborne laser scanning point clouds. These data sets are used to reconstruct railroad track centre lines. A feature level data fusion is carried out in order to combine the advantages of both data sets and to achieve a maximum of accuracy and completeness.The workflow consists of three successive processing steps. First, object-based image analysis is used to derive a railroad track mask from ortho-imagery. This spatial location information is then combined with the height information to classify the laser points. Lastly, the location of railroad track centre lines from these classified points were approximated using a feature extraction method based on an adapted random sample consensus algorithm. This workflow is tested on two railroad sections and was found to deliver very accurate results in a quickly and highly automated manner.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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. PMID:24234223

  13. 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.

  14. Interactive analysis of thermal imagery. [computer graphics terminal for photointerpretation

    NASA Technical Reports Server (NTRS)

    Madding, R. P.; Fisher, L. T.

    1976-01-01

    Necessary knowledge is presented on data acquisition and preparation for analysis of thermal imagery of power plant heated discharges remotely sensed from an aircraft, with special emphasis on analog to digital conversion of analog tapes acquired during scanning and to geometrical scaling. The central element in the interactive analysis of thermal imagery is an interactive graphics computer terminal which allows an interpreter to effectively interact with a large-scale computer, providing decisions or data as computations are carried out. A temperature calibration is performed, which the interpreter may test anywhere on the image. When satisfied that calibration is correct, the portion of the image to be analyzed is outlined. Printed and microfiche analyses of the plume are produced. The flow chart of programs for analysis of thermal imagery is presented and discussed in some detail.

  15. 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.

  16. 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.

  17. Towards the objective analysis of clouds from satellite imagery data

    NASA Technical Reports Server (NTRS)

    Coakley, J. A., Jr.; Baldwin, D. G.

    1984-01-01

    It is suspected that clouds play a major role in climate dynamics. However, conclusive studies regarding the effects related to the cloud cover appear difficult because there is a lack of objective data. The present investigation is concerned with an objective scheme for deriving clouds and their properties from satellite imagery data for the oceans. The objective analysis makes use of the spatial coherence method for retrieving cloud cover from satellite imagery data. This method has advantages over other techniques often applied to imagery data. It is not necessary that clouds fill completely the observing instrument's field-of-view, and a priori or satellite derived knowledge of the cloud radiative properties is not needed.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. Forest Inventory Attribute Estimation Using Airborne Laser Scanning, Aerial Stereo Imagery, Radargrammetry and Interferometry-Finnish Experiences of the 3d Techniques

    NASA Astrophysics Data System (ADS)

    Holopainen, M.; Vastaranta, M.; Karjalainen, M.; Karila, K.; Kaasalainen, S.; Honkavaara, E.; Hyyppä, J.

    2015-03-01

    Three-dimensional (3D) remote sensing has enabled detailed mapping of terrain and vegetation heights. Consequently, forest inventory attributes are estimated more and more using point clouds and normalized surface models. In practical applications, mainly airborne laser scanning (ALS) has been used in forest resource mapping. The current status is that ALS-based forest inventories are widespread, and the popularity of ALS has also raised interest toward alternative 3D techniques, including airborne and spaceborne techniques. Point clouds can be generated using photogrammetry, radargrammetry and interferometry. Airborne stereo imagery can be used in deriving photogrammetric point clouds, as very-high-resolution synthetic aperture radar (SAR) data are used in radargrammetry and interferometry. ALS is capable of mapping both the terrain and tree heights in mixed forest conditions, which is an advantage over aerial images or SAR data. However, in many jurisdictions, a detailed ALS-based digital terrain model is already available, and that enables linking photogrammetric or SAR-derived heights to heights above the ground. In other words, in forest conditions, the height of single trees, height of the canopy and/or density of the canopy can be measured and used in estimation of forest inventory attributes. In this paper, first we review experiences of the use of digital stereo imagery and spaceborne SAR in estimation of forest inventory attributes in Finland, and we compare techniques to ALS. In addition, we aim to present new implications based on our experiences.

  3. Aerial Photogrammetric Analysis of a Scree Slope and Cliff

    NASA Astrophysics Data System (ADS)

    Saunders, Greg; Galland, Olivier; Mair, Karen

    2014-05-01

    Mapping the physical features of landslide tracks provides information about factors controlling landslide movement. The increasing availability of unmanned aerial vehicles (UAV) provides the opportunity to efficiently and cost effectively map terrain. The main goal of this field study is to create a streamlined work-flow from acquisition to interpretation for the photogrammetric analysis of landslide tracks. Here an open source software package MicMac is used for ortho-image and point-cloud creation. A series of two flights were conducted over a scree (rockfall) slope in Kolsas, Norway. The slope runs roughly 500 m north-south with a maximum width of 60 m. A cliff to the west is the source area for the scree. The cliff consists of conglomerate, basalt, and porphyry from bottom to top respectively. The grain size of boulders in the scree slope apparently varies due to lateral differences in the cliff composition. The flights were completed under cloud cover and consisted of multiple lengthwise passes over the scree field. There was a minimum of 75% overlap between images. During the first flight the altitude was roughly 100 m, the camera was positioned normal to the scree (60 degrees from horizontal), and the resolution was 2.7 cm per pixel. The second flight had an altitude of 200 m, the camera orientation was 30 degrees from horizontal, and the resolution was 4.0 cm per pixel. Using the Micmac engine, Ortho-photos and Digital Elevation Models (DEM) were created for both the scree and the cliff. This data will allow for analysis of grain-size, surface roughness, grain-shape, fracture plane orientation, as well as geological mapping. Further work will focus the quantitative assessment of the significance different camera altitudes and angles have on the results. The work-flow used in this study provides a repeatable method for aerial photogrammetric surveys of scree slopes.

  4. 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.

  5. 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.

  6. Using aerial photography and image analysis to measure changes in giant reed populations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A study was conducted along the Rio Grande in southwest Texas to evaluate color-infrared aerial photography combined with supervised image analysis to quantify changes in giant reed (Arundo donax L.) populations over a 6-year period. Aerial photographs from 2002 and 2008 of the same seven study site...

  7. 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.

  8. Analysis Of Multispectral Imagery And Modeling Contaminant Transport

    NASA Astrophysics Data System (ADS)

    Irvine, J. M.; Becker, N. M.; Brumby, S.; David, N. A.

    2003-12-01

    A significant concern in the monitoring of hazardous waste is the potential for contaminants to migrate into locations where their presence poses greater environmental risks. The transport modeling performed in this study demonstrates the joint use of remotely sensed multispectral imagery and mathematical modeling to assess the surface migration of contaminants. KINEROS, an event-driven model of surface runoff and sediment transport, was used to assess uranium transport for various rain events. While our specific application was uranium transport, the methods apply to surface transport of any substance of concern. The model inputs include parameters related to the size and slope of watershed components, vegetation, and soil conditions. One distinct set of model inputs was derived from remotely sensed imagery data and another from site-specific knowledge. To derive the parameters of the KINEROS model from remotely sensed data, classification analysis was performed on IKONOS four-band multispectral imagery of the watershed. A system known as GENIE, developed by Los Alamos National Laboratory, employs genetics algorithms to evolve classifiers based on small, user-selected training samples. The classification analysis derived by employing GENIE provided insight into the correct KINEROS parameters for various sub-elements of the watershed. The model results offer valuable information about portions of the watershed that contributed the most to contaminant transport. These methods are applicable to numerous sites where possible transport of waste materials or other hazardous substances poses an environmental risk. Consequently, the approach presented here is relevant to homeland security and emergency response scenarios, as well as long-term environmental monitoring applications. Because the approach rests on the analysis of remote sensing data, the techniques can be used to monitor a range of sites and can reduce costs of data collection for model calibration.

  9. Motion/imagery secure cloud enterprise architecture analysis

    NASA Astrophysics Data System (ADS)

    DeLay, John L.

    2012-06-01

    Cloud computing with storage virtualization and new service-oriented architectures brings a new perspective to the aspect of a distributed motion imagery and persistent surveillance enterprise. Our existing research is focused mainly on content management, distributed analytics, WAN distributed cloud networking performance issues of cloud based technologies. The potential of leveraging cloud based technologies for hosting motion imagery, imagery and analytics workflows for DOD and security applications is relatively unexplored. This paper will examine technologies for managing, storing, processing and disseminating motion imagery and imagery within a distributed network environment. Finally, we propose areas for future research in the area of distributed cloud content management enterprises.

  10. 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.

  11. 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.

  12. 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

  13. Mapping Giant Salvinia with Satellite Imagery and Image Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    QuickBird multispectral satellite imagery was evaluated for distinguishing giant salvinia (Salvinia molesta Mitchell) in a large reservoir in east Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Color-infrared (green, red, and near-infrared bands)...

  14. 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.

  15. Trends in quantitative aerial thermography

    SciTech Connect

    Schott, J.R.; Wilkinson, E.P.

    1983-06-01

    Recent improvements in aerial thermographic techniques, particularly in achievable spatial resolution and noise equivalent temperature variation, have enabled the use of thermography in a more objective fashion. Interpretation of the information contained in thermograms has also been improved through the use of certain techniques accounting for roof material type (emissivity), background effects, and atmospheric variables. With current methods, roof surface temperature from aerial imagery can be measured to within 1.8/sup 0/F (1.0/sup 0/C) of the actual temperature. These advances in thermogram analysis have opened the door for potential direct measurement of rooftop heat-loss levels from thermogram data. Ultimately, it is felt that this type of information would make it feasible to direct intensive energy-conservation efforts toward a smaller population, where the need and cost benefits will be the greatest.

  16. 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

  17. 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

  18. Utility of a scanning densitometer in analyzing remotely sensed imagery

    NASA Technical Reports Server (NTRS)

    Dooley, J. T.

    1976-01-01

    The utility of a scanning densitometer for analyzing imagery in the NASA Lewis Research Center's regional remote sensing program was evaluated. Uses studied include: (1) quick-look screening of imagery by means of density slicing, magnification, color coding, and edge enhancement; (2) preliminary category classification of both low- and high-resolution data bases; and (3) quantitative measurement of the extent of features within selected areas. The densitometer was capable of providing fast, convenient, and relatively inexpensive preliminary analysis of aerial and satellite photography and scanner imagery involving land cover, water quality, strip mining, and energy conservation.

  19. 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)

  20. 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

  1. 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. PMID:16435690

  2. Improved iterative error analysis for endmember extraction from hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Sun, Lixin; Zhang, Ying; Guindon, Bert

    2008-08-01

    Automated image endmember extraction from hyperspectral imagery is a challenge and a critical step in spectral mixture analysis (SMA). Over the past years, great efforts were made and a large number of algorithms have been proposed to address this issue. Iterative error analysis (IEA) is one of the well-known existing endmember extraction methods. IEA identifies pixel spectra as a number of image endmembers by an iterative process. In each of the iterations, a fully constrained (abundance nonnegativity and abundance sum-to-one constraints) spectral unmixing based on previously identified endmembers is performed to model all image pixels. The pixel spectrum with the largest residual error is then selected as a new image endmember. This paper proposes an updated version of IEA by making improvements on three aspects of the method. First, fully constrained spectral unmixing is replaced by a weakly constrained (abundance nonnegativity and abundance sum-less-or-equal-to-one constraints) alternative. This is necessary due to the fact that only a subset of endmembers exhibit in a hyperspectral image have been extracted up to an intermediate iteration and the abundance sum-to-one constraint is invalid at the moment. Second, the search strategy for achieving an optimal set of image endmembers is changed from sequential forward selection (SFS) to sequential forward floating selection (SFFS) to reduce the so-called "nesting effect" in resultant set of endmembers. Third, a pixel spectrum is identified as a new image endmember depending on both its spectral extremity in the feature hyperspace of a dataset and its capacity to characterize other mixed pixels. This is achieved by evaluating a set of extracted endmembers using a criterion function, which is consisted of the mean and standard deviation of residual error image. Preliminary comparison between the image endmembers extracted using improved and original IEA are conducted based on an airborne visible infrared imaging

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Image analysis techniques with special reference to analysis and interpretation of geological features from LANDSAT imagery. [India

    NASA Technical Reports Server (NTRS)

    Kamat, D. S.; Majumder, K. L.; Naik, S. D.; Swaminathan, V. L.

