WorldWideScience

Sample records for satellite imagery aerial

  1. APPLICABILITY EVALUATION OF OBJECT DETECTION METHOD TO SATELLITE AND AERIAL IMAGERIES

    Directory of Open Access Journals (Sweden)

    K. Kamiya

    2016-06-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Van Eeckhout, E.; Pope, P.; Becker, N.; Wells, B. [Los Alamos National Lab., NM (United States); Lewis, A.; David, N. [Environmental Research Inst. of Michigan, Santa Fe, NM (United States)

    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.

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

    Science.gov (United States)

    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.

  5. A surge of Perseibreen, Svalbard, examined using aerial photography and ASTER high resolution satellite imagery

    OpenAIRE

    Dowdeswell, Julian A.; Benham, Toby J.

    2003-01-01

    The identification of surge activity is important in assessing the duration of the active and quiescent phases of the surge cycle of Svalbard glaciers. Satellite and aerial photographic images are used to identify and describe the form and flow of Perseibreen, a valley glacier of 59 km2 on the east coast of Spitsbergen. Heavy surface crevassing and a steep ice front, indicative of surge activity, were first observed on Perseibreen in April 2002. Examination of high resolution (15 m) Advanced ...

  6. OVERVIEW OF MODERN RESEARCH OF LANDSLIDES ACCORDING TO AERIAL AND SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    K. M. Lyapishev

    2015-01-01

    Full Text Available This article is an overview of researches of landslides using remote sensing methods such as aerial photography, satellite images, radar interferometry, and their combination with the use of GIS technology. Modern methods of investigation of landslides are very diverse. The authors propose different approaches to the identification, classification and monitoring of landslides. Data analysis techniques can help in creating more sophisticated approach to the analysis of landslides.

  7. Aerial Photography and Imagery, Ortho-Corrected, 2004 Satellite Imagery, Published in 2004, 1:12000 (1in=1000ft) scale, Anne Arundel County, OIT GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  8. Automatic urban debris zone extraction from post-hurricane very high-resolution satellite and aerial imagery

    Directory of Open Access Journals (Sweden)

    Shasha Jiang

    2016-05-01

    Full Text Available Automated remote sensing methods have not gained widespread usage for damage assessment after hurricane events, especially for low-rise buildings, such as individual houses and small businesses. Hurricane wind, storm surge with waves, and inland flooding have unique damage signatures, further complicating the development of robust automated assessment methodologies. As a step toward realizing automated damage assessment for multi-hazard hurricane events, this paper presents a mono-temporal image classification methodology that quickly and accurately differentiates urban debris from non-debris areas using post-event images. Three classification approaches are presented: spectral, textural, and combined spectral–textural. The methodology is demonstrated for Gulfport, Mississippi, using IKONOS panchromatic satellite and NOAA aerial colour imagery collected after 2005 Hurricane Katrina. The results show that multivariate texture information significantly improves debris class detection performance by decreasing the confusion between debris and other land cover types, and the extracted debris zone accurately captures debris distribution. Additionally, the extracted debris boundary is approximately equivalent regardless of imagery type, demonstrating the flexibility and robustness of the debris mapping methodology. While the test case presents results for hurricane hazards, the proposed methodology is generally developed and expected to be effective in delineating debris zones for other natural hazards, including tsunamis, tornadoes, and earthquakes.

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

    OpenAIRE

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

    2014-01-01

    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...

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

    Science.gov (United States)

    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 (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, the resulting fine resolution UTC map will be

  11. ERTS-A satellite imagery

    Science.gov (United States)

    Colvocoresses, Alden P.

    1970-01-01

    The first satellite designed to survey the Earth's resources is scheduled to be launched in 1972. This satellite, known as ERTS-A, will telemeter frames of imagery each covering 100-nautical-mile squares of the Earth. Except for the internal anomalies in the sensor system, the imagery, after being properly scaled, rectified, and controlled, may be considered an orthographic view of the Earth and used as a planimetric photomap. The accuracy of this photomap will be limited, principally by the geometric fidelity of the sensor system rather than by external effects, such as relief displacement, which restrict the direct cartographic use of the conventional aerial photograph. ERST-A is not designed as a topographic mapping satellite but does have real potential' for thematic mapping particularly in areas now covered by topographic maps.

  12. Aerial Photography and Imagery, Uncorrected, historic aerial imagery; 1931-1990, Published in 2006, Washoe County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Uncorrected dataset, was produced all or in part from Hardcopy Maps information as of 2006. It is described as 'historic aerial...

  13. Advanced Image Processing of Aerial Imagery

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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...

  15. Normalization of satellite imagery

    Science.gov (United States)

    Kim, Hongsuk H.; Elman, Gregory C.

    1990-01-01

    Sets of Thematic Mapper (TM) imagery taken over the Washington, DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects. Seasonal color changes of the area can be better observed when such normalization is applied to space imagery taken in time series. In normalized imagery, the grey scale depicts variations in surface reflectance and tonal signature of multi-band color imagery can be directly interpreted for quantitative information of the target.

  16. Thematic mapping from satellite imagery

    CERN Document Server

    Denègre, J

    2013-01-01

    Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre

  17. D Surface Generation from Aerial Thermal Imagery

    Science.gov (United States)

    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.

  18. Aerial Photography and Imagery, Oblique, Pictometry Imagery, Published in 2009, North Georgia College and State University.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, was produced all or in part from Orthoimagery information as of 2009. It is described as 'Pictometry Imagery'....

  19. Comparison of satellite imagery and infrared aerial photography as vegetation mapping methods in an arctic study area: Jameson Land, East Greenland

    DEFF Research Database (Denmark)

    Hansen, Birger Ulf; Mosbech, Anders

    1994-01-01

    Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland......Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland...

  20. NAIP Aerial Imagery (Resampled), Salton Sea - 2005 [ds425

    Data.gov (United States)

    California Department of Resources — NAIP 2005 aerial imagery that has been resampled from 1-meter source resolution to approximately 30-meter resolution. This is a mosaic composed from several NAIP...

  1. Aerial Photography and Imagery, Ortho-Corrected, Aerial Photography and Imagery, Ortho-Corrected -, Published in unknown, Not Applicable scale, FREAC.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at Not Applicable scale as of unknown. It is described as 'Aerial Photography and Imagery,...

  2. COMPARATIVE ASSESSMENT OF VERY HIGH RESOLUTION SATELLITE AND AERIAL ORTHOIMAGERY

    Directory of Open Access Journals (Sweden)

    P. Agrafiotis

    2015-03-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  4. Historical aerial imagery reveals rapid frontal retreat following the 1920’s warming in southeast Greenland

    DEFF Research Database (Denmark)

    Bjørk, Anders Anker; Kjær, Kurt H.; Korsgaard, Niels Jákup;

    sea surface and air temperatures. However, little is known about the long term glacier history prior to the satellite era. Here we show a unique record of the frontal history of 132 glaciers in southeast Greenland based on historical aerial and satellite imagery from 1933 to 2010. Our results...

  5. User Validation of VIIRS Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Don Hillger

    2015-12-01

    Full Text Available Visible/Infrared Imaging Radiometer Suite (VIIRS Imagery from the Suomi National Polar-orbiting Partnership (S-NPP satellite is the finest spatial resolution (375 m multi-spectral imagery of any operational meteorological satellite to date. The Imagery environmental data record (EDR has been designated as a Key Performance Parameter (KPP for VIIRS, meaning that its performance is vital to the success of a series of Joint Polar Satellite System (JPSS satellites that will carry this instrument. Because VIIRS covers the high-latitude and Polar Regions especially well via overlapping swaths from adjacent orbits, the Alaska theatre in particular benefits from VIIRS more than lower-latitude regions. While there are no requirements that specifically address the quality of the EDR Imagery aside from the VIIRS SDR performance requirements, the value of VIIRS Imagery to operational users is an important consideration in the Cal/Val process. As such, engaging a wide diversity of users constitutes a vital part of the Imagery validation strategy. The best possible image quality is of utmost importance. This paper summarizes the Imagery Cal/Val Team’s quality assessment in this context. Since users are a vital component to the validation of VIIRS Imagery, specific examples of VIIRS imagery applied to operational needs are presented as an integral part of the post-checkout Imagery validation.