    1977-01-01

    The principal component analysis enhances the contrast existing between the different cover types present in an imagery. A procedure is presented with regards to the determination of the principal components. The method is tested for a portion of the LANDSAT imagery pertaining to Anantapur region. Another technique, using the concept of non-linear contrast stretching is defined and developed and carried out on the same imagery. The results are presented as photographs. An interpretation of the geology of the region is derived from these photographs.

  14. Better sensors = better imagery = better outputs

    NASA Astrophysics Data System (ADS)

    Smith, Michael

    2014-05-01

    The photogrammetric workflow has traditionally relied upon the use of high quality metric cameras that enable the acquisition of good quality imagery, from which outputs with a well constrained geometry can be obtained. However with the proliferation of low altitude aerial photography from a range of platforms, the quality of sensor itself has largely become of secondary importance in order to reduce weight and minimise cost. These instruments are often "off-the-shelf" consumer digital cameras, not designed for either aerial photography or photogrammetry. This imposes limitations upon the quality of imagery that can be collected and outputs subsequently produced. Photogrammetric techniques such as a self-calibrating bundle adjustment or Structure from Motion allow the use of "less stable" imagery. Yet at the simplest level, the better the sensor, the better the imagery, the better the output. Where analysis and the validity of scientific conclusions are dependent upon the quality of outputs it is critical that consideration is given to the choice of sensor - the wide availability and application of UAVs across disciplines means that users may not be aware of such choices and their implications. This presentation is designed to stimulate discussion around the use of consumer cameras with a focus upon the exposure triangle of ISO-aperture-shutter speed and how this is related to dynamic range and the signal-to-noise ratio. A further important factor is understanding the ground resolution element in terms of resolution, focal length, sensor size (crop factor) and height.

  15. 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

  16. 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

  17. 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.

  18. Estimating seasonal changes of land cover, surface wetness and latent heat flux of wet polygonal tundra (Samoylov Island, Lena-Delta, Siberia) with high-resolution aerial and hyperspectral CHRIS Proba satellite imagery

    NASA Astrophysics Data System (ADS)

    Muster, S.; Langer, M.; Boike, J.

    2009-12-01

    Vegetation cover, land cover and surface wetness are few of the many factors exerting control on the partitioning of energy to latent, sensible and ground heat flux. Spatial estimates of these factors can be inferred from remote sensing data. The fractionated polygonal tundra landscape of Samoylov Island of wet and dry surfaces induces strong spatial variations of resistance to evapotranspiration. The development of low-centered ice-wedge polygons results in a prominent microrelief that is the most important factor for small-scale differences in vegetation type and near surface soil moisture. Depressed polygon centers alternate with elevated polygon rims with elevation differences of up to 0.5 m over a few meters distance. In the depressed polygon centers, drainage is strongly impeded due to the underlying permafrost resulting in water-saturated soils or small ponds. A process-based understanding of the surface energy balance, however, needs to consider both the temporal and the spatial variations of the surface. In the course of the summer season, the surface wetness changes significantly since the water table falls about 5 cm below the surface. This change in surface wetness is likely to be associated with changing evapotranspiration rates. We consider the effect of seasonal changes in land cover, vegetation cover and surface wetness on latent heat flux by investigating a time-series of high-resolution aerial and hyperspectral satellite imagery and comparing them to ground-based measurements of near-surface soil moisture and latent heat flux. Two sets of aerial images from August 15 and September 11, 2008 in the VNIR provide detailed information of the polygonal landscape with a resolution of 0.3m. CHRIS Proba imagery provides hyperspectral data with 18 spectral bands in the VNIR range (400 - 1050 nm) and a resolution of 17 m. Acquisition dates are June 21, July 23 and September 10, 2008. Daily point-based measurements of near-surface soil moisture and latent

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Object-Based Analysis of Aerial Photogrammetric Point Cloud and Spectral Data for Land Cover Mapping

    NASA Astrophysics Data System (ADS)

    Debella-Gilo, M.; Bjørkelo, K.; Breidenbach, J.; Rahlf, J.

    2013-04-01

    The acquisition of 3D point data with the use of both aerial laser scanning (ALS) and matching of aerial stereo images coupled with advances in image processing algorithms in the past years provide opportunities to map land cover types with better precision than before. The present study applies Object-Based Image Analysis (OBIA) to 3D point cloud data obtained from matching of stereo aerial images together with spectral data to map land cover types of the Nord-Trøndelag county of Norway. The multi-resolution segmentation algorithm of the Definiens eCognition™ software is used to segment the scenes into homogenous objects. The objects are then classified into different land cover types using rules created based on the definitions given for each land cover type by the Norwegian Forest and Landscape Institute. The quality of the land cover map was evaluated using data collected in the field as part of the Norwegian National Forest Inventory. The results show that the classification has an overall accuracy of about 80% and a kappa index of about 0.65. OBIA is found to be a suitable method for utilizing 3D remote sensing data for land cover mapping in an effort to replace manual delineation methods.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Spectral analysis algorithm for material detection from multispectral imagery

    NASA Astrophysics Data System (ADS)

    Racine, Joseph K.

    2011-06-01

    Material detection from multi-spectral imagery is critical to numerous geospatial applications. However, given the limited number of channels from various air and space-borne imaging sensors, coupled with varying illumination conditions, material-specific detection rules tend to generate large numbers of false positives. This paper will describe a novel approach that uses various band ratios (for example, [Blue + Green]/Red) to identify targets-of-interest, regardless of the illumination conditions and position of the sensor relative to the target. The approach uses a physics-based spectral model to estimate the observed channel-weighted radiance based on solar irradiance, atmospheric transmission, reflectivity of the target-of-interest and the spectral weighting functions of the sensor's channels. The observed channelweighted radiance is then converted to the expected channel pixel value by the channel-specific conversion factor. With each channel's pixel values estimated, the algorithm goes through a process to find which band ratio values show the least amount of variance, despite varying irradiance spectra and atmospheric absorption. The band ratios with the least amount of variance are then used to identify the target-of-interest in an image file. To determine the expected false alarm rate, the same band ratios are evaluated against a library of background materials using the same calculation method for determining the target-of-interest's channel pixel values. Testing of this approach against ground-truth imagery, with as few as four channels, has shown a high rate of success in identifying targets-of-interest, while maintaining low false alarm rates.

  9. 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.

  10. NON-RIGID REGISTRATION OF HYPERSPECTRAL IMAGERY FOR ANALYSIS OF AGRONOMIC SCENES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Analysis of remote sensing imagery usually entails the registration of images from different multiple wavelengths. Even though a staring instrument has the advantage of readily producing coherent spectral images, often these images still need some form of band-to-band registration to correct for in...

  11. 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.

  12. 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.

  13. 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.

  14. Analysis of initial drainage network evolution from aerial photography and a DEM time series

    NASA Astrophysics Data System (ADS)

    Schneider, Anna; Gerke, Horst H.; Maurer, Thomas; Nenov, Rossen; Raab, Thomas

    2013-04-01

    The evolution of erosion rill or gully networks is a formative process in initial landscape development. Digital representations of drainage networks are often derived from Digital Elevation Models (DEMs) based on morphometric parameters, or mapped in field surveys or from aerial photographs. This study attempted to reconstruct and analyze the first five years of erosion rill network evolution in the 6 ha artificial catchment 'Hühnerwasser', which serves as a real world-laboratory to study patterns and processes of initial ecosystem development. The drainage network was characterized in a twofold approach, based on the analysis of remotely-sensed data. We used high-resolution drone-based aerial photographs to map the actively eroding rill network for four states of development, and a time series of ten Digital Elevation Models to characterize the morphology of the surface. Rill network maps and morphometric parameters were combined to allow for region-specific analyses of morphometry for different parts of the rill network. After a rapid growth of the erosion rill network during the first two years of development, a reduction of the area of actively eroding rills was observed. Region-specific analysis of morphometry indicates an increase in flow accumulation in the central parts of the rill network, which suggests that locally evolving feedback cycles between flow accumulation and erosion affected rill network development, in addition to the effects of precipitation characteristics and the growth of vegetation cover. The combination of drainage network characterization from aerial photography and DEMs could improve analyses of initial drainage network development in experimental studies, as it allows for critical comparisons of flow accumulation patterns and the actual patterns of erosion rills or gullies.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. Analysis and simulation of the infrared characteristics of the aerial target

    NASA Astrophysics Data System (ADS)

    Ma, Sen; Li, Xiao-xia; Zhao, Nan

    2011-08-01

    This paper consults and improves the on hand computational methods and circuits, which comprehensively utilizes the knowledge of the Aerodynamics, the heat transfer theory, the radio optics, ANSYS and so on. In the analysis of the IR characteristics of aerial targets, taking it into account that most of the computing methods on hand are empirical or semi-empirical, which are more simple, but more limited, less sufficient and scientific and have more human factors, so we begin with the determination of the thermal field, adopt the numerical method to realize the calculation and modeling of the IR radiation with ANSYS, analysis how the spectral coverage and the observed bearing affect the IR radiation, and then get the credible and all-side numerical calculation results. Then, this paper introduces a method utilizing 3DS MAX and OpenGL to generate the IR picture of the target, which divides the grey level of the IR radiation reasonably according to the final numeric calculating results and the principle of the grey level division, and then we generate the IR pictures of the aerial targets.

  20. 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.

  1. 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.

  2. Cloning and analysis of a gene cluster from Streptomyces coelicolor that causes accelerated aerial mycelium formation in Streptomyces lividans.

    PubMed Central

    Ma, H; Kendall, K

    1994-01-01

    We describe the cloning and analysis of two overlapping DNA fragments from Streptomyces coelicolor that cause aerial mycelium to appear more rapidly than usual when introduced into Streptomyces lividans on a low-copy-number plasmid vector. Colonies of S. lividans TK64 harboring either clone produce visible aerial mycelia after only 48 h of growth, rather than the usual 72 to 96 h. From deletion and sequence analysis, this rapid aerial mycelium (Ram) phenotype appears to be due to a cluster of three genes that we have designated ramA, ramB, and ramR. Both ramA and ramB potentially encode 65-kDa proteins with homology to ATP-dependent membrane-translocating proteins. A chromosomal ramB disruption mutant of S. lividans was found to be severely defective in aerial mycelium formation. ramR could encode a 21-kDa protein with significant homology to the UhpA subset of bacterial two-component response regulator proteins. The overall organization and potential proteins encoded by the cloned DNA suggest that this is the S. coelicolor homolog of the amf gene cluster that has been shown to be important for aerial mycelium formation in Streptomyces griseus. However, despite the fact that the two regions probably have identical functions, there is relatively poor homology between the two gene clusters at the DNA sequence level. Images PMID:8206859

  3. 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

  4. 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.

  5. 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.

  6. 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

  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.

    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

  8. 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

  9. Regional analysis of tertiary volcanic Calderas (western U.S.) using Landsat Thematic Mapper imagery

    NASA Technical Reports Server (NTRS)

    Spatz, David M.; Taranik, James V.

    1989-01-01

    The Landsat Thematic Mapper (TM) imagery of the Basin and Range province of southern Nevada was analyzed to identify and map volcanic rock assemblages at three Tertiary calderas. It was found that the longer-wavelength visible and the NIR TM Bands 3, 5, and 7 provide more effective lithologic discrimination than the shorter-wavelength bands, due partly to deeper penetration of the longer-wavelength bands, resulting in more lithologically driven radiances. Shorter-wavelength TM Bands 1 and 2 are affected more by surficial weathering products including desert varnish which may or may not provide an indirect link to lithologic identity. Guidelines for lithologic analysis of volcanic terrains using Landsat TM imagery are outlined.

  10. An automated analysis of wide area motion imagery for moving subject detection

    NASA Astrophysics Data System (ADS)

    Tahmoush, Dave

    2015-05-01

    Automated analysis of wide area motion imagery (WAMI) can significantly reduce the effort required for converting data into reliable decisions. We register consecutive WAMI frames and use false-color frame comparisons to enhance the visual detection of possible subjects in the imagery. The large number of WAMI detections produces the need for a prioritization of detections for further inspection. We create a priority queue of detections for automated revisit with smaller field-ofview assets based on the locations of the movers as well as the probability of the detection. This automated queue works within an operator's preset prioritizations but also allows the flexibility to dynamically respond to new events as well as incorporating additional information into the surveillance tasking.

  11. 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.

  12. 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.

  13. 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.

  14. Analysis of GOES imagery and digitized data for the SEV-UPS period, August 1979

    NASA Technical Reports Server (NTRS)

    Bowley, C. J.; Burke, H. H. K.; Barnes, J. C.

    1981-01-01

    In support of the Southeastern Virginia Urban Plume Study (SEV-UPS), GOES satellite imagery was analyzed for the month of August 1979. The analyzed GOES images provide an additional source of meteorological input useful in the evaluation of air quality data collected during the month long period of the SEV-UPS experiment. In addition to the imagery analysis, GOES digitized data were analyzed for the period of August 6 to 11, during which a regional haze pattern was detectable in the imagery. The results of the study indicate that the observed haze patterns correspond closely with areas shown in surface based measurements to have reduced visibilities and elevated pollution levels. Moreover, the results of the analysis of digitized data indicate that digital reflectance counts can be directly related to haze intensity both over land and ocean. The model results agree closely with the observed GOES digital reflectance counts, providing further indication that satellite remote sensing can be a useful tool for monitoring regional elevated pollution episodes.

  15. 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

  16. 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.

  17. 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

  18. Optimal Beamforming and Performance Analysis of Wireless Relay Networks with Unmanned Aerial Vehicle

    NASA Astrophysics Data System (ADS)

    Ouyang, Jian; Lin, Min

    2015-03-01

    In this paper, we investigate a wireless communication system employing a multi-antenna unmanned aerial vehicle (UAV) as the relay to improve the connectivity between the base station (BS) and the receive node (RN), where the BS-UAV link undergoes the correlated Rician fading while the UAV-RN link follows the correlated Rayleigh fading with large scale path loss. By assuming that the amplify-and-forward (AF) protocol is adopted at UAV, we first propose an optimal beamforming (BF) scheme to maximize the mutual information of the UAV-assisted dual-hop relay network, by calculating the BF weight vectors and the power allocation coefficient. Then, we derive the analytical expressions for the outage probability (OP) and the ergodic capacity (EC) of the relay network to evaluate the system performance conveniently. Finally, computer simulation results are provided to demonstrate the validity and efficiency of the proposed scheme as well as the performance analysis.

  19. 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

  20. 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.

  1. 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…

  2. 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.

  3. 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.

  4. Analysis of SSME inspection imagery using AI approaches

    NASA Astrophysics Data System (ADS)

    Finegan, Michael K., Jr.; Wee, W. G.

    The automated analysis of SSME injector assemblies has been investigated for the cases of LOX post surface defects and injector-baffle deterioration. Defects are isolated via 2D feature extraction from borescope and camera images; temporal-frequency transforms are then used to create a multiresolution set of feature vectors representing image contents. The potential flaws thus discriminated are then segmented and classified according to known categories. AI is applied in the form of a blackboard architecture that is controlled by a rule-based production system.

  5. Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aerial multispectral images are a good source of crop, soil, and ground coverage information. Spectral reflectance indices provide a useful tool for monitoring crop growing status. A series of aerial images were acquired by an airborne MS4100 multispectral imaging system on the cotton and soybean f...

  6. 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.

  7. Deformable mirror interferometric analysis for the direct imagery of exoplanets

    NASA Astrophysics Data System (ADS)

    Mazoyer, Johan; Galicher, Raphaël.; Baudoz, Pierre; Lanzoni, Patrick; Zamkotsian, Frédéric; Rousset, Gérard

    2014-07-01

    Direct imaging of exoplanet systems requires the use of coronagraphs to reach high contrast levels (10-8 to 10-11) at small angular separations (0.100). However, the performance of these devices is drastically limited by aberrations (in phase or in amplitude, introduced either by atmosphere or by the optics). Coronagraphs must therefore be combined with extreme adaptive optic systems, composed of a focal plane wavefront sensor and of a high order deformable mirror. These adaptive optic systems must reach a residual error in the corrected wavefront of less than 0.1 nm (RMS) with a rate of 1 kHz. In addition, the surface defects of the deformable mirror, inherent from the fabrication process, must be limited in order to avoid the introduction of amplitude aberrations. An experimental high contrast bench has been developed at the Paris Observatory (LESIA). This bench includes a Boston Micromachine deformable mirror composed of 1024 actuators. For a precise analysis of its surface and performance, we characterized this mirror on the interferometric bench developed since 2004 at the Marseille Observatory (LAM). In this paper, we present this interferometric bench as well as the results of the analysis. This will include a precise surface characterization and a description of the behavior of the actuators, on a 10 by 10 actuator range (behavior of a single actuator, study of the cross-talk between neighbor actuators, influence of a stuck actuator) and on full mirror scale (general surface shape).

  8. 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.

  9. Mapping temporal changes in connectivity using high-resolution aerial data and object based image analysis

    NASA Astrophysics Data System (ADS)

    Masselink, Rens; Anders, Niels; Keesstra, Saskia; Seeger, Manuel

    2014-05-01

    Within the field of geomorphology mapping has always been an important tool to interpret spatial and temporal distributions of phenomena and processes at the surface. In the field of connectivity however, although throughout the past decade many articles have been published, there are only very few that go into the mapping of connectivity. This study aimed at developing a new, automated method for mapping connectivity within agricultural catchments. The method, which is a combination of Object-Based Image Analysis (OBIA) and traditional geomorphological field mapping, was applied to two agricultural catchments in Navarre, Spain, both with an area of approximately 2 sq.km. An unmanned aerial vehicle (UAV) was used to take aerial photographs with a resolution of 6 cm, of which a DEM with a 12 cm resolution was created using structure-from-motion photogrammetry. Connectivity was mapped within the study areas using OBIA using a top down method, meaning that connectivity was mapped at different scale levels, starting at the largest scale. Firstly sub-catchments were automatically delineated, after which several characteristics and features that affect connectivity within the sub-catchments were classified, e.g. landuse, landslides, rills, gullies, riparian vegetation, changes in slope, ploughing direction etc. In two consecutive years (2013-2014) photographs were taken and connectivity of both catchments of both years will be compared. Future work will include a quantification of the mapped connectivity (highly connected years vs. low connected years), causes and consequences of these differences in connectivity, comparison to existing connectivity indices and comparison of mapped connectivity in sub-catchments and measured discharge.

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. '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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. Analysis of ERTS imagery using special electronic viewing/measuring equipment

    NASA Technical Reports Server (NTRS)

    Evans, W. E.; Serebreny, S. M.

    1973-01-01

    An electronic satellite image analysis console (ESIAC) is being employed to process imagery for use by USGS investigators in several different disciplines studying dynamic hydrologic conditions. 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. Quantitative measurements of distances, areas, and brightness profiles can be extracted digitally under operator supervision. Initial results are presented for the display and measurement of snowfield extent, glacier development, sediment plumes from estuary discharge, playa inventory, phreatophyte and other vegetative changes.

  4. 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.

  5. 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.

  6. Forest cover type analysis of New England forests using innovative WorldView-2 imagery

    NASA Astrophysics Data System (ADS)

    Kovacs, Jenna M.

    For many years, remote sensing has been used to generate land cover type maps to create a visual representation of what is occurring on the ground. One significant use of remote sensing is the identification of forest cover types. New England forests are notorious for their especially complex forest structure and as a result have been, and continue to be, a challenge when classifying forest cover types. To most accurately depict forest cover types occurring on the ground, it is essential to utilize image data that have a suitable combination of both spectral and spatial resolution. The WorldView-2 (WV2) commercial satellite, launched in 2009, is the first of its kind, having both high spectral and spatial resolutions. WV2 records eight bands of multispectral imagery, four more than the usual high spatial resolution sensors, and has a pixel size of 1.85 meters at the nadir. These additional bands have the potential to improve classification detail and classification accuracy of forest cover type maps. For this reason, WV2 imagery was utilized on its own, and in combination with Landsat 5 TM (LS5) multispectral imagery, to evaluate whether these image data could more accurately classify forest cover types. In keeping with recent developments in image analysis, an Object-Based Image Analysis (OBIA) approach was used to segment images of Pawtuckaway State Park and nearby private lands, an area representative of the typical complex forest structure found in the New England region. A Classification and Regression Tree (CART) analysis was then used to classify image segments at two levels of classification detail. Accuracies for each forest cover type map produced were generated using traditional and area-based error matrices, and additional standard accuracy measures (i.e., KAPPA) were generated. The results from this study show that there is value in analyzing imagery with both high spectral and spatial resolutions, and that WV2's new and innovative bands can be useful

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. Phytochemical analysis, antibacterial, and antifungal assessment of aerial parts of Polygonatum verticillatum.

    PubMed

    Khan, Haroon; Saeed, Muhammad; Muhammad, Naveed; Perviz, Samreen

    2016-05-01

    The current study was designed to assess the phytochemical profile, antibacterial, and antifungal activities of the crude methanol extract of the aerial parts of Polygonatum verticillatum (PA) and its various subsequent solvent fractions using agar well diffusion, agar tube dilution, and microdilution methods. Phytochemical analysis showed positive for different chemical groups and also contained marked quantity of saponin and flavonoid contents. Significant antibacterial activity was observed against various tested pathogenic bacteria. The only susceptible Gram-positive bacterium was Bacillus subtilis and their minimum inhibitory concentrations (MICs) measured ranged from 11-50 µg/ml. The sensitive Gram-negative bacteria were Salmonella typhi and Shigella flexeneri The estimated MICs were in the range of 2-7 µg/ml and 8-50 µg/ml for S. typhi and S. flexeneri, respectively. However, the antifungal activity of the plant was limited to Microsporum canis and their MICs ranged from 60 to 250 µg/ml. Our study confirmed significant antibacterial potential of the plant and substantiated its folk use in dysentery and pyrexia of multiple origins. PMID:24311628

  12. 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

    2016-01-01

    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

  13. 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

  14. 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

  15. 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

  16. Toward generalized planetary stereo analysis scheme—Prototype implementation with multi-resolution Martian stereo imagery

    NASA Astrophysics Data System (ADS)

    Kim, Jung-Rack; Lin, Shih-Yuan; Choi, Yun-Soo; Kim, Young-Hwi

    2013-07-01

    Stereo analysis of orbital imagery is highly valuable for scientific research in planetary surface. Thus, the processing of planetary stereo imagery has been progressed with various approaches and resulted in a series of uncontrolled topographic products. In order to fully utilize the data derived from image systems carried on various planetary orbiters, the generalized algorithms of stereo image processing and Digital Terrain Model (DTM) extraction have been developed. Based on Kim and Muller's approach (2009), the algorithms were updated employing the feed-forwarded model-based matcher and the generic sensor model. It is a sort of iterative stereo procedure delivering the reference data to next stage for 3D zoom-up. Thus the system is capable of processing various stereo data sets with the generic approach and achieves stable photogrammetric accuracy of resultant DTMs. To demonstrate the potential of this stereo processing routine, the DTMs obtained from various Mars orbital images covering some sample test sites were processed with the prototype processor. As the result, the processed DTMs clearly illustrated detailed geological features and high agreement with the height spots of Mars Obiter Laser Altimeter (MOLA). It was proved that the overall processing strategy in this paper was effective and the topographic products were accurate and reliable.

  17. 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.