  6. Converting aerial imagery to application maps

    Science.gov (United States)

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

  7. Aerial Photography and Imagery, Ortho-Corrected, 2007 imagery over Eureka Township, Published in 2007, Eureka County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2007. It is described as '2007 imagery...

  8. Satellite Imagery Assisted Road-Based Visual Navigation System

    Science.gov (United States)

    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

  9. Evaluating large scale orthophotos derived from high resolution satellite imagery

    Science.gov (United States)

    Ioannou, Maria Teresa; Georgopoulos, Andreas

    2013-08-01

    For the purposes of a research project, for the compilation of the archaeological and environmental digital map of the island of Antiparos, the production of updated large scale orthophotos was required. Hence suitable stereoscopic high resolution satellite imagery was acquired. Two Geoeye-1 stereopairs were enough to cover this small island of the Cyclades complex in the central Aegean. For the orientation of the two stereopairs numerous ground control points were determined using GPS observations. Some of them would also serve as check points. The images were processed using commercial stereophotogrammetric software suitable to process satellite stereoscopic imagery. The results of the orientations are evaluated and the digital terrain model was produced using automated and manual procedures. The DTM was checked both internally and externally with comparison to other available DTMs. In this paper the procedures for producing the desired orthophotography are critically presented and the final result is compared and evaluated for its accuracy, completeness and efficiency. The final product is also compared against the orthophotography produced by Ktimatologio S.A. using aerial images in 2007. The orthophotography produced has been evaluated metrically using the available check points, while qualitative evaluation has also been performed. The results are presented and a critical approach for the usability of satellite imagery for the production of large scale orthophotos is attempted.

  10. Encoding and analyzing aerial imagery using geospatial semantic graphs

    Energy Technology Data Exchange (ETDEWEB)

    Watson, Jean-Paul; Strip, David R.; McLendon, William Clarence,; 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.

  11. 7 CFR 611.22 - Availability of satellite imagery.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Availability of satellite imagery. 611.22 Section 611... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image...

  12. Commercial satellite imagery comes of age

    Energy Technology Data Exchange (ETDEWEB)

    Jasani, Bhupendra [King' s College, London (United Kingdom). Dept. of War Studies

    2003-05-01

    In the absence of on-site inspections until recently, in the Seventh Quarterly Report to the United Nations Security Council, the Executive Director of the UN Monitoring, Verification and Inspection Commission (UNMOVIC) stated that the imagery acquired over Iraq, which UNMOVIC is receiving through a commercial satellite supplier is continuously, being analysed. Not only this but the report hopes that 'Member States will continue to provide it with imagery from their own assets as such assistance provided to date has proven very valuable' Even after the on-site inspections have begun, satellite imagery over Iraq continues, for example, to be used for inspection planning purposes. This indicates that commercial satellite imagery might finally be used on a routine basis. As the findings by the UNMOVIC are not made public, this paper examines a number of images acquired over Baghdad from different commercial satellite sources and at different times to determine what could be concluded about Iraq's nuclear and chemical weapon activities in the region.

  13. Aerial Photography and Imagery, Ortho-Corrected - Montana 2013 NAIP Orthophotos

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains imagery from the National Agriculture Imagery Program (NAIP). These data are digital aerial photos, at one meter resolution, of the entire...

  14. LA0801 Ortho-rectified Aerial Imagery of Terrebonne and Timbalier Bays Barrier Islands, Louisiana.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — AERO-METRIC, INC. (AME) was provided aerial photographic imagery collected by NOAA along the shoreline of Louisiana. The purpose of the imagery was to provide...

  15. Oblique Aerial Imagery for NMA - Some best Practices

    Science.gov (United States)

    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.

  16. Updating Maps Using High Resolution Satellite Imagery

    Science.gov (United States)

    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.

  17. High resolution channel geometry from repeat aerial imagery

    Science.gov (United States)

    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

  18. 3D SURFACE GENERATION FROM AERIAL THERMAL IMAGERY

    Directory of Open Access Journals (Sweden)

    B. Khodaei

    2015-12-01

    Full Text Available 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.

  19. Application of Unmanned Aerial Systems in Spatial Downscaling of Landsat VIR imageries of Agricultural Fields

    Science.gov (United States)

    Torres, A.; Hassan Esfahani, L.; Ebtehaj, A.; McKee, M.

    2016-12-01

    While coarse space-time resolution of satellite observations in visible to near infrared (VIR) is a serious limiting factor for applications in precision agriculture, high resolution remotes sensing observation by the Unmanned Aerial Systems (UAS) systems are also site-specific and still practically restrictive for widespread applications in precision agriculture. We present a modern spatial downscaling approach that relies on new sparse approximation techniques. The downscaling approach learns from a large set of coincident low- and high-resolution satellite and UAS observations to effectively downscale the satellite imageries in VIR bands. We focus on field experiments using the AggieAirTM platform and Landsat 7 ETM+ and Landsat 8 OLI observations obtained in an intensive field campaign in 2013 over an agriculture field in Scipio, Utah. The results show that the downscaling methods can effectively increase the resolution of Landsat VIR imageries by the order of 2 to 4 from 30 m to 15 and 7.5 m, respectively. Specifically, on average, the downscaling method reduces the root mean squared errors up to 26%, considering bias corrected AggieAir imageries as the reference.

  20. Aerial Photography and Imagery, Oblique, 2008 Aerial Oblique imagery for Iredell County, NC, Published in 2008, 1:2400 (1in=200ft) scale, Iredell County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Other information as of 2008. It is...

  1. Processing Satellite Imagery To Detect Waste Tire Piles

    Science.gov (United States)

    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

  2. Aerial Photography and Imagery, Ortho-Corrected, Pictometry Imagery, Published in 2009, North Georgia College and State University.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2009. It is described as 'Pictometry...

  3. Automatic Sea Bird Detection from High Resolution Aerial Imagery

    Science.gov (United States)

    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.

  4. High-biomass sorghum yield estimate with aerial imagery

    Science.gov (United States)

    Sui, Ruixiu; Hartley, Brandon E.; Gibson, John M.; Yang, Chenghai; Thomasson, J. Alex; Searcy, Stephen W.

    2011-01-01

    To reach the goals laid out by the U.S. Government for displacing fossil fuels with biofuels, high-biomass sorghum is well-suited to achieving this goal because it requires less water per unit dry biomass and can produce very high biomass yields. In order to make biofuels economically competitive with fossil fuels it is essential to maximize production efficiency throughout the system. The goal of this study was to use remote sensing technologies to optimize the yield and harvest logistics of high-biomass sorghum with respect to production costs based on spatial variability within and among fields. Specific objectives were to compare yield to aerial multispectral imagery and develop predictive relationships. A 19.2-ha high-biomass sorghum field was selected as a study site and aerial multispectral images were acquired with a four-camera imaging system on July 17, 2009. Sorghum plant samples were collected at predetermined geographic coordinates to determine biomass yield. Aerial images were processed to find relationships between image reflectance and yield of the biomass sorghum. Results showed that sorghum biomass yield in early August was closely related (R2 = 0.76) to spectral reflectance. However, in the late season the correlations between the biomass yield and spectral reflectance were not as positive as in the early season. The eventual outcome of this work could lead to predicted-yield maps based on remotely sensed images, which could be used in developing field management practices to optimize yield and harvest logistics.

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

    Science.gov (United States)

    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.

  6. Aerial Photography and Imagery, Uncorrected, Oconto County 1975 Aerial Photographs, Published in 1975, 1:9600 (1in=800ft) scale, Bay-Lake Regional Planning Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Uncorrected dataset, published at 1:9600 (1in=800ft) scale, was produced all or in part from Uncorrected Imagery information as...

  7. Aerial Photography and Imagery, Ortho-Corrected, Published in 2009, SWGRC.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2009. Data by this publisher are often...

  8. Aerial Photography and Imagery, Ortho-Corrected, Published in unknown, Park County GIS Department.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of unknown. Data by this publisher are...

  9. Aerial Photography and Imagery, Ortho-Corrected - 2011 Digital Orthophotos - Lee County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — The dataset consists of tiled orthogonal imagery produced from nadir images captured by Pictometry International January 2nd and March 21st, 2011. Automatic aerial...

  10. Aerial Photography and Imagery, Ortho-Corrected, Urban areas, Published in 2009, Boone County Government.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2009. It is described as 'Urban areas'....