  18. 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

  19. Ground-Cover Measurements: Assessing Correlation Among Aerial and Ground-Based Methods

    NASA Astrophysics Data System (ADS)

    Booth, D. Terrance; Cox, Samuel E.; Meikle, Tim; Zuuring, Hans R.

    2008-12-01

    Wyoming’s Green Mountain Common Allotment is public land providing livestock forage, wildlife habitat, and unfenced solitude, amid other ecological services. It is also the center of ongoing debate over USDI Bureau of Land Management’s (BLM) adjudication of land uses. Monitoring resource use is a BLM responsibility, but conventional monitoring is inadequate for the vast areas encompassed in this and other public-land units. New monitoring methods are needed that will reduce monitoring costs. An understanding of data-set relationships among old and new methods is also needed. This study compared two conventional methods with two remote sensing methods using images captured from two meters and 100 meters above ground level from a camera stand (a ground, image-based method) and a light airplane (an aerial, image-based method). Image analysis used SamplePoint or VegMeasure software. Aerial methods allowed for increased sampling intensity at low cost relative to the time and travel required by ground methods. Costs to acquire the aerial imagery and measure ground cover on 162 aerial samples representing 9000 ha were less than 3000. The four highest correlations among data sets for bare ground—the ground-cover characteristic yielding the highest correlations (r)—ranged from 0.76 to 0.85 and included ground with ground, ground with aerial, and aerial with aerial data-set associations. We conclude that our aerial surveys are a cost-effective monitoring method, that ground with aerial data-set correlations can be equal to, or greater than those among ground-based data sets, and that bare ground should continue to be investigated and tested for use as a key indicator of rangeland health.

  20. 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.

  1. 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...

  2. 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

  3. Using Transactional Analysis and Mental Imagery to Help Shame-Based Identity Adults Make Peace with Their Past

    ERIC Educational Resources Information Center

    Adams, Susan A.

    2008-01-01

    Development of a shame-based identity, also known as "toxic shame," can significantly interfere with an adult's ability to form an intimate relationship with another. As adults find peace from their past using transactional analysis and mental imagery, they learn to empower themselves to form healthy, intimate relationships.

  4. 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

  5. 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.

  6. REMOTE SENSING OF SULFUR DIOXIDE EFFECTS ON VEGETATION - PHOTOMETRIC ANALYSIS OF AERIAL PHOTOGRAPHS

    EPA Science Inventory

    Spectral reflectances were measured by tri-band densitometry of aerial color-infrared photographs of soybean (Glycine mas fields that had been affected by sulfur dioside (SO2) emissions from large, coal-fired power plants in northwestern Alabama and western Tennessee. The photogr...

  7. "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…

  8. 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

  9. 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...

  10. 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...

  11. 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

  12. 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.

  13. Mapping a Riparian Weed with SPOT 5 Imagery and Image Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    SPOT 5 (10 m resolution) multi-spectral satellite imagery was evaluated for mapping infestations of the invasive grass giant reed (Arundo donax L.) along the Rio Grande in southwest Texas. The imagery had three bands (green, red, and near-infrared). Three subsets from the SPOT 5 image were extract...

  14. 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. PMID:26599827

  15. 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

  16. 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

  17. Contact area as the intuitive definition of contact CD based on aerial image analysis

    NASA Astrophysics Data System (ADS)

    Polonsky, Netanel; Sagiv, Amir; Mangan, Shmoolik

    2009-03-01

    As feature sizes continue to diminish, optical lithography is driven into the extreme low-k1 regime, where the high MEEF increasingly complicates the relationship between the mask pattern and the aerial image. This is true in particular for twodimensional mask patterns, which are by nature much more complicated than patterns possessing one-dimensional symmetry. Thus, the intricacy of 2D image formation typically requires a much broader arsenal of resolution enhancement techniques over complex phase shift masks, including SRAFs and OPC, as well as exotic off-axis illumination geometries. This complexity on the mask side makes the printability effect of a random defect on a 2D pattern a field of rich and delicate phenomenology. This complexity is reflected in the dispute over the CD definition of 2D patterns: some sources use the X and Y values, while others use the contact area. Here, we argue that for compact features, for which the largest dimension is not wider than the PSF of the stepper optics, the area definition is the natural one. We study the response of the aerial image to small perturbations in mask pattern. We show that any perturbation creates an effect extending in all directions, thus affecting the area and not the size in a single direction. We also show that, irrespective of the source of perturbation, the aerial signal is proportional to the variation in the area of the printed feature. The consequence of this effect is that aerial inspection signal scales linearly with the variation of printed area of the tested feature.

  18. 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

  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. 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.

  1. 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.

  2. 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

  3. 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

  4. 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

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

    PubMed

    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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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. MSS scene 1085-17294 of the Big Horn region has been subjected to detailed structural analysis. Band 7 is particularly good for revealing structural and drainage patterns because of enhance topographic detail and the subdued vegetational contrasts. Considerable stereo coverage through sidelap with adjoining scenes adds to the effectiveness of the study and has been used on both positive transparencies and enlarged prints. Negative prints of Band 7 positive transparencies have proven to be much more useful than positive prints because the higher resolution of the positive transparencies can be maintained. The Bighorn Mountains are crisscrossed by a number of prominent topographic linears, most of which can be correlated with known fault and shear zones in the Precambrian crystalline core. Many of these do not appear to continue into the flanking sedimentary rocks and a few that do (Tensleep, Tongue River lineaments) are very difficult to trace farther out into the basins. The Tongue River lineament, long a source of speculation and uncertainty as to its existence, appears as a very prominent discontinuity in the imagery.

  17. 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

  18. 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.

  19. 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

  20. 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

  1. Use of the SRI electronic satellite image analysis console for mapping southern Arizona plant communities from ERTS-1 imagery

    NASA Technical Reports Server (NTRS)

    Turner, R. M.

    1973-01-01

    Cloud-free imagery covering the Tucson, Ariz., region for the period from August 22 to November 2, 1972, was used to determine the utility of ERTS-1 data for discriminating boundaries between plant communities. The following studies were made from imagery analyzed by use of an Electronic Satellite Image Analysis Console: (1) console-generated color composites from MSS-5 and MSS-6 bands were recorded photographically from the console color monitor. The color photographs were then used to compare with short-term changes in vegetative cover observed on the ground; (2) using the console, microdensitometric traces were made along selected traverses to quantify changes in scene irradiance across the image field; (3) quantitative plant coverage data, collected at ground-truth stations along the traverses, were compared with the densitometric values.

  2. 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

  3. Coastal change analysis of Lovells Island using high resolution ground based LiDAR imagery

    NASA Astrophysics Data System (ADS)

    Ly, Jennifer K.

    Many methods have been employed to study coastline change. These methods range from historical map analysis to GPS surveys to modern airborne LiDAR and satellite imagery. These previously used methods can be time consuming, labor intensive, and expensive and have varying degrees of accuracy and temporal coverage. Additionally, it is often difficult to apply such techniques in direct response to an isolated event within an appropriate temporal framework. Here we utilize a new ground based Canopy Biomass LiDAR (CBL) system built at The University of Massachusetts Boston (in collaboration with the Rochester Institute of Technology) in order to identify and analyze coastal change on Lovells Island, Boston Harbor. Surveys of a bluff developing in an eroding drumlin and beach cusps on a high-energy cobble beach on Lovells Island were conducted in June, September and December of 2013. At each site for each survey, the CBL was set up and multiple scans of each feature were taken on a predetermined transect that was established parallel to the high-water mark at distances relative to the scale of the bluff and cusps. The scans from each feature were compiled, integrated and visualized using Meshlab. Results from our surveys indicate that the highly portable and easy to deploy CBL system produces images of exceptional clarity, with the capacity to resolve small-scale changes to coastal features and systems. The CBL, while still under development (and coastal surveying protocols with it are just being established), appears to be an ideal tool for analyzing coastal geological features and is anticipated to prove to be a useful tool for the observation and analysis of coastal change. Furthermore, there is significant potential for utilizing the low cost ultra-portable CBL in frequent deployments to develop small-scale erosion rate and sediment budget analyses.

  4. 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

  5. Analysis of aerial survey data on Florida manatee using Markov chain Monte Carlo.

    PubMed

    Craig, B A; Newton, M A; Garrott, R A; Reynolds, J E; Wilcox, J R

    1997-06-01

    We assess population trends of the Atlantic coast population of Florida manatee, Trichechus manatus latirostris, by reanalyzing aerial survey data collected between 1982 and 1992. To do so, we develop an explicit biological model that accounts for the method by which the manatees are counted, the mammals' movement between surveys, and the behavior of the population total over time. Bayesian inference, enabled by Markov chain Monte Carlo, is used to combine the survey data with the biological model. We compute marginal posterior distributions for all model parameters and predictive distributions for future counts. Several conclusions, such as a decreasing population growth rate and low sighting probabilities, are consistent across different prior specifications. PMID:9192449

  6. Wavefront aberration measurement method for a hyper-NA lithographic projection lens based on principal component analysis of an aerial image.

    PubMed

    Zhu, Boer; Wang, Xiangzhao; Li, Sikun; Yan, Guanyong; Shen, Lina; Duan, Lifeng

    2016-04-20

    A wavefront aberration measurement method for a hyper-NA lithographic projection lens by use of an aerial image based on principal component analysis is proposed. Aerial images of the hyper-NA lithographic projection lens are expressed accurately by using polarized light and a vector imaging model, as well as by considering the polarization properties. As a result, the wavefront aberrations of the hyper-NA lithographic projection lens are measured accurately. The lithographic simulator PROLITH is used to validate the accuracies of the wavefront aberration measurement and analyze the impact of the polarization rotation of illumination on the accuracy of the wavefront aberration measurement, as well as the degree of polarized light and the sample interval of aerial images. The result shows that the proposed method can retrieve 33 terms of Zernike coefficients (Z5-Z37) with a maximum error of less than 0.00085λ. PMID:27140087

  7. Resolution enhancement of multichannel microwave imagery from the Nimbus-7 SMMR for maritime rainfall analysis

    NASA Technical Reports Server (NTRS)

    Olson, William S.; Weinman, James A.; Chin, Roland T.; Yeh, Chia-Lung

    1986-01-01

    A restoration of the 37, 21, 18, 10.7, and 6.6 GHz satellite imagery from the scanning multichannel microwave radiometer (SMMR) aboard Nimbus-7 to 22.2 km resolution is attempted using a deconvolution method based upon nonlinear programming. The images are deconvolved with and without the aid of prescribed constraints, which force the processed image to abide by partial a priori knowledge of the high-resolution result. The restored microwave imagery may be utilized to examine the distribution of precipitating liquid water in marine rain systems.

  8. Resolution enhancement of multichannel microwave imagery from the Nimbus-7 SMMR for maritime rainfall analysis

    NASA Technical Reports Server (NTRS)

    Olson, W. S.; Yeh, C. L.; Weinman, J. A.; Chin, R. T.

    1985-01-01

    A restoration of the 37, 21, 18, 10.7, and 6.6 GHz satellite imagery from the scanning multichannel microwave radiometer (SMMR) aboard Nimbus-7 to 22.2 km resolution is attempted using a deconvolution method based upon nonlinear programming. The images are deconvolved with and without the aid of prescribed constraints, which force the processed image to abide by partial a priori knowledge of the high-resolution result. The restored microwave imagery may be utilized to examined the distribution of precipitating liquid water in marine rain systems.

  9. 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

  10. Assessing plantation canopy condition from airborne imagery using spectral mixture analysis and fractional abundances

    NASA Astrophysics Data System (ADS)

    Goodwin, Nicholas; Coops, Nicholas C.; Stone, Christine

    2005-05-01

    Pine plantations in Australia are subject to a range of abiotic and biotic damaging agents that affect tree health and productivity. In order to optimise management decisions, plantation managers require regular intelligence relating to the status and trends in the health and condition of trees within individual compartments. Remote sensing technology offers an alternative to traditional ground-based assessment of these plantations. Automated estimation of foliar crown health, especially in degraded crowns, can be difficult due to mixed pixels when there is low or fragmented vegetation cover. In this study we apply a linear spectral unmixing approach to high spatial resolution (50 cm) multispectral imagery to quantify the fractional abundances of the key image endmembers: sunlit canopy, shadow, and soil. A number of Pinus radiata tree crown attributes were modelled using multiple linear regression and endmember fraction images. We found high levels of significance ( r2 = 0.80) for the overall crown colour and colour of the crown leader ( r2 = 0.79) in tree crowns affected by the fungal pathogen Sphaeropsis sapinea, which produces both needle necrosis and chlorosis. Results for stands associated with defoliation and chlorosis through infestation by the aphid Essigella californica were lower with an r2 = 0.33 for crown transparency and r2 = 0.31 for proportion of crown affected. Similar analysis of data from a nitrogen deficient site produced an outcome somewhat in between the other two damaging agents. Overall the sunlit canopy image fraction has been the most important variable used in the modelling of forest condition for all damaging agents.

  11. 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%.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Data flow analysis for transition from film to electronic imagery management

    NASA Astrophysics Data System (ADS)

    Hedgcock, Marcus W.; Smith, Suzy; Levitt, Tod S.

    1992-07-01

    The transition from analog film-based to electronic imagery management in radiology departments and clinics requires accurate projection of storage and network capabilities. We previously developed a method of estimating from film usage, static storage requirements for the central archive systems. Planning requires us to project: (a) intermediate (e.g. magnetic disk) storage needs for local area networks and workstations serving clinical care areas, and (b) data transmission rates needed to deliver data to nodes on the network, given the expected dataflows empirically derived in our previous studies. The majority of medical imagery is currently stored on 14'' by 17'' film, each film representing about 6 Mbytes of storage at current standard digitization resolutions. With such applications, initial projections of data rates can be made using records of film usage available in most departments. However, it is also necessary to perform a survey of film users to determine usage of new imagery modalities and comparison imagery requirements in the areas to be served by the network.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. Measuring creative imagery abilities.

    PubMed

    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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Analysis of ERTS-1 imagery of Wyoming and its application to evaluation of Wyoming's natural resources

    NASA Technical Reports Server (NTRS)

    Marrs, R. W.; Breckenridge, R. M.

    1973-01-01

    The author has identified the following significant results. The Wyoming investigation has progressed according to schedule during the Jan. - Feb., 1973 report period. A map of the maximum extent of Pleistocene glaciation was compiled for northwest Wyoming from interpretations of glacial features seen on ERTS-1 imagery. Using isodensitometry as a tool for image enhancement, techniques were developed which allowed accurate delineation of small urban areas and provided distinction of broad classifications within these small urban centers.

  10. Analysis of terrain data based on satellite imagery for aviation purposes

    NASA Astrophysics Data System (ADS)

    Eilmus, B.; Heidelmeyer, G.; Klingauf, U.

    2007-10-01

    Due to the regulation of the ICAO (International Civil Aviation Organization), which requires the provision of electronic terrain data with a certain quality by each contracting state for its territory, the demand for terrain data for aviation purposes increases. This regulation poses a problem particularly for developing and newly industrialising countries, which have not the financial resources for the generation of terrain data meeting the required specifications. Studies performed at the Institute of Flight Systems and Automatic Control at the Technische Universitaet Darmstadt show that a promising and cost-effective method to encounter this challenge is the use of high resolution optical satellite imagery with a stereoscopic coverage. This method can be performed without the acquisition of ground control points and leads by this to cost reductions. To validate this method, the accuracy of terrain data generated from satellite imagery is analysed. Due to the various available very high resolution satellites, the accuracy is not limited by the spatial resolution of the imagery, but principally by the accuracy of the geolocation. This is why furthermore methods are proposed that may help to increase the accuracy, to eliminate blunders as well as systematic errors and thus to enhance the reliability of the acquired terrain information in order to achieve applicability in aviation.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. Utility of hyperspectral imagery for seagrass mapping in Tampa Bay

    NASA Astrophysics Data System (ADS)

    Carlson, P. R.

    2006-12-01

    Tampa Bay has lost significant amounts of seagrass as the result of declines in water clarity. Of the 16,300 ha of seagrass present in 1950, only 8800 ha remained in 1982. However, since the mid 1980's, a concerted effort has been made to improve Tampa Bay water quality, and seagrass cover increased to 10500 ha in 2002. This project was undertaken to determine whether hyperspectral imagery can be used to 1) replace traditional seagrass mapping methods and 2) distinguish between seagrasses and macroalgae such as Caulerpa prolifera. Hyperspectral imagery of the shoreline of Tampa Bay was acquired in May 2005, using the AISA hyperspectral sensor flown on an aircraft at an altitude of 1500 m. For seagrass mapping tests, a study area near Apollo Beach, Florida was selected for analysis. The area was selected because it contains a number of features which make seagrass classification from natural color aerial photographs extremely difficult: variable water depth, CDOM, and mixed seagrass/algal species composition. Classification accuracy was assessed using confusion matrices based on a separate group of 155 data points selected haphazardly throughout the image. Unsupervised classification by the Isodata method using all 90 spectral bands between 394 and 803 nm resulted in poor classification accuracy. However, first derivative spectra identified six key wavelengths with potential for habitat classification (770, 759, 717, 688, 589, and 492 nm). Minimum distance classification based on these six wavelengths improved overall classification accuracy to 95 percent. The prospect of replacing manual interpretation of aerial photography with supervised classification of hyperspectral imagery seems very feasible. With some additional testing, the technique may become the operational standard for seagrass mapping in Tampa Bay.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. Analysis of the reasons for accidents and of protective measures against induced voltage on aerial electrical transmission lines

    SciTech Connect

    Misrikhanov, M. Sh.; Mirzaabdullaev, A. O.

    2009-01-15

    The problem of safety during work on aerial transmission lines under an induced voltage is examined. Results are presented from a study of the causes of accidents over the last 20 years in electrical grids in this country. A determination of different levels of induced voltage on disconnected aerial transmission lines as a function of their grounding scheme is proposed. The order of magnitudes for each level are given, along with approximate expressions for calculating them.

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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

  6. Analysis of high-resolution remote sensing imagery with textures derived from single pixel objects

    NASA Astrophysics Data System (ADS)

    de Kok, R.; Tasdemir, K.

    2011-11-01

    The application of co-occurrence matrices for the calculation of contrast in satellite imagery is a common approach. The textural as well as contextual information from these grey level co-occurrence matrix (GLCM) calculations encounter restrictions due to compromises in their practical implementation. As an alternative, a contrast calculation inside an object-based (OBIA) environment (eCognition) using single-pixel objects is considered. This requires fewer compromises in the implementation, with the flexibility of experimenting on the influence of much larger contextual information for single pixels by expanding the search radius. The contextual information based on contrast can be applied in the classification of the agricultural domain as well as a variety of classes in the 1:25.000 land use/cover classification. The OBIA environment enables a rapid evaluation on various spatial and spectral feature attributes. This allows an evaluation of context on an ever increasing search radius without using larger disk space for synthetic imagery. After the initial evaluation, a small selection of essential contrast maps can be exported as GeoTiff files to allow an input for automated methods. If proven useful, GeoTiff export becomes redundant and the integration of classification methods such as self-organizing maps into the OBIA environment allows effective use of contrast characteristics on small and large neighborhoods.

  7. 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.

  8. Analysis of urban reflectance and urban sprawl in China using TM/ETM+ imagery

    NASA Astrophysics Data System (ADS)

    Zhang, Hongen; Qiu, Yanling; Chen, Ling; Zhao, Jianfu

    2006-12-01

    The future world is a world of city. Spectral characterization of urban reflectance is important. The overall reflectance of the urban mosaic is determined by the spectral reflectance of surface materials and shadows and their spatial distribution. Building materials dominate net reflectance in most cities but in many cases vegetation also has a very strong influence on urban reflectance. In the study, the spectral characterization of urban reflectance properties is analyzed using Landsat TM and ETM+ imagery of a collection of the province capital city in China. The result shows these urban areas have similar mixing space topologies and can be represented by three-component linear mixture models The reflectance of these cities can be described as linear combinations of High Albedo, Dark and Vegetation spectral endmembers within a three dimensional mixing space containing over 80% of the variance in the observed reflectance. The relative proportions of these endmembers vary considerably among different cities but in all cases the reflectance of the urban core lies near the dark end and the new build-up areas near the light end of a mixing line between the High Albedo and Dark endmembers. In spite of the spectral heterogeneity, built-up areas do occupy distinct regions of the spectral mixing space. Based on the above analyzation, the urban spatial extent of 34 cities of China, representing the physical manifestation of a range of social, economic, cultural, and political dimensions associated with urban dynamics, was mapped using Landsat imagery collected of 1990 and 2000.

  9. 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.

  10. 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

  11. A meta-analysis of imagery rehearsal for post-trauma nightmares: effects on nightmare frequency, sleep quality, and posttraumatic stress.

    PubMed

    Casement, Melynda D; Swanson, Leslie M

    2012-08-01

    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 from the initial to post-treatment assessments. These effects were sustained through 6 to 12 months 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, sleep and circadian regulation). PMID:22819998

  12. 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

  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. 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.

  15. Preliminary analysis of remote infrared imagery of shuttle during entry: An aerothermodynamic flight experiment

    NASA Technical Reports Server (NTRS)

    Swenson, B. L.; Edsinger, L. E.

    1977-01-01

    The preliminary feasibility of remote high-resolution infrared imagery of the space shuttle orbiter lower surface during entry to obtain accurate measurements of aerodynamic heat transfer to that vehicle was examined. In general, it was determined that such such images can be taken from an existing aircraft/telescope system (the C-141 AIRO) with a minimum modification or addition of systems using available technology. These images will have a spatial resolution of about 0.3 m and a temperature resolution much better than 2.5 percent. The data from these images will be at conditions and at a scale not reproducible in ground based facilities and should aid in the reduction of the prudent factors of safety required to account for phenomenological uncertainties on the thermal protection system design. Principal phenomena to be observed include laminar heating, boundary-layer transition, turbulent heating, surface catalysis, and flow separation and reattachment.

  16. 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.

  17. 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., Jr.; 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.

  18. 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

  19. 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.

  20. Automated radar image analysis research in support of military needs

    NASA Astrophysics Data System (ADS)

    Rohde, Frederick W.; Chen, Pi-Fuay; Hevenor, Richard A.

    1986-10-01

    Synthetic aperture radars (SAR) are high resolution radars that can be used for reconnaissance, surveillance, and terrain analysis. The high resolution in range and azimuth is achieved by pulse compression and phase history processing, respectively. SAR images have much in common with optical images such as aerial photographs. Both are characterized by tones, patterns, shapes, and shadows. There are, however, significant differences between SAR and optical images due to the differences in the wavelengths and in the illumination and reflection of the targets. Cloud cover presents an obstacle to optical imagery but not to SAR imagery because radar waves can penetrate cloud cover. Optical imagery provides more detailed information than SAR imagery because of its higher resolution. The resolution of optical imagery decreases with distance whereas the resolution of SAR imagery is independent of distance. For large distances, for example from satellites to the surface of the Earth, the resolution of SAR imagery approaches the resolution of optical imagery. These properties make SAR a very useful tool for military purposes. SAR systems can collect large quantities of imagery. For the timely and economic analysis and interpretation of SAR imagery there is a need for the development of automated and interactive capabilities that will reduce the dependency on and requirements for highly trained image analysts.

  1. 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

  2. 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.

  3. 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.