  11. Hurricane Gustav Aerial Photography: Rapid ResponseImagery of the Surrounding Regions After Landfall

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the surrounding regionsafter Hurricane Gustav made landfall. The aerial photography missions wereconducted by the NOAA Remote...

  12. Aerial Photography and Imagery, Ortho-Corrected, Published in 2005, Ashland County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2005. Data by this publisher are often...

  13. Aerial Photography and Imagery, Ortho-Corrected, Published in unknown, BRANCH COUNTY.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of unknown. Data by this publisher are...

  14. Aerial Photography and Imagery, Ortho-Corrected - 2011 Digital Orthophotos - Lee County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — The dataset consists of tiled orthogonal imagery produced from nadir images captured by Pictometry International January 2nd and March 21st, 2011. Automatic aerial...

  15. Aerial Photography and Imagery, Ortho-Corrected, Published in Not Provided, Phillips County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset as of Not Provided. Data by this publisher are often provided in State Plane coordinate system; in a...

  16. Aerial Photography and Imagery, Ortho-Corrected, Published in 2007, Towns County E911 Mapping.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2007. Data by this publisher are often...

  17. Hurricane Ike Aerial Photography: Rapid ResponseImagery of the Surrounding Regions After Landfall

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the surrounding regionsafter Hurricane Ike made landfall. The aerial photography missions wereconducted by the NOAA Remote...

  18. Aerial Photography and Imagery, Ortho-Corrected, Urban area resolution, Published in 2006, Mahaska County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2006. It is described as 'Urban area...

  19. LA0801 Ortho-rectified Aerial Imagery of Terrebonne and Timbalier Bays Barrier Islands, Louisiana.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — AERO-METRIC, INC. (AME) was provided aerial photographic imagery along the shoreline of Louisiana under Contract DG133C-06-CO-0055, Task Order T0006. The purpose of...

  20. High Resolution Imagery and Three-line Array Imagery Automatic Registration for China’s TH-1 Satellite Imagery

    OpenAIRE

    2014-01-01

    An automatic image registration method of high resolution (HR) imagery and three-line array imagery for China’s TH-1 mapping satellite is invented. The 2m resolution HR imagery is normalized to 5m resolution three-line array imagery firstly. Then using precise point prediction model (P3M) matching method, thousands of correspondent points can be matched. Based on these matched points, feature points collected on HR imagery can be converted onto three-line array imagery automatically. Conseque...

  1. Aerial Photography and Imagery, Ortho-Corrected, 2004 imagery over Eureka Township and Crescent Valley, unknown resolution, Published in 2004, Eureka County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2004. It is described as '2004 imagery...

  2. Aerial Photography and Imagery, Oblique, Pictometry Oblique Imagery for the 10-County Atlanta Regional Commission Region, Published in 2007, Atlanta Regional Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, was produced all or in part from Other information as of 2007. It is described as 'Pictometry Oblique Imagery...

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

    Science.gov (United States)

    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...

  4. Aerial Photography and Imagery, Ortho-Corrected, Historic 1958 black and white aerial photography for Wicomico County, Maryland. Imagery was scanned from historic hard copy images and georeferenced to current imagery. This data is available via map service., Published in 2010, 1:12000 (1in=1000ft) scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC Regional | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2010. Historic 1958 black and white aerial photography for Wicomico County, Maryland. Imagery...

  5. Multipath sparse coding for scene classification in very high resolution satellite imagery

    Science.gov (United States)

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

    2015-10-01

    With the rapid development of various satellite sensors, automatic and advanced scene classification technique is urgently needed to process a huge amount of satellite image data. Recently, a few of research works start to implant the sparse coding for feature learning in aerial scene classification. However, these previous research works use the single-layer sparse coding in their system and their performances are highly related with multiple low-level features, such as scale-invariant feature transform (SIFT) and saliency. Motivated by the importance of feature learning through multiple layers, we propose a new unsupervised feature learning approach for scene classification on very high resolution satellite imagery. The proposed unsupervised feature learning utilizes multipath sparse coding architecture in order to capture multiple aspects of discriminative structures within complex satellite scene images. In addition, the dense low-level features are extracted from the raw satellite data by using different image patches with varying size at different layers, and this approach is not limited to a particularly designed feature descriptors compared with the other related works. The proposed technique has been evaluated on two challenging high-resolution datasets, including the UC Merced dataset containing 21 different aerial scene categories with a 1 foot resolution and the Singapore dataset containing 5 land-use categories with a 0.5m spatial resolution. Experimental results show that it outperforms the state-of-the-art that uses the single-layer sparse coding. The major contributions of this proposed technique include (1) a new unsupervised feature learning approach to generate feature representation for very high-resolution satellite imagery, (2) the first multipath sparse coding that is used for scene classification in very high-resolution satellite imagery, (3) a simple low-level feature descriptor instead of many particularly designed low-level descriptor

  6. Aerial Photography and Imagery, Oblique, This was done along the entire Southshore of Lake Superior., Published in 2003, Bayfield County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, was produced all or in part from Uncorrected Imagery information as of 2003. It is described as 'This was done...

  7. LA0801 Ortho-rectified Aerial Imagery of Terrebonne and Timbalier Bays Barrier Islands, Louisiana (NODC Accession 0075828)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — AERO-METRIC, INC. (AME) was provided aerial photographic imagery collected by NOAA along the shoreline of Louisiana. The purpose of the imagery was to provide...

  8. Aerial Photography and Imagery, Ortho-Corrected, Digital Aerial Photography 1970. Limited georeferencing. See metadata for additional information., Published in 1970, 1:4800 (1in=400ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 1970. Digital Aerial Photography 1970. Limited georeferencing. See metadata for additional...

  9. The pan-sharpening of satellite and UAV imagery for agricultural applications

    Science.gov (United States)

    Jenerowicz, Agnieszka; Woroszkiewicz, Malgorzata

    2016-10-01

    Remote sensing techniques are widely used in many different areas of interest, i.e. urban studies, environmental studies, agriculture, etc., due to fact that they provide rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. Agricultural management is one of the most common application of remote sensing methods nowadays. Monitoring of agricultural sites and creating information regarding spatial distribution and characteristics of crops are important tasks to provide data for precision agriculture, crop management and registries of agricultural lands. For monitoring of cultivated areas many different types of remote sensing data can be used- most popular are multispectral satellites imagery. Such data allow for generating land use and land cover maps, based on various methods of image processing and remote sensing methods. This paper presents fusion of satellite and unnamed aerial vehicle (UAV) imagery for agricultural applications, especially for distinguishing crop types. Authors in their article presented chosen data fusion methods for satellite images and data obtained from low altitudes. Moreover the authors described pan- sharpening approaches and applied chosen pan- sharpening methods for multiresolution image fusion of satellite and UAV imagery. For such purpose, satellite images from Landsat- 8 OLI sensor and data collected within various UAV flights (with mounted RGB camera) were used. In this article, the authors not only had shown the potential of fusion of satellite and UAV images, but also presented the application of pan- sharpening in crop identification and management.

  10. Aerial Photography and Imagery, Ortho-Corrected, This data set contains imagery from the National Agriculture Imagery Program (NAIP). NAIP acquires digital ortho imagery during the agricultural growing seasons in the continental U.S. NAIP imagery may contain as much as 10% cloud cover per tile. This fil, Published in 2005, 1:63360 (1in=1mile) scale, University of Georgia.

    Data.gov (United States)

    NSGIC Education | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2005. This data set contains imagery from the National Agriculture Imagery Program (NAIP). NAIP...

  11. Using satellite imagery for crime mapping in South Africa.

    CSIR Research Space (South Africa)

    Schmitz, Peter MU

    2002-12-01

    Full Text Available . Increasingly, technologies such as digital orthophotographs, high-resolution satellite imagery and the global positioning system (GPS) are being used for these areas to provide base mapping and application data for geographical information systems (GIS...

  12. Potentials of satellite imagery for monitoring arctic goose productivity

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This paper reports upon the exciting possibility that satellite imagery may now provide feasible means for grossly monitoring arctic habitat conditions in a timely...

  13. The Potential Uses of Commercial Satellite Imagery in the Middle East

    Energy Technology Data Exchange (ETDEWEB)

    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.

  14. Accurate Estimation of Orientation Parameters of Uav Images Through Image Registration with Aerial Oblique Imagery

    Science.gov (United States)

    Onyango, F. A.; Nex, F.; Peter, M. S.; Jende, P.

    2017-05-01

    Unmanned Aerial Vehicles (UAVs) have gained popularity in acquiring geotagged, low cost and high resolution images. However, the images acquired by UAV-borne cameras often have poor georeferencing information, because of the low quality on-board Global Navigation Satellite System (GNSS) receiver. In addition, lightweight UAVs have a limited payload capacity to host a high quality on-board Inertial Measurement Unit (IMU). Thus, orientation parameters of images acquired by UAV-borne cameras may not be very accurate. Poorly georeferenced UAV images can be correctly oriented using accurately oriented airborne images capturing a similar scene by finding correspondences between the images. This is not a trivial task considering the image pairs have huge variations in scale, perspective and illumination conditions. This paper presents a procedure to successfully register UAV and aerial oblique imagery. The proposed procedure implements the use of the AKAZE interest operator for feature extraction in both images. Brute force is implemented to find putative correspondences and later on Lowe's ratio test (Lowe, 2004) is used to discard a significant number of wrong matches. In order to filter out the remaining mismatches, the putative correspondences are used in the computation of multiple homographies, which aid in the reduction of outliers significantly. In order to increase the number and improve the quality of correspondences, the impact of pre-processing the images using the Wallis filter (Wallis, 1974) is investigated. This paper presents the test results of different scenarios and the respective accuracies compared to a manual registration of the finally computed fundamental and essential matrices that encode the orientation parameters of the UAV images with respect to the aerial images.

  15. ACCURATE ESTIMATION OF ORIENTATION PARAMETERS OF UAV IMAGES THROUGH IMAGE REGISTRATION WITH AERIAL OBLIQUE IMAGERY

    Directory of Open Access Journals (Sweden)

    F. A. Onyango

    2017-05-01

    Full Text Available Unmanned Aerial Vehicles (UAVs have gained popularity in acquiring geotagged, low cost and high resolution images. However, the images acquired by UAV-borne cameras often have poor georeferencing information, because of the low quality on-board Global Navigation Satellite System (GNSS receiver. In addition, lightweight UAVs have a limited payload capacity to host a high quality on-board Inertial Measurement Unit (IMU. Thus, orientation parameters of images acquired by UAV-borne cameras may not be very accurate. Poorly georeferenced UAV images can be correctly oriented using accurately oriented airborne images capturing a similar scene by finding correspondences between the images. This is not a trivial task considering the image pairs have huge variations in scale, perspective and illumination conditions. This paper presents a procedure to successfully register UAV and aerial oblique imagery. The proposed procedure implements the use of the AKAZE interest operator for feature extraction in both images. Brute force is implemented to find putative correspondences and later on Lowe’s ratio test (Lowe, 2004 is used to discard a significant number of wrong matches. In order to filter out the remaining mismatches, the putative correspondences are used in the computation of multiple homographies, which aid in the reduction of outliers significantly. In order to increase the number and improve the quality of correspondences, the impact of pre-processing the images using the Wallis filter (Wallis, 1974 is investigated. This paper presents the test results of different scenarios and the respective accuracies compared to a manual registration of the finally computed fundamental and essential matrices that encode the orientation parameters of the UAV images with respect to the aerial images.

  16. Historical aerial imagery reveals rapid frontal retreat following the 1920's warming in southeast Greenland

    Science.gov (United States)

    Bjork, A. A.; Kjaer, K. H.; Korsgaard, N. J.; Khan, S. A.; Kjeldsen, K. K.; Andresen, C. S.

    2011-12-01

    The Greenland ice sheet (GIS) is undergoing massive changes in its frontal positions, velocity structure, and overall mass balance. Since 2000, marine and terrestrial terminating glaciers in southeast Greenland have experienced dramatic frontal retreat and dynamic thinning in response to increased sea surface and air temperatures. However, little is known about the long term glacier history prior to the satellite era. Here we show a unique record of the frontal history of 132 glaciers in southeast Greenland based on historical aerial and satellite imagery from 1933 to 2010. Our results demonstrate decadal sensitivity to temperature changes with rapid retreat following the early century warming (1919-1932) and glacial advance during a minor, but profound mid century cooling (1955-1972) succeeded by the present warming again leading to massive retreat. One significant finding lies in the similarity of the retreat following the early century warming and the latest decade, with a majority of the 132 glaciers exhibiting larger retreat rates in the early period. Furthermore, during the mid century cooling glaciers in southeast Greenland showed a surprisingly rapid response to the cooling, indicating that stabilization and subsequent advance can occur with a short cooling period. Marine terminating glaciers originating from the GIS experienced the largest frontal fluctuations often out of sync with local glaciers and ice caps indicating a larger coherence with ocean temperatures, whereas local glaciers and ice caps and GIS terrestrial terminating glaciers shows frontal fluctuations closely related to the air temperature.

  17. Andean terraced hills (a use of satellite imagery)

    CERN Document Server

    Sparavigna, Amelia Carolina

    2010-01-01

    The aim of this paper is in stimulating the use of satellite imagery, in particular the free service of Google Maps, to investigate the distribution of the agricultural technique of terraced hills in Andean countries, near Titicaca Lake. In fact, satellite maps can give a clear view of the overall surface modified by human work, being then a precious help for on-site archaeological researches and for historical analysis. Satellite imagery is also able to give the distribution of burial and worship places. The paper discusses some examples near the Titicaca Lake.

  18. Highway Traffic Incident Detection using High-Resolution Aerial Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Seyed M.M. Kahaki

    2011-01-01

    -fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} ° and the performance for learning system in order to vehicle detection is 86%. This performance achived in testing algorithm on 45 highway aerial images. Conclusion: In order to consider with the high complexity of this kind of imagery, we integrate knowledge about roadways using formulated scale-dependent models. The intensity images are used for the extraction of road from satellite images. Threshold techniques, neural network and Radon transform are used for the road extraction, vehicle detection and incident detection. Results indicated that in most aerial images the incident can be detect by applying the angle algorithm.

  19. Harnessing Satellite Imageries in Feature Extraction Using Google Earth Pro

    Science.gov (United States)

    Fernandez, Sim Joseph; Milano, Alan

    2016-07-01

    Climate change has been a long-time concern worldwide. Impending flooding, for one, is among its unwanted consequences. The Phil-LiDAR 1 project of the Department of Science and Technology (DOST), Republic of the Philippines, has developed an early warning system in regards to flood hazards. The project utilizes the use of remote sensing technologies in determining the lives in probable dire danger by mapping and attributing building features using LiDAR dataset and satellite imageries. A free mapping software named Google Earth Pro (GEP) is used to load these satellite imageries as base maps. Geotagging of building features has been done so far with the use of handheld Global Positioning System (GPS). Alternatively, mapping and attribution of building features using GEP saves a substantial amount of resources such as manpower, time and budget. Accuracy-wise, geotagging by GEP is dependent on either the satellite imageries or orthophotograph images of half-meter resolution obtained during LiDAR acquisition and not on the GPS of three-meter accuracy. The attributed building features are overlain to the flood hazard map of Phil-LiDAR 1 in order to determine the exposed population. The building features as obtained from satellite imageries may not only be used in flood exposure assessment but may also be used in assessing other hazards and a number of other uses. Several other features may also be extracted from the satellite imageries.

  20. Photogrammetric Processing Using ZY-3 Satellite Imagery

    Science.gov (United States)

    Kornus, W.; Magariños, A.; Pla, M.; Soler, E.; Perez, F.

    2015-03-01

    This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are

  1. Aerial Photography and Imagery, Ortho-Corrected, 2009 Aerial Orthophotography for Iredell County, NC, Published in 2005, 1:2400 (1in=200ft) scale, Iredell County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  2. Aerial Photography and Imagery, Ortho-Corrected, Aerial Photography of Lowndes County, GA, Published in 2007, 1:1200 (1in=100ft) scale, Southern Georgia Regional Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  3. Aerial Photography and Imagery, Ortho-Corrected, Olympus Aerial Survey bound, Published in 2009, 1:24000 (1in=2000ft) scale, Washington County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Other information as of 2009....