  4. ERTS imagery for ground-water investigations

    USGS Publications Warehouse

    Moore, Gerald K.; Deutsch, Morris

    1975-01-01

    ERTS imagery offers the first opportunity to apply moderately high-resolution satellite data to the nationwide study of water resources. This imagery is both a tool and a form of basic data. Like other tools and basic data, it should be considered for use in ground-water investigations. The main advantage of its use will be to reduce the need for field work. In addition, however, broad regional features may be seen easily on ERTS imagery, whereas they would be difficult or impossible to see on the ground or on low-altitude aerial photographs. Some present and potential uses of ERTS imagery are to locate new aquifers, to study aquifer recharge and discharge, to estimate ground-water pumpage for irrigation, to predict the location and type of aquifer management problems, and to locate and monitor strip mines which commonly are sources for acid mine drainage. In many cases, boundaries which are gradational on the ground appear to be sharp on ERTS imagery. Initial results indicate that the accuracy of maps produced from ERTS imagery is completely adequate for some purposes.

  5. Remote sensing reconnaissance of faulting in alluvium, Lake Mead to Lake Havasu, California, Nevada and Arizona. An application of ERTS-1 satellite imagery

    NASA Technical Reports Server (NTRS)

    Bechtold, I. C. (Principal Investigator); Liggett, M. A.; Childs, J. F.

    1973-01-01

    The author has identified the following significant results. Analysis of ERTS-1 MSS and other imagery for a 125 x 25 mile area in the southern part of the Basin-Range Province of southeastern California, southern Nevada, and northwestern Arizona indicates the presence of numerous color and contrast anomalies in alluvium. Field work guided by high altitude U-2 and side-looking aerial radar imagery confirmed that these anomalies are fault zones, many of which are believed to be of recent age. Few faults in alluvium have been reported from previous ground based geologic studies in the area. ERTS-1 imagery provides a synoptic perspective previously unavailable for regional geologic studies. The ability to conduct rapid and inexpensive reconnaissance of recent faulting has important applications to land use planning, ground water exploration, geologic hazards, and the siting and design of engineering projects.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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. PMID:26251060

  11. 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.

  12. 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.

  13. 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.

  14. 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%.

  15. 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.

  16. 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.

  17. Experimental analysis of bed load sediment motions using high-speed imagery

    NASA Astrophysics Data System (ADS)

    Fathel, S. L.; Furbish, D. J.; Schmeeckle, M. W.

    2013-12-01

    Bed load sediment particles move as complex motions over the surface of a stream bed, accelerating and decelerating in response to the near-bed turbulence and due to particle-bed interactions. Using high-speed imagery of coarse sand particles on a planer bed surface, we track individual particle hops from start to stop. This work re-examines, and adds to, previously published measurements taken from flume experiments, such that we are able to better characterize these hopping motions. In particular, we analyze both the cross-stream and streamwise hop distances in combination with their associated travel times. Measurements confirm that the cross-stream particle hop distances scale with travel time to the 4/3 power and the streamwise hop distances scale with travel time to the 5/3 power. Even though both of these hopping motions scale with travel time, we find that streamwise motions are generally less scattered about the 5/3 relation in comparison with more erratic cross-stream motions. As previously suggested, the probability density function of the streamwise hop distances takes the form of a gamma-like distribution, where a large portion of the motions are small, positive distances. In contrast to previous work, we find that the probability density function of the travel times takes the form of an exponential-like distribution, which suggests a steady disentrainment rate with respect to time following particle entrainment. Collectively, these data represent a sample from the joint probability density function of hop distances and travel times. This work is aimed at developing a deeper understanding of this joint probability density function, sediment entrainment and disentrainment, and issues arising from time and window censorship, wherein the censored data may represent a biased description of the underlying ensemble distribution of hop distances and travel times.

  18. 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. PMID:26099149

  19. 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)…

  20. SAR imagery of the Grand Banks (Newfoundland) pack ice pack and its relationship to surface features

    NASA Technical Reports Server (NTRS)

    Argus, S. D.; Carsey, F. D.

    1988-01-01

    Synthetic Aperture Radar (SAR) data and aerial photographs were obtained over pack ice off the East Coast of Canada in March 1987 as part of the Labrador Ice Margin Experiment (LIMEX) pilot project. Examination of this data shows that although the pack ice off the Canadian East Coast appears essentially homogeneous to visible light imagery, two clearly defined zones of ice are apparent on C-band SAR imagery. To identify factors that create the zones seen on the radar image, aerial photographs were compared to the SAR imagery. Floe size data from the aerial photographs was compared to digital number values taken from SAR imagery of the same ice. The SAR data of the inner zone acquired three days apart over the melt period was also examined. The studies indicate that the radar response is governed by floe size and meltwater distribution.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Integrating horizontal borehole imagery and cluster analysis with microseismic data for Niobrara/Codell reservoir characterization, Wattenberg Field, Colorado, USA

    NASA Astrophysics Data System (ADS)

    Dudley, Colton M.

    Unconventional reservoirs are multi-variate problems requiring integration of data across multiple disciplines. Integration of multi-scale data to solve shale plays has become increasingly more common (Roth (2010), Norton (2011), Quirein et al. (2012), Xie et al. (2012), Close et al. (2012). In this thesis I examine microseismic data heterogeneity by integrating borehole imagery and cluster analysis of the well logs along the horizontal sections of two horizontal wells to delineate microseismic data trends. Microseismic data are the direct measurement of the real time hydraulic fracture treatment or stimulation and reveals the reaction of the subsurface to stimulation. Microseismic data are often not studied at the wellbore scale, yet this is exactly where the stimulation initiates. Horizontal wells are rarely horizontal. The well can traverse tens of feet from the heel to the toe of the well and undulate in and out of the pay. In addition, the geologic structure intersecting the well, such as faults, can cause the well to penetrate varying lithology without a change in well deviation or azimuth. Thus, stage locations along the horizontal section of the well are in and out of the pay and as a result affect the stimulation and the microseismic data. Therefore, I examine the lithological and structural components along the entire horizontal section of two wells and utilize the results to delineate the microseismic data heterogeneity. Integrating horizontal borehole imagery and cluster analysis can aid in quantifying the lithology and structure controlling microseismic data heterogeneity. Areas depicting a distinct difference in microseismic data trends are primarily due to the lithology and structure along the horizontal wellbore. It was found that linear microseismic data trends are due to lack of a natural fracture network and are affected by the modern day stress field and clustered microseismic data trends are due to a complex natural fracture network and an

  7. Effect of Amazon smoke on cloud microphysics and albedo - analysis from satellite imagery

    SciTech Connect

    Kaufman, Y.J. ); Nakajima, Teruyuki )

    1993-04-01

    NOAA Advanced Very High Resolution Radiometer images taken over the Brazilian Amazon Basin during the biomass burning season of 1987 are used to study the effect of smoke aerosol particles on the properties of low cumulus and stratocumulus clouds. The reflectance at a wavelength of 0.64 [mu]m and the drop size, derived from the cloud reflectance at 3.75 [mu]m, are studied for tens of thousands of clouds. The opacity of the smoke layer adjacent to each cloud is also monitored simultaneously. Satellite data can be used to generate large-scale statistics of the properties of clouds and surrounding aerosol from which the interaction of aerosol with clouds can be surmised. To minimize the effect of variations in the precipitable water vapor and in other smoke and cloud properties, biomass burning in the tropics is chosen as the study topic. The results are averaged for numerous clouds with the same ambient smoke optical thickness. It is shown that the presence of dense smoke can reduce the remotely sensed drop size of continental cloud drops from 15 to 9 [mu]m. Due to the high initial reflectance of clouds in the visible part of the spectrum and the presence of graphitic carbon, the average cloud reflectance at 0.64 [mu]m is reduced from 0.71 to 0.68 for an increase in smoke optical thickness from 0.1 to 2.0. The measurements are compared to results from other years. A high concentration of aerosol particles causes a decrease in the cloud-drop size and that smoke darkens the bright Amazonian clouds. Comparison with theoretical computations based on Twomey's model show that it is possible to explain the reduction in the cloud reflectance at 0.64 [mu]m for smoke imagery index of -0.02 to -0.03. Smoke particles are hygroscopic and have a similar size distribution to maritime and anthropogenic sulfuric aerosol particles. These results may also be representative of the interaction of sulfuric particles with clouds. 65 refs., 10 figs., 3 tabs.

  8. 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

  9. 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.

  10. 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

  11. Aerial photographic reproductions

    USGS Publications Warehouse

    U.S. Geological Survey

    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.

  12. 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.

  13. 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

  14. Kuroshio front in the East China Sea: Joint analysis of oceanographic data, RADARSAT-1 SAR and multi-sensor imagery

    NASA Astrophysics Data System (ADS)

    Litovchenko, K.; Ivanov, A.; He, M. X.

    2003-04-01

    The unique RADARSAT-1 synthetic aperture radar (SAR) (ScanSAR Narrow A mode) image in the East China Sea covering of the Kuroshio frontal zone from the Luson Strait (Taiwan) to Cheju Island (Korea) has been acquired on November 19, 2000. In addition, 2 ERS-2 SAR.PRI images covering the adjacent areas have been acquired in November 2000. On the basis of the in situ observations and satellite remote sensing data the surface manifestations visible on the SAR images are analyzed. To support image analysis of the signature of the Kuroshio front a multi-sensor approach has been applied and available data/measurements in this area have been collected and used. Topex-Poseidon data, monthly averaged sea surface temperature (SST) field from NOAA satellites and SeaWiFS-based chlorophyll-a distribution have been additionally used. Imagery from space was also accompanied by measurements of the standard oceanographic and meteorological parameters, wind and surface wave characteristic records available from the oceanographic databases of China and Japan, as well as data/measurements collected by the ships crossing the frontal zone. Satellite imagery and in situ data also document the existence of the frontal zone with pronounced western boundary coinciding with the SAR image signature. SAR signatures of oceanic fronts are considered are a result of action of a number of physical mechanisms changing the sea surface roughness, among them are: (1) surface wave-current interaction modulated spectrum of surface waves; (2) difference in atmospheric boundary layer stability due to air-sea differences causing changes in radar backscatter, and (3) damping short waves due to oil films accumulation in convergent zones. By comparing and analyzing all available data, it’s concluded that the SAR signature of the Kuroshio front is a result, mainly, of surface wave-current interaction at observed winds more than of 10-12 m/s. The surface roughness responsible for backscatter contrast (up to 5

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  2. 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

  3. 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

  4. Spatial pattern analysis in Persian oak (Quercus brantii var. persica) forests on B&W aerial photographs.

    PubMed

    Erfanifard, Yousef; Feghhi, Jahangir; Zobeiri, Mahmoud; Namiranian, Manouchehr

    2009-03-01

    The purpose of this investigation was to develop a method to determine the spatial pattern of trees as a robust indicator to monitor changes from B&W aerial photographs in Persian oak forests of Zagros, Iran. A 500 x 600 m study area was selected in Servak forests next to Yasuj city in Kohgiluyeh-Va-BuyerAhmad Province. All the trees were tagged in the study area and the point map of stems were prepared. The spatial distribution of trees was determined as "dispersed" using nearest neighbour technique. Then the index of "C" calculated by T-square sampling method was applied to the point map of the study area in 30 systematic sample points in a 100 x 100 m network. Comparing the results of this method with the true spatial pattern of the study area showed that "C" can detect the spatial arrangement of trees. Thereafter the index was used on the air photo of the study area that was made of B&W aerial photographs. The method suggested in this study provides a suitable approach for detecting the spatial pattern of trees in Zagros forests on B&W air photos. PMID:18351437

  5. 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.