  4. Aerial Photography and Imagery, Ortho-Corrected - VOLUSIA 2006 Orthophotography

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — 2006, 6 inch Pixel Color Orthophotography - - Panchromatic, red, green, blue and near infrared imagery was acquired using the Leica ADS40 multi-spectral scanner (see...

  5. Aerial Photography and Imagery, Ortho-Corrected - VOLUSIA 2006 Orthophotography

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — 2006, 6 inch Pixel Color Orthophotography - - Panchromatic, red, green, blue and near infrared imagery was acquired using the Leica ADS40 multi-spectral scanner (see...

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

    Science.gov (United States)

    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...

  7. Developing a framework for monitoring coastal habitats using aerial imagery and object-based image analysis

    DEFF Research Database (Denmark)

    Juel, Anders

    of decreased habitat dynamics exists. A valuable source of land cover changes are historical aerial imagery of which Denmark has unique datasets.This poster presents an object-based image analysis approach for mapping and monitoring af coastal habitat stucture, which integrates the high spectral resolution...

  8. Quantifying the Effect of Aerial Imagery Resolution in Automated Hydromorphological River Characterisation

    Directory of Open Access Journals (Sweden)

    Monica Rivas Casado

    2016-08-01

    Full Text Available Existing regulatory frameworks aiming to improve the quality of rivers place hydromorphology as a key factor in the assessment of hydrology, morphology and river continuity. The majority of available methods for hydromorphological characterisation rely on the identification of homogeneous areas (i.e., features of flow, vegetation and substrate. For that purpose, aerial imagery is used to identify existing features through either visual observation or automated classification techniques. There is evidence to believe that the success in feature identification relies on the resolution of the imagery used. However, little effort has yet been made to quantify the uncertainty in feature identification associated with the resolution of the aerial imagery. This paper contributes to address this gap in knowledge by contrasting results in automated hydromorphological feature identification from unmanned aerial vehicles (UAV aerial imagery captured at three resolutions (2.5 cm, 5 cm and 10 cm along a 1.4 km river reach. The results show that resolution plays a key role in the accuracy and variety of features identified, with larger identification errors observed for riffles and side bars. This in turn has an impact on the ecological characterisation of the river reach. The research shows that UAV technology could be essential for unbiased hydromorphological assessment.

  9. Incremental road discovery from aerial imagery using curvilinear spanning tree (CST) search

    Science.gov (United States)

    Wang, Guozhi; Huang, Yuchun; Xie, Rongchang; Zhang, Hongchang

    2016-10-01

    Robust detection of road network in aerial imagery is a challenging task since roads have different pavement texture, road-side surroundings, as well as grades. Roads of different grade have different curvilinear saliency in the aerial imagery. This paper is motivated to incrementally extract roads and construct the topology of the road network of aerial imagery from the higher-grade-first perspective. Inspired by the spanning tree technique, the proposed method starts from the robust extraction of the most salient road segment(s) of the road network, and incrementally connects segments of less saliency of curvilinear structure until all road segments in the network are extracted. The proposed algorithm includes: curvilinear path-based road morphological enhancement, extraction of road segments, and spanning tree search for the incremental road discovery. It is tested on a diverse set of aerial imagery acquired in the city and inter-city areas. Experimental results show that the proposed curvilinear spanning tree (CST) can detect roads efficiently and construct the topology of the road network effectively. It is promising for the change detection of the road network.

  10. Multi-decadal record of ice dynamics on Daugaard Jensen Gletscher, East Greenland, from satellite imagery and terrestrial measurements

    DEFF Research Database (Denmark)

    Stearns, L.A.; Hamilton, G.S.; Reeh, Niels

    2005-01-01

    The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained in approxima......The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained...... vs snow accumulation in the interior catchment show that Daugaard Jensen Gletscher has a small negative mass balance. This result is consistent with other mass-balance estimates for the inland region of the glacier....

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

    Science.gov (United States)

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

    2015-11-04

    European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management.

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

    Directory of Open Access Journals (Sweden)

    Monica Rivas Casado

    2015-11-01

    Full Text Available 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.

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

    Science.gov (United States)

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

    2015-08-12

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

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

    Directory of Open Access Journals (Sweden)

    Irene Borra-Serrano

    2015-08-01

    Full Text Available 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.

  15. Polar bears from space: assessing satellite imagery as a tool to track Arctic wildlife.

    Directory of Open Access Journals (Sweden)

    Seth Stapleton

    Full Text Available 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.

  16. Aerial Photography and Imagery, Ortho-Corrected, Hi-Resolution Ortho Imagery, Published in 2008, 1:1200 (1in=100ft) scale, Department of Information Technology.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  17. Aerial Photography and Imagery, Ortho-Corrected, Mecklenburg County 2007 Digital Ortho Imagery, Published in 2007, 1:2400 (1in=200ft) scale, Mecklenburg County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  18. Aerial Photography and Imagery, Ortho-Corrected, County wide imagery, Published in 2007, 1:1200 (1in=100ft) scale, Norton County Appraisal Office.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

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

    Science.gov (United States)

    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

  20. On RPC Model of Satellite Imagery

    Institute of Scientific and Technical Information of China (English)

    ZHANG Guo; YUAN Xiuxiao

    2006-01-01

    The RPC model has recently raised considerable interest in the photogrammetry and remote sensing community. The RPC is a generalized sensor model that is capable of achieving high approximation accuracy. Unfortunately, the computation of the parameters of RPC model is subject to the initial of the parameter in all available literature. An algorithm for computation of parameters of RPC model without initial value is presented and tested on SPOT-5, CBERS-2, ERS-1 imageries. RPC model is suitable for both push-broom and SAR imagery.

  1. AUTOMATIC EXTRACTION OF BUILDING OUTLINE FROM HIGH RESOLUTION AERIAL IMAGERY

    Directory of Open Access Journals (Sweden)

    Y. Wang

    2016-06-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  4. LOW-LEVEL TIE FEATURE EXTRACTION OF MOBILE MAPPING DATA (MLS/IMAGES AND AERIAL IMAGERY

    Directory of Open Access Journals (Sweden)

    P. Jende

    2016-03-01

    Full Text Available 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

  5. DECISION LEVEL FUSION OF LIDAR DATA AND AERIAL COLOR IMAGERY BASED ON BAYESIAN THEORY FOR URBAN AREA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    H. Rastiveis

    2015-12-01

    Full Text Available 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.

  6. A procedure for semi-Automatic Orthophoto Generation from High Resolution Satellite Imagery

    Science.gov (United States)

    Alrajhi, M. N.; Jacobsen, K.; Heipke, C.

    2013-10-01

    The General Directorate of Surveying and Mapping (GDSM), under the Ministry of Municipal and Rural Affairs (MOMRA) is responsible for the production and dissemination of accurate geospatial data for all the metropolitan cities, towns and rural settlements in the Kingdom of Saudi Arabia. GDSM maintains digital geospatial databases that support the production of conventional line and orthophoto maps at scales ranging from 1:1,000 to 1:20,000. The current procedures for the acquisition of new aerial imagery cover a long time cycle of three or more years. Consequently, the availability of recently acquired High Resolution Satellite Imagery (HRSI) presents an attractive alternative image data source for rapid response to updated geospatial data needs. The direct sensor orientation of HRSI is not accurate enough requiring ground control points (GCP). A field survey of GCP is time consuming and costly. Seeking an alternative approach, a research study has recently been completed to use existing image and data base information instead of traditional ground control for the orthoprojection of HRSI in order to automate and speed up as much as possible the whole process. Based on a series of practical experiments, the ability for automated matching of aerial and satellite images by using the Speeded-Up Robust Features (SURF) algorithm is demonstrated to be useful for this task. Practical results from matching with SURF validate the ability for multi-scale, multi-sensor and multi-season matching of aerial and satellite images. The matched tie points are then used to transform the satellite orthophoto to the aerial orthophoto through a 2D affine coordinate transformation. GeoEye-1 and IKONOS imagery, when geo-referenced through SURF-based matching and transformed meet the MOMRA Map Accuracy Standards for 1:10,000 and 1:20,000 scale. However, a similarly processed SPOT-5 image does not meet these standards. This research has led to the development of a simple and efficient tool

  7. Mapping cultivable land from satellite imagery with clustering algorithms

    Science.gov (United States)

    Arango, R. B.; Campos, A. M.; Combarro, E. F.; Canas, E. R.; Díaz, I.

    2016-07-01

    Open data satellite imagery provides valuable data for the planning and decision-making processes related with environmental domains. Specifically, agriculture uses remote sensing in a wide range of services, ranging from monitoring the health of the crops to forecasting the spread of crop diseases. In particular, this paper focuses on a methodology for the automatic delimitation of cultivable land by means of machine learning algorithms and satellite data. The method uses a partition clustering algorithm called Partitioning Around Medoids and considers the quality of the clusters obtained for each satellite band in order to evaluate which one better identifies cultivable land. The proposed method was tested with vineyards using as input the spectral and thermal bands of the Landsat 8 satellite. The experimental results show the great potential of this method for cultivable land monitoring from remote-sensed multispectral imagery.

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

    Science.gov (United States)

    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

  9. Get Close to Glaciers with Satellite Imagery.

    Science.gov (United States)

    Hall, Dorothy K.

    1986-01-01

    Discusses the use of remote sensing from satellites to monitor glaciers. Discusses efforts to use remote sensing satellites of the Landsat series for examining the global distribution, mass, balance, movements, and dynamics of the world's glaciers. Includes several Landsat images of various glaciers. (TW)

  10. Aerial Photography and Imagery, Ortho-Corrected, 1997 Ortho Imagery collected by Abrams Aerial Survey, Published in 1997, 1:2400 (1in=200ft) scale, CITY OF PORTAGE.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  11. Aerial Photography and Imagery, Ortho-Corrected, MFRDC has aerial imagery for Dooly, Crisp, Macon, Taylor, Schley, Marion and Webster counties., Published in 2006, 1:1200 (1in=100ft) scale, Middle Flint RDC.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Other information as of 2006....

  12. Parameterization of Vegetation Aerodynamic Roughness of Natural Regions Satellite Imagery

    Science.gov (United States)

    Jasinski, Michael F.; Crago, Richard; Stewart, Pamela

    1998-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. The parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  13. Identifying hydro resources with enhanced satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Cambridge, M.; Moore, J.M.; Canas, A.

    1986-10-01

    Landsat multi-spectral scanner (MSS) imagery in photographic form was used, in conjunction with available topographic and geologic maps, during the preliminary planning studies of potential dam sites in the Ulu Jelai river basin, Peninsular Malaysia. The Imperial College (London, UK) prototype analog image processing system was used to provide colour composite and edge-enhanced images for drainage, geological fold, fault and joint trace (tectonic fabric) mapping and to provide information on rock type distribution at scales between 1:250,000 and 1:50,000. Remotely sensed space imagery, enhanced by analog (optical) techniques, is a cheap, convenient and useful supplement to existing geologic and topographic maps for preliminary regional site assessment in tropical terrain.

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

    Science.gov (United States)

    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

  15. Geomorphic habitat units derived from 2011 aerial imagery and elevation data for the Elwha River estuary, Washington

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 03 September 2011 0.3 meter resolution Microsoft/Digital Globe aerial imagery;...

  16. Aerial Photography and Imagery, Ortho-Corrected, Published in 2005, 1:4800 (1in=400ft) scale, Sauk County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  17. Aerial Photography and Imagery, Ortho-Corrected, Published in 2008, 1:2400 (1in=200ft) scale, Sampson County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  18. Aerial Photography and Imagery, Ortho-Corrected, Published in 2008, 1:1200 (1in=100ft) scale, Warren County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  19. Aerial Photography and Imagery, Ortho-Corrected, Scheduled for new flights Spring 2010, Published in 2010, Washington County, Iowa GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 2010. It is described as 'Scheduled...

  20. Aerial Photography and Imagery, Oblique, Pictometry done Spring 2009, not rectified into GIS yet, Published in 2009, Jones County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset as of 2009. It is described as 'Pictometry done Spring 2009, not rectified into GIS yet'. Data by this publisher...

  1. Aerial Photography and Imagery, Oblique, Published in 2009, 1:4800 (1in=400ft) scale, Cerro Gordo County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:4800 (1in=400ft) scale as of 2009. Data by this publisher are often provided in State Plane...

  2. Aerial Photography and Imagery, Ortho-Corrected, Published in 2008, 1:1200 (1in=100ft) scale, Greenwood County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  3. Aerial Photography and Imagery, Oblique, Published in 2010, 1:1200 (1in=100ft) scale, Brown County, WI.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of 2010....

  4. Open-Source Processing and Analysis of Aerial Imagery Acquired with a Low-Cost Unmanned Aerial System to Support Invasive Plant Management

    Directory of Open Access Journals (Sweden)

    Jan R. K. Lehmann

    2017-07-01

    Full Text Available Remote sensing by Unmanned Aerial Systems (UAS is a dynamic evolving technology. UAS are particularly useful in environmental monitoring and management because they have the capability to provide data at high temporal and spatial resolutions. Moreover, data acquisition costs are lower than those of conventional methods such as extensive ground sampling, manned airplanes, or satellites. Small fixed-wing UAS in particular offer further potential benefits as they extend the operational coverage of the area under study at lower operator risks and accelerate data deployment times. Taking these aspects into account, UAS might be an effective tool to support management of invasive plant based on early detection and regular monitoring. A straightforward UAS approach to map invasive plant species is presented in this study with the intention of providing ready-to-use field maps essential for action-oriented management. Our UAS utilizes low-cost sensors, free-of-charge software for mission planning and an affordable, commercial aerial platform to reduce operational costs, reducing expenses with personnel while increasing overall efficiency. We illustrate our approach using a real example of invasion by Acacia mangium in a Brazilian Savanna ecosystem. A. mangium was correctly identified with an overall accuracy of 82.7% from the analysis of imagery. This approach provides land management authorities and practitioners with new prospects for environmental restoration in areas where invasive plant species are present.

  5. Recommended satellite imagery capabilities for disaster management

    Science.gov (United States)

    Richards, P. B.; Robinove, C. J.; Wiesnet, D. R.; Salomonson, V. V.; Maxwell, M. S.

    1982-01-01

    This study explores the role that satellite imaging systems might play in obtaining information needed in the management of natural and manmade disasters. Information requirements which might conceivably be met by satellite were identified for over twenty disasters. These requirements covered pre-disaster mitigation and preparedness activities, disaster response activities, and post-disaster recovery activities. The essential imaging satellite characteristics needed to meet most of the information requirements are 30 meter (or finer) spatial resolution, frequency of observations of one week or less, data delivery times of one day or less, and stereo, synoptic all-weather coverage of large areas in the visible, near infrared, thermal infrared and microwave bands. Of the current and planned satellite systems investigated for possible application to disaster management, Landsat-D and SPOT appear to have the greatest potential during disaster mitigation and preparedness activities, but all satellites studied have serious deficiencies during response and recovery activities. Several strawman concepts are presented for a satellite system optimized to support all disaster management activities.

  6. Pseudo natural colour aerial imagery for urban and suburban mapping

    DEFF Research Database (Denmark)

    Knudsen, Thomas

    2005-01-01

    Due to their near-infrared data channel, digital airborne four-channel imagers provide a potentially good discrimination between vegetation and human-made materials, which is very useful in automated mapping. Due to their red, green and blue data channels, they also provide natural colour images......, which are very useful in traditional (manual) mapping. In this paper, an algorithm is described which provides an approximation to the spectral capabilities of the four-channel imagers by using a colour-infrared aerial photo as input. The algorithm is tailored to urban/suburban surroundings, where...

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

    Science.gov (United States)

    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.

  8. An Automated Approach to Extracting River Bank Locations from Aerial Imagery Using Image Texture

    Science.gov (United States)

    2015-11-04

    12·98) (e) FORM CANCELS AND SUPERSEOES AU. PREVIOUS VERSIONS RIVER RESEARCH AND APPLICATIONS River Res. Applic. (2013) Published online in Wiley ... Online Library (wileyonlinelibrary.com) DOI: 10.1002/rra.2701AN AUTOMATED APPROACH TO EXTRACTING RIVER BANK LOCATIONS FROM AERIAL IMAGERY USING IMAGE...Computer Science. Vol. 2. Pratt W. 1991. Digital Image Processing. John Wiley and Sons: New York. Sera J. 1983. Image Analysis and Mathematical Morphology

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

    Science.gov (United States)

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

    2015-04-01

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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...