  6. 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

  7. 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

  8. Assessing the spatial fidelity of resolution-enhanced imagery using Fourier analysis: a proof-of-concept study

    NASA Astrophysics Data System (ADS)

    Civco, Daniel L.; Witharana, Chandi

    2012-10-01

    Pan-sharpening of moderate resolution multispectral remote sensing data with those of a higher spatial resolution is a standard practice in remote sensing image processing. This paper suggests a method by which the spatial properties of resolution merge products can be assessed. Whereas there are several accepted metrics, such as correlation and root mean square error, for quantifying the spectral integrity of fused images, relative to the original multispectral data, there is less agreement on a means by which to assess the spatial properties, relative to the original higher-resolution, pansharpening data. In addition to qualitative, visual, and somewhat subjective evaluation, quantitative measures used have included correlations between high-pass filtered panchromatic and fused images, gradient analysis, wavelet analysis, among others. None of these methods, however, fully exploits the spatial and structural information contained in the original high resolution and fused images. This paper proposes the use of the Fourier transform as a means to quantify the degree to which a fused image preserves the spatial properties of the pan-sharpening high resolution data. A highresolution 8-bit panchromatic image was altered to produce a set of nine different test images, as well as a random image. The Fourier Magnitude (FM) image was calculated for each of the datasets and compared via FM to FM image correlation. Furthermore, the following edge detection algorithms were applied to the original and altered images: (a) Canny; (b) Sobel; and (c) Laplacian. These edge-filtered images were compared, again by way of correlation, with the original edge-filtered panchromatic image. Results indicate that the proposed method of using FTMI as a means of assessing the spatial fidelity of high-resolution imagery used in the data fusion process outperforms the correlations produced by way of comparing edge-enhanced images.

  9. Imagery of pineal tumors.

    PubMed

    Deiana, G; Mottolese, C; Hermier, M; Louis-Tisserand, G; Berthezene, Y

    2015-01-01

    Pineal tumors are rare and include a large variety of entities. Germ cell tumors are relatively frequent and often secreting lesions. Pineal parenchymal tumors include pineocytomas, pineal parenchymal tumor of intermediate differentiation, pineoblastomas and papillary tumors of the pineal region. Other lesions including astrocytomas and meningiomas as well as congenital malformations i.e. benign cysts, lipomas, epidermoid and dermoid cysts, which can also arise from the pineal region. Imagery is often non-specific but detailed analysis of the images compared with the hormone profile can narrow the spectrum of possible diagnosis. PMID:25676911

  10. Low-Altitude Coastal Aerial Photogrammetry for High-Resolution Seabed Imaging and Habitat Mapping of Shallow Areas

    NASA Astrophysics Data System (ADS)

    Alevizos, E.

    2012-04-01

    This paper explores the application of Kite Aerial Photography at the coastal environment along with digital photogrammetry for seabed geomorphological mapping. This method takes advantage of sea-water clearance that allows the transmission of sunlight through the water column and backscatter of seabed reflection under certain conditions of sunlight, weather and sea state. We analyze the procedure of acquisition, processing and interpretation of kite aerial imagery from the sub-littoral zone up to 5 meters depth. Using a calibrated non-metric digital compact camera we managed to acquire several vertical aerial images from two coastal sites in the Attica Peninsula (Greece) covering an area of approximately 200x100 meters. Both sites express significant geomorphological variability and they have a relatively smooth slope profile. For the photogrammetric processing we acquired topographic and bathymetric survey simultaneously with Kite Aerial Photography using a portable GPS of sub-meter accuracy. In order to deal with bottom control measurements we developed Bottom Control Points which were placed on the seabed. These act like the Ground Control Points and they can be easily deployed in the marine environment. The processing included interior and exterior orientation as well as ortho-rectification of images. This produced final orthomosaics for each site at scales 1:500 - 1:1500 with a resolution of a few centimeters. Interpretation of the seabed was based on color and texture features of certain areas with explicit seabed reflectivity and was supported by underwater photographs for ground truthing. At the final stage of image analysis, we recognized the boundaries (contrasting reflectivity) between different bottom types and digitized them as 2D objects using GIS. Concluding, this project emphasizes on the advantages and physical restrictions of Kite Aerial Photography in mapping small-scale geomorphological features in coastal, estuarine and lagoonal environments

  11. 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.

  12. 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

  13. 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...

  14. Use of unmanned aerial vehicles (UAV) for urban tree inventories

    NASA Astrophysics Data System (ADS)

    Ritter, Brian A.

    In contrast to standard aerial imagery, unmanned aerial systems (UAS) utilize recent technological advances to provide an affordable alternative for imagery acquisition. Increased value can be realized through clarity and detail providing higher resolution (2-5 cm) over traditional products. Many natural resource disciplines such as urban forestry will benefit from UAS. Tree inventories for risk assessment, biodiversity, planning, and design can be efficiently achieved with the UAS. Recent advances in photogrammetric processing have proved automated methods for three dimensional rendering of aerial imagery. Point clouds can be generated from images providing additional benefits. Association of spatial locational information within the point cloud can be used to produce elevation models i.e. digital elevation, digital terrain and digital surface. Taking advantage of this point cloud data, additional information such as tree heights can be obtained. Several software applications have been developed for LiDAR data which can be adapted to utilize UAS point clouds. This study examines solutions to provide tree inventory and heights from UAS imagery. Imagery taken with a micro-UAS was processed to produce a seamless orthorectified image. This image provided an accurate way to obtain a tree inventory within the study boundary. Utilizing several methods, tree height models were developed with variations in spatial accuracy. Model parameters were modified to offset spatial inconsistencies providing statistical equality of means. Statistical results (p = 0.756) with a level of significance (α = 0.01) between measured and modeled tree height means resulted with 82% of tree species obtaining accurate tree heights. Within this study, the UAS has proven to be an efficient tool for urban forestry providing a cost effective and reliable system to obtain remotely sensed data.

  15. Using google street view for systematic observation of the built environment: analysis of spatio-temporal instability of imagery dates

    PubMed Central

    2013-01-01

    Background Recently, Google Street View (GSV) has been examined as a tool for remotely conducting systematic observation of the built environment. Studies have found it offers benefits over in-person audits, including efficiency, safety, cost, and the potential to expand built environment research to larger areas and more places globally. However, one limitation has been the lack of documentation on the date of imagery collection. In 2011, Google began placing a date stamp on images which now enables investigation of this concern. This study questions the spatio-temporal stability in the GSV date stamp. Specifically, is the imagery collected contemporaneously? If not, how frequently and where is imagery from different time periods woven together to represent environmental conditions in a particular place. Furthermore, how much continuity exists in imagery for a particular time period? Answering these questions will provide guidance on the use of GSV as a tool for built environment audits. Methods GSV was used to virtually “drive” five sites that are a part of the authors’ ongoing studies. Each street in the sites was “driven” one mouse-click at a time while observing the date stamp on each image. Every time the date stamp changed, this “disruption” was marked on the map. Every street segment in the site was coded by the date the imagery for that segment was collected. Spatial query and descriptive statistics were applied to understand the spatio-temporal patterns of imagery dates. Results Spatio-temporal instability is present in the dates of GSV imagery. Of the 353 disruptions, 82.4% occur close to (<25 m) intersections. The remainder occurs inconsistently in other locations. The extent of continuity for a set of images collected with the same date stamp ranged from 3.13 m to 3373.06 m, though the majority of continuous segments were less than 400 m. Conclusion GSV offers some benefits over traditional built environment audits. However, this

  16. Comprehensive analysis of Shuttle Orbiter leeside surface infrared imagery obtained during atmospheric entry

    NASA Technical Reports Server (NTRS)

    Myrick, D. L.; Throckmorton, D. A.

    1986-01-01

    The thermographic analysis techniques developed for processing of data from the Shuttle Infrared Leeside Temperature Sensing (SILTS) experiment are discussed. The SILTS experiment will obtain high-spatial-resolution infrared images of the leeside of the Space Shuttle Orbiter during atmospheric entry by means of a scanning infrared radiometer located atop the orbiter's vertical stabilizer. Comprehensive analysis of the SILTS thermography requires accurate consideration of all those factors (such as geometry of the observed surfaces, local surface emissivity, solar radiation, and other potential sources of image degradation) which may potentially affect the output of the infrared radiometer. An overview of the entire data processing procedure and brief descriptions of the data processing algorithms are presented.

  17. Contribution of high resolution PLEIADES imagery to active faults analysis. Case study of the Longriba Fault System, eastern Tibet.

    NASA Astrophysics Data System (ADS)

    Ansberque, Claire; Bellier, Olivier; Godard, Vincent; Lasserre, Cécile; Wang, Mingming; Xu, Xiwei; Tan, Xibin

    2015-04-01

    High resolution imagery has largely developed during those two last decades allowing the possibility to observe and quantify geological and geomorphological features ranging from meter to few centimeters. Active tectonic and geomorphological studies have greatly benefited from the systematic use of such data. For that reason, we tested the contribution of PLEAIDES images to the analysis of an active strike-slip fault system in eastern Tibet. We used 50 cm resolution panchromatic PLEIADES images in order to map active fault segmentation, localize offsets of geomorphic markers and quantify vertical and horizontal displacements. We propose a preliminary study using PLEIADES images along the Longriba Fault System (LFS). The LFS, located at the eastern Tibetan Plateau margin, is constituted of two NW-SE dextral strike-slip and parallel fault zones: Longriqu and Maoergai, 80 and 120 km-long, respectively. It accommodates ~4 mm/yr dextral slip and very few vertical motion. We used stereo-pairs to build relative Digital Elevation Models (DEMs) (without ground control points) with a horizontal resolution ranging from 2 to 5 m, in order to understand the geometry of the system. We measured fault segments with lengths ranging from a hundred meters to several kilometers which are relatively close from each others, and several offsets of geomorphic markers (alluvial fans, ridges, rivers) ranging from a few meters to ~40 m. According to the segmentation deduced from those results we suggest that the fault has a high seismic potential (>Mw7.0) and that probably many surface rupturing earthquakes occurred along the LFS over the Holocene.

  18. 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

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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…

  7. 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

  8. 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

  9. 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.

  10. Urban expansion analysis based on spatial variables derived from multi-temporal remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Yang, Yetao; Wang, Yingying; Zhou, Qiming; Gong, Jianya

    2008-10-01

    In this research, we focus on the spatial pattern of the urban expansion. The spatial pattern of the urban area can be quantitatively delineated by many spatial variables. Numerous spatial variables have been examined to evaluate their applicability to the urban change. These metrics include road network accessibility, built-up density and some landscape metrics. Remote sensing technology was used for monitoring dynamic urban change. Multi-temporal Landsat TM images (1988, 1991, 1994, 1997, 2000, and 2002) were used for the change detection using post-classification comparison method. The road network and its change were extracted from multitemporal images using the GDPA algorithm. Contagion, one of the landscape metrics, was selected, because it it can describe the heterogeneity of the suburban area, where the landuse change is most likely to happen. Analysis has also been conducted to identify the relationship between urban change and these spatial variables.

  11. 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.

  12. 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

  13. 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.

  14. A Superposed Epoch Analysis of Geomagnetic Storms over a Solar Cycle: Geomagnetic and Solar Wind Data, Radar Backscatter & Auroral Imagery

    NASA Astrophysics Data System (ADS)

    Hutchinson, J. A.; Wright, D. M.; Milan, S. E.; Grocott, A.