  12. Pseudo natural colour aerial imagery for urban and suburban mapping

    DEFF Research Database (Denmark)

    Knudsen, Thomas

    2005-01-01

    Due to their near-infrared data channel, digital airborne four-channel imagers provide a potentially good discrimination between vegetation and human-made materials, which is very useful in automated mapping. Due to their red, green and blue data channels, they also provide natural colour images......, which are very useful in traditional (manual) mapping. In this paper, an algorithm is described which provides an approximation to the spectral capabilities of the four-channel imagers by using a colour-infrared aerial photo as input. The algorithm is tailored to urban/suburban surroundings, where...... the quality of the generated (pseudo) natural colour images are fully acceptable for manual mapping. This brings the combined availability of near-infrared and (pseudo) natural colours within reach for mapping projects based on traditional photogrammetry, which is valuable since traditional analytical cameras...

  13. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Leon County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  14. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Taylor County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  15. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Palm Beach County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  16. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Madison County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  17. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Indian River County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  18. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Volusia County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  19. Aerial Photography and Imagery, Ortho-Corrected - FL Bay Ortho Imagery Project Spring 2013

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This file references a single orthogonal imagery tile produced from nadir images captured by Pictometry International during the period of December 30th, 2012 and...

  20. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Okeechobee County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  1. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Walton County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  2. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Hillsborough County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  3. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Sumter County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  4. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Duval County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  5. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Hernando County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  6. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Baker County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  7. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Hernando County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  8. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Pasco County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  9. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Miami-Dade County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  10. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Washington County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  11. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Glades County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  12. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Martin County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  13. Aerial Photography and Imagery, Ortho-Corrected - FL Bay Ortho Imagery Project Spring 2013

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This file references a single orthogonal imagery tile produced from nadir images captured by Pictometry International during the period of December 30th, 2012 and...

  14. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Brevard County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  15. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Bradford County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

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

    Science.gov (United States)

    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 (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.

  17. Vehicle detection from very-high-resolution (VHR) aerial imagery using attribute belief propagation (ABP)

    Science.gov (United States)

    Wang, Yanli; Li, Ying; Zhang, Li; Huang, Yuchun

    2016-10-01

    With the popularity of very-high-resolution (VHR) aerial imagery, the shape, color, and context attribute of vehicles are better characterized. Due to the various road surroundings and imaging conditions, vehicle attributes could be adversely affected so that vehicle is mistakenly detected or missed. This paper is motivated to robustly extract the rich attribute feature for detecting the vehicles of VHR imagery under different scenarios. Based on the hierarchical component tree of vehicle context, attribute belief propagation (ABP) is proposed to detect salient vehicles from the statistical perspective. With the Max-tree data structure, the multi-level component tree around the road network is efficiently created. The spatial relationship between vehicle and its belonging context is established with the belief definition of vehicle attribute. To effectively correct single-level belief error, the inter-level belief linkages enforce consistency of belief assignment between corresponding components at different levels. ABP starts from an initial set of vehicle belief calculated by vehicle attribute, and then iterates through each component by applying inter-level belief passing until convergence. The optimal value of vehicle belief of each component is obtained via minimizing its belief function iteratively. The proposed algorithm is tested on a diverse set of VHR imagery acquired in the city and inter-city areas of the West and South China. Experimental results show that the proposed algorithm can detect vehicle efficiently and suppress the erroneous effectively. The proposed ABP framework is promising to robustly classify the vehicles from VHR Aerial imagery.

  18. Aerial Photography and Imagery, Ortho-Corrected, 4 inch aerial photography (color, infrared, and color oblique) in urban areas, 1 foot in national forest, Published in 2006, 1:600 (1in=50ft) scale, Los Angeles County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2006. 4 inch aerial photography (color, infrared, and color oblique) in urban areas, 1 foot in...

  19. Using high-resolution satellite imagery to assess populations of animals in the Antarctic

    Science.gov (United States)

    LaRue, Michelle Ann

    The Southern Ocean is one of the most rapidly-changing ecosystems on the planet due to the effects of climate change and commercial fishing for ecologically-important krill and fish. It is imperative that populations of indicator species, such as penguins and seals, be monitored at regional- to global scales to decouple the effects of climate and anthropogenic changes for appropriate ecosystem-based management of the Southern Ocean. Remotely monitoring populations through high-resolution satellite imagery is currently the only feasible way to gain information about population trends of penguins and seals in Antarctica. In my first chapter, I review the literature where high-resolution satellite imagery has been used to assess populations of animals in polar regions. Building on this literature, my second chapter focuses on estimating changes in abundance in the Weddell seal population in Erebus Bay. I found a strong correlation between ground and satellite counts, and this finding provides an alternate method for assessing populations of Weddell seals in areas where less is known about population status. My third chapter explores how size of the guano stain of Adelie penguins can be used to predict population size. Using high-resolution imagery and ground counts, I built a model to estimate the breeding population of Adelie penguins using a supervised classification to estimate guano size. These results suggest that the size of guano stain is an accurate predictor of population size, and can be applied to estimate remote Adelie penguin colonies. In my fourth chapter, I use air photos, satellite imagery, climate and mark-resight data to determine that climate change has positively impacted the population of Adelie penguins at Beaufort Island through a habitat release that ultimately affected the dynamics within the southern Ross Sea metapopulation. Finally, for my fifth chapter I combined the literature with observations from aerial surveys and satellite imagery to

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

    Science.gov (United States)

    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. Hazing Iran: Satellite Imagery, Human Rights, and City as Camp

    OpenAIRE

    Zhang, Amy

    2014-01-01

    As perhaps most obviously evidenced in the political maneuverings that led up to the second Gulf War in 2003, the use of satellite imagery to document spatial terrain is often, and almost instantly, politicized. In the two images presented here, this politicization takes on a two-way relationship and is open to contrasting and inevitably dualistic readings. One way of describing their relationship is as "Target" and "Aftermath". On the left, we have an image of the nuclear plant near the Iran...

  2. Visualization techniques for data mining of Latur district satellite imagery

    OpenAIRE

    Kodge, B. G.; Hiremath, P. S.

    2011-01-01

    This study presents a new visualization tool for classification of satellite imagery. Visualization of feature space allows exploration of patterns in the image data and insight into the classification process and related uncertainty. Visual Data Mining provides added value to image classifications as the user can be involved in the classification process providing increased confidence in and understanding of the results. In this study, we present a prototype visualization tool for visual dat...

  3. Automatic Mosaicking of Satellite Imagery Considering the Clouds

    Science.gov (United States)

    Kang, Yifei; Pan, Li; Chen, Qi; Zhang, Tong; Zhang, Shasha; Liu, Zhang

    2016-06-01

    With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosaicking method is proposed for cloudy satellite imagery in this paper. Firstly, modified Otsu thresholding and morphological processing are employed to extract cloudy areas and obtain the percentage of cloud cover. Then, cloud detection results are used to optimize the process of dodging and mosaicking. Thus, the mosaic image can be combined with more clear-sky areas instead of cloudy areas. Besides, clear-sky areas will be clear and distortionless. The Chinese GF-1 wide-field-of-view orthoimages are employed as experimental data. The performance of the proposed approach is evaluated in four aspects: the effect of cloud detection, the sharpness of clear-sky areas, the rationality of seamlines and efficiency. The evaluation results demonstrated that the mosaic image obtained by our method has fewer clouds, better internal color consistency and better visual clarity compared with that obtained by traditional method. The time consumed by the proposed method for 17 scenes of GF-1 orthoimages is within 4 hours on a desktop computer. The efficiency can meet the general production requirements for massive satellite imagery.

  4. IAEA Safeguards: Cost/benefit analysis of commercial satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Christer [SSC Satellitbild AB, Kiruna (Sweden)

    1999-03-01

    A major milestone in the efforts to strengthen the Safeguards System was reached in May 1997 when the Board of Governors approved a `Model Protocol Additional to Safeguards Agreements`. The Protocol provides the legal basis necessary to enhance the Agency`s ability to detect undeclared nuclear material and activities by using information available from open sources to complement the declarations made by Member States. Commercially available high-resolution satellite data has emerged as one potential complementary open information source to support the traditional and extended Safeguard activities of IAEA. This document constitutes a first report from SSC Satellitbild giving the Agency tentative and initial estimates of the potential cost and time-savings possible with the new proposed technology. The initial cost/benefit simulation will be further finalised in the following `Implementation Blueprint` study. The general foundation and starting point for the cost/benefit calculation is to simulate a new efficient and relatively small `imagery unit` within the IAEA, capable of performing advanced image processing as a tool for various safeguards tasks. The image processing capacity is suggested to be task- and interpretation-oriented. The study was performed over a period of 1,5 weeks in late 1998, and is based upon interviews of IAEA staff, reviews of existing IAEA documentation as well as from SSC Satellitbild`s long-standing experience of satellite imagery and field missions. The cost/benefit analysis is based on a spreadsheet simulation of five potential applications of commercial satellite imagery: Reference information; Confirmation of Agency acquired and Member State supplied data; Change detection and on-going monitoring; Assessing open source information available to the Agency; Detecting undeclared activities and undeclared sites. The study confirms that the proposed concept of a relatively small `imagery unit` using high-resolution data will be a sound and

  5. Aerial Photography and Imagery, Ortho-Corrected, 1-meter natural color imagery imagery over 13 of 15 counties (excluding Maricopa and Cochise), Published in 2005, 1:12000 (1in=1000ft) scale, Arizona State Cartographer's Office.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  6. Automated Identification of Rivers and Shorelines in Aerial Imagery Using Image Texture

    Science.gov (United States)

    2011-01-01

    defining the criteria for segmenting the image. For these cases certain automated, unsupervised (or minimally supervised), image classification ...banks, image analysis, edge finding, photography, satellite, texture, entropy 16. SECURITY CLASSIFICATION OF: a. REPORT Unclassified b. ABSTRACT...high resolution bank geometry. Much of the globe is covered by various sorts of multi- or hyperspectral imagery and numerous techniques have been

  7. Aerial Photography and Imagery, Oblique, This data set was acquired through a federal grant with Pictometry International. The imagery is either 4" or 9" resolution., Published in 2011, Not Applicable scale, Chippewa County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Oblique dataset current as of 2011. This data set was acquired through a federal grant with Pictometry International. The imagery is...

  8. Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

    Science.gov (United States)

    Lu, Bing; He, Yuhong

    2017-06-01

    Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition

  9. Crop classification using temporal stacks of multispectral satellite imagery

    Science.gov (United States)

    Moody, Daniela I.; Brumby, Steven P.; Chartrand, Rick; Keisler, Ryan; Longbotham, Nathan; Mertes, Carly; Skillman, Samuel W.; Warren, Michael S.

    2017-05-01

    The increase in performance, availability, and coverage of multispectral satellite sensor constellations has led to a drastic increase in data volume and data rate. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. The data analysis capability, however, has lagged behind storage and compute developments, and has traditionally focused on individual scene processing. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and can scale with the high-rate and dimensionality of imagery being collected. We investigate and compare the performance of pixel-level crop identification using tree-based classifiers and its dependence on both temporal and spectral features. Classification performance is assessed using as ground-truth Cropland Data Layer (CDL) crop masks generated by the US Department of Agriculture (USDA). The CDL maps contain 30m spatial resolution, pixel-level labels for around 200 categories of land cover, but are however only available post-growing season. The analysis focuses on McCook county in South Dakota and shows crop classification using a temporal stack of Landsat 8 (L8) imagery over the growing season, from April through October. Specifically, we consider the temporal L8 stack depth, as well as different normalized band difference indices, and evaluate their contribution to crop identification. We also show an extension of our algorithm to map corn and soy crops in the state of Mato Grosso, Brazil.

  10. Coral Reef environment reconstruction using small drones, new generation photogrammetry algorithms and satellite imagery

    Science.gov (United States)

    Elisa, Casella; Rovere, Alessio; Harris, Daniel; Parravicini, Valeriano

    2016-04-01

    Surveys based on Remotely Piloted Aircraft Systems (RPAS), together with new-generation Structure from Motion (SfM) and Multi-View Stereo (MVS) reconstruction algorithms have been employed to reconstruct the shallow bathymetry of the inner lagoon of a coral reef in Moorea, French Polinesia. This technique has already been used with a high rate of success on coastal environments (e.g. sandy beaches and rocky shorelines) reaching accuracy of the final Digital Elevation Model in the order of few centimeters. The application of such techniques to reconstruct shallow underwater environments is, though, still little reported. We then used the bathymetric dataset obtained from aerial pictures as ground-truth for relative bathymetry obtained from satellite imagery (WorldView-2) of a larger area within the same study site. The first results of our work suggest that RPAS coupled with SfM and MVS algorithms can be used to reconstruct shallow water environments with favorable weather conditions, and can be employed to ground-truth to satellite imagery.

  11. Sherlock Holmes' or Don Quixote`s certainty? Interpretations of cropmarks on satellite imageries in archaeological investigation

    Science.gov (United States)

    Wilgocka, Aleksandra; RÄ czkowski, Włodzimierz; Kostyrko, Mikołaj; Ruciński, Dominik

    2016-08-01

    Years of experience in air-photo interpretations provide us to conclusion that we know what we are looking at, we know why we can see cropmarks, we even can estimate, when are the best opportunities to observe them. But even today cropmarks may be a subject of misinterpretation or wishful thinking. The same problems appear when working with aerial photographs, satellite imageries, ALS, geophysics, etc. In the paper we present several case studies based on data acquired for and within ArchEO - archaeological applications of Earth Observation techniques project to discuss complexity and consequences of archaeological interpretations. While testing usefulness of satellite imagery in Poland on various types of sites, cropmarks were the most frequent indicators of past landscapes as well as archaeological and natural features. Hence, new archaeological sites have been discovered mainly thanks to cropmarks. This situation has given us an opportunity to test not only satellite imageries as a source of data but also confront them with results of other non-invasive methods of data acquisition. When working with variety of data we have met several issues which raised problems of interpretation. Consequently, questions related to the cognitive value of remote sensing data appear and should be discussed. What do the data represent? To what extent the imageries, cropmarks or other visualizations represent the past? How should we deal with ambiguity of data? What can we learn from pitfalls in the interpretation of cropmarks, soilmarks etc. to share more Sherlock's methodology rather than run around Don Quixote's delusions?

  12. Approximate Approaches to Geometric Corrections of High Resolution Satellite Imagery

    Institute of Scientific and Technical Information of China (English)

    SHI Wenzhong; Ahmed Shaker

    2004-01-01

    The exploitation of different non-rigorous mathematical models as opposed to the satellite rigorous models is discussed for geometric corrections and topographic/thematic maps production of high-resolution satellite imagery (HRSI). Furthermore, this paper focuses on the effects of the number of GCPs and the terrain elevation difference within the area covered by the images on the obtained ground points accuracy. From the research, it is obviously found that non-rigorous orientation and triangulation models can be used successfully in most cases for 2D rectification and 3D ground points determination without a camera model or the satellite ephemeris data. In addition, the accuracy up to the sub-pixel level in plane and about one pixel in elevation can be achieved with a modest number of GCPs.

  13. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    Science.gov (United States)

    Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

    2016-06-01

    Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in

  14. Radiometric Correction of Multitemporal Satellite Imagery

    Directory of Open Access Journals (Sweden)

    S. G. Biday,

    2010-01-01

    Full Text Available Problem statement: Repeated observation of a given area over time yields potential for many forms of change detection analysis. These repeated observations are confounded in terms of radiometric consistency due to changes in sensor calibration over time, differences in illumination, observation angles and variation in atmospheric effects. Also major problem with satellite images is that regions below clouds are not covered by sensor. Cloud detection, removal and data prediction in cloudy region is essential for image interpretation. Approach: This study demonstrated applicability of empirical relative radiometric normalization methods to a set of multitemporal cloudy images acquired by Resourcesat-1 LISS III sensor. Objective of this study was to detect and remove cloud cover and normalize an image radiometrically. Cloud detection was achieved by using Average Brightness Threshold (ABT algorithm. The detected cloud removed and replaced with data from another images of the same area. We proposed a new method in which cloudy pixels are replaced with predicted pixel values obtained by regression. After cloud removal, the proposed normalization method was applied to reduce the radiometric influence caused by non surface factors. This process identified landscape elements whose reflectance values are nearly constant over time, i.e., the subset of non-changing pixels are identified using frequency based correlation