    2010-12-01

    Geomagnetic storms - episodes of intense solar wind-magnetosphere coupling usually associated with extreme conditions in the solar wind such as coronal mass ejections (CMEs) or co-rotating interaction regions (CIRs) - cause large global disturbances in the Earth’s magnetosphere. During such storms, large amounts of energy are deposited in the magnetotail and inner magnetosphere, producing an enhanced ring current and energising plasma to relativistic levels by as yet unknown excitation mechanisms. By exploiting data from the Advanced Composition Explorer (ACE) spacecraft in conjunction with space- and ground-based measurements of geospace over the last solar cycle, a database of geomagnetic storms has been compiled and analysed. Here we present some statistical findings from a superposed epoch analysis of 143 events identified from the global SYM-H index. We find that the duration of the main phase of storms decreases for increasing storm size, as defined by the maximum negative excursion of SYM-H, contrary to the results of previous studies. We also discuss a comparison of CME and CIR driven storms in terms of storm size, phase duration and evolution, and the associated solar wind-magnetosphere coupling. Initial work has successfully identified characteristic radar backscatter observed by the Super Dual Auoral Radar Network (SuperDARN) and, in particular, the new lower-latitude StormDARN radar network during these storm-time conditions. Here we present early findings of a superposed epoch analysis of auroral imagery from the IMAGE spacecraft and ionospheric convection maps from the SuperDARN radar network. This work further illustrates the storm-time coupling between the solar wind and magnetosphere, and develops the relationship between auroral oval radius and the evolution of the storm-time SYM-H index first reported by Milan et al., (2009). Once completed, this will be the most complete superposed epoch analyses of storms to date, combining multiple datasets

  15. 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…

  16. Contact-free monitoring of circulation and perfusion dynamics based on the analysis of thermal imagery

    PubMed Central

    Pereira, Carina Barbosa; Czaplik, Michael; Blanik, Nikolai; Rossaint, Rolf; Blazek, Vladimir; Leonhardt, Steffen

    2014-01-01

    Acute circulatory disorders are commonly associated with systemic inflammatory response (SIRS) and sepsis. During sepsis, microcirculatory perfusion is compromised leading to tissue hypoperfusion and potentially to multiple organ dysfunction. In the present study, acute lung injury (ALI), one of the major causes leading to SIRS and sepsis, was experimentally induced in six female pigs. To investigate the progress of body temperature distribution, measurements with a long-wave infrared camera were carried out. Temperature centralization was evidenced during ALI owing to impairments of peripheral perfusion. In addition, statistical analysis demonstrated strong correlations between (a) standard deviation of the skin temperature distribution (SD) and shock index (SI) (p<0.0005), (b) SD and mean arterial pressure (MAP) (p<0.0005), (c) ΔT/Δx and SI (p<0.0005), as well as between (d) ΔT/Δx and MAP (p<0.0005). For clarification purposes, ΔT/Δx is a parameter implemented to quantify the spatial temperature gradient. This pioneering study created promising results. It demonstrated the capacity of infrared thermography as well as of the indexes, SD and ΔT/Δx, to detect impairments in both circulation and tissue perfusion. PMID:24761290

  17. 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.

  18. Characterizing Levees using Polarimetric and Interferometric Synthetic Aperture Radar Imagery

    NASA Astrophysics Data System (ADS)

    Dabbiru, L.; Aanstoos, J. V.; Mahrooghy, M.; Gokaraju, B.; Nobrega, R. A.; Younan, N. H.

    2011-12-01

    Monitoring the physical condition of levees is vital in order to protect them from flooding. The dynamics of subsurface water events can cause damage on levee structures which could lead to slough slides, sand boils or through seepage. Synthetic Aperture Radar (SAR) technology, due to its high spatial resolution and soil penetration capability, is a good choice to identify such problem areas so that they can be treated to avoid possible catastrophic failure. The radar polarimetric and interferometric data is capable of identifying variations in soil properties of the areas which might cause levee failure. The study area encompasses portion of levees of the lower Mississippi river in the United States. The methodology of this research is mainly categorized into two streams: 1) polarimetric data analysis and classification, and 2) interferometric analysis. Two sources of SAR imagery are used: a) quad-polarized, L-band data from Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) for polarimetric classification, and b) high resolution dual-polarized Terrasar-X data for interferometric analysis. NASA's UAVSAR imagery acquired between 2009 and 2011 are used for the analysis. The polarimetric classification is performed based on the decomposition parameters: entropy (H), anisotropy (A) and alpha (α) and the results detected slough slides on the levees and potential future slides. In the interferometric approach, the Terrasar-X SAR images acquired at different times in the year 2011 are combined into pairs to exploit the phase difference of the signals. The interferometric information is used to find evidence of potential small-scale deformations which could be pre-cursors to levee failure.

  19. Yield mapping of high-biomass sorghum with aerial imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 high biomass...

  20. 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...

  1. 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.

  2. Development of methodology for the optimization of classification accuracy of Landsat TM/ETM+ imagery for supporting fast flood hydrological analysis

    NASA Astrophysics Data System (ADS)

    Alexakis, D. D.; Hadjimitsis, D. G.; Agapiou, A.; Retalis, A.; Themistocleous, K.; Michaelides, S.; Pashiardis, S.

    2012-04-01

    One of the important tools for detection and quantification of land-cover changes across catchment areas is the classification of multispectral satellite imagery. Land cover changes, may be used to describe dynamics of urban settlements and vegetation patterns as an important indicator of urban ecological environments. Several techniques have been reported to improve classification results in terms of land use discrimination and accuracy of resulting classes. The aim of this study is to improve classification results of multispectral satellite imagery for supporting flood risk assessment analysis in a catchment area in Cyprus (Yialias river). This paper describes the results obtained by integrating remote sensing techniques such as classification analysis and contemporary statistical analysis (maximum entropy) for detecting urbanization activities in a catchment area in Cyprus. The final results were incorporated in an integrated flood risk management model. This study aims to test different material samples in the Yialias region in order to examine: a) their spectral behavior under different precipitation rates and b) to introduce an alternative methodology to optimize the classification results derived from single satellite imagery with the combined use of satellite, spectroradiometric and precipitation data. At the end, different classification algorithms and statistical analysis are used to verify and optimize the final results such as object based classification and maximum entropy. The main aim of the study is the verification of the hypothesis that the multispectral classification accuracy is improved if the land surface humidity is high. This hypothesis was tested against Landsat derived reflectance values and validated with in-situ reflectance observations with the use of high spectral resolution spectroradiometers. This study aspires to highlight the potential of medium resolution satellite images such as those of Landsat TM/ETM+ for Land Use / Land cover

  3. 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

  4. 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

  5. Aerial Photography Summary Record System

    USGS Publications Warehouse

    U.S. Geological Survey

    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.

  6. The application of Skylab imagery to analysis of fault tectonics and earthquake hazards in the Peninsular Ranges, southern California

    NASA Technical Reports Server (NTRS)

    Merifield, P. M. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. Frame 114 of the Salton Sea area was studied in all bands to analyze the appearance of important faults. These faults were also studied in the field as well as from aircraft and in aerial photography. The San Andreas/Banning and the Mission Creek faults can be traced across Coachella Valley even though they are buried by alluvium. The faults form ground water barriers and the near surface ground water on the northeast sides of the faults supports patches of vegetation (mesquite and palms) in an otherwise barren desert. These oases are best seen in band 3 (color IR). Otherwise, faults are best seen in band 4 (aerial color). Of the B and W bands, 5 (red) is best for delineating faults. Bands 1 and 2 are excessively grainy and the resolution is considerably inferior to the other bands.

  7. 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

  8. 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

  9. 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

  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. 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.

  12. 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

  13. Within-field Corn Nitrogen Response Related to Aerial Photograph Color

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Precision agriculture management of nitrogen (N) using aerial imagery of corn [Zea mays L.] canopy color has been a proposed strategy to understand crop N health and base within-season N fertilizer application rates. The objective of this study was to evaluate at field scale the relationship between...

  14. 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.

  15. 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.

  16. Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images

    NASA Astrophysics Data System (ADS)

    Fiorucci, F.; Cardinali, M.; Carlà, R.; Rossi, M.; Mondini, A. C.; Santurri, L.; Ardizzone, F.; Guzzetti, F.

    2011-06-01

    We tested the possibility of using digital, color aerial ortho-photographs and monoscopic, panchromatic satellite images of comparable spatial and radiometric resolution, to map recent landslides in Italy and to update existing measures of landslide mobilization. In a 90-km 2 area in Umbria, central Apennines, rainfall resulted in abundant landslides in the period from September 2004 to June 2005. Analysis of the rainfall record determined the approximate dates of landslide occurrence and revealed that the slope failures occurred in response to moderately wet rainfall periods. The slope failures occurred primarily in cultivated terrain and left subtle morphological and land cover signatures, making the recognition and mapping of the individual landslides problematic. Despite the difficulty with the identification of the landslides without the use of stereoscopic visualization, visual analysis of the aerial and satellite images allowed mapping 457 new landslides, ranging in area 3.0 × 10 1 < AL < 2.5 × 10 4 m 2, for a total landslide area ALT = 6.92 × 10 5 m 2. To identify the landslides, the investigators adopted the interpretation criteria commonly used to identify and map landslides on aerial photography. The result confirms that monoscopic, very high resolution images taken by airborne and satellite sensors can be used to prepare landslide maps even where slope failures are difficult to detect, provided the imagery has sufficient geometric and radiometric resolutions. The different dates of the aerial (March 2005) and the satellite (June-July 2005) images allowed the temporal segmentation of the landslide information, and studying the statistics of landslide area and volume for different periods. Compared to pre-existing information on the abundance and size of the landslides in the area, the inventory obtained by studying the aerial and satellite images proved more complete. The new mapping showed 145% more landslides and 85% more landslide area than a pre

  17. Landscape-scale geospatial research utilizing low elevation aerial photography generated with commercial unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Lipo, C. P.; Lee, C.; Wechsler, S.

    2012-12-01

    With the ability to generate on demand high-resolution imagery across landscapes, unmanned aerial systems (UAS) are increasingly become the tools of choice for geospatial researchers. At CSULB, we have implemented a number of aerial systems in order to conduct archaeological, vegetation and terrain analyses. The platforms include the commercially available X100 by Gatewing, a hobby based aircraft, kites, and tethered blimps. From our experience, each platform has advantages and disadvantages n applicability int eh field and derived imagery. The X100, though comparatively more costly, produces images with excellent coverage of areas of interest and can fly in a wide range of weather conditions. The hobby plane solutions are low-cost and flexible in their configuration but their relative lightweight makes them difficult to fly in windy conditions and the sets of images produced can widely vary. The tethered blimp has a large payload and can fly under many conditions but its ability to systematically cover large areas is very limited. Kites are extremely low-cost but have similar limitations to blimps for area coverage and limited payload capabilities. Overall, we have found the greatest return for our investment from the Gatewing X100, despite its relatively higher cost, due to the quality of the images produced. Developments in autopilots, however, may improve the hobby aircraft solution and allow X100 like products to be produced in the near future. Results of imagery and derived products from these UAS missions will be presented and evaluated. Assessment of the viability of these UAS-products will inform the research community of their applicability to a range of applications, and if viable, could provide a lower cost alternative to other image acquisition methods.

  18. 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.

  19. 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.

  20. 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…

  1. 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

  2. A Morphology Independent Methodology for Quantifying River Planform Change and Characteristics from Remotely Sensed Imagery

    NASA Astrophysics Data System (ADS)

    Rowland, J. C.; Gangodagamage, C.; Shelef, E.; Pope, P. A.; Brumby, S. P.; Wilson, C. J.

    2014-12-01

    The ready availability of remotely sensed imagery offers the potential to examine river dynamics and planform characteristics at global scales. The Landsat archive currently offers the greatest spatial and temporal coverage of the entire globe. However, at 30 meter multispectral resolution detailed and accurate examination of planform changes using Landsat imagery is restricted to intermediate (~ 500 m wide) to very large (~ 1 km wide) rivers or smaller rivers with very high rates of change. Many of these larger river systems exhibit multi-threaded or braided channel patterns that present significant challenges for many of the existing methodologies for quantifying changes developed for single threaded meandering river systems. In order to examine planform changes in river systems across all scales and morphologies we developed a set of algorithms for quantifying river mobility and planform attributes using raster-based river masks extracted from remotely sensed data. Unlike many prior methodologies for measuring river migration and erosion that rely on changes in the position of river channel centerlines, our methods adopt river banks as a frame of reference for quantifying change. The choice of a bank-centric reference frame was motivated by both a primary interest in the spatial and temporal patterns of bank change and the significant challenge of extracting and comparing channel centerlines in multi-threaded systems. Unlike prior vector-based analysis of river channels, our analysis retains a raster-based representation of the river from the original imagery source. At each bank pixel, our algorithms compute linear rates of bank change, local channel width, bank curvature, and bank aspect (used for examination of the influence of thermal processes such as freeze thaw and permafrost influence). The spatially distributed measurements are also aggregated along equally spaced river segments to examine spatial patterns in erosion/accretion rates, and channel widths

  3. 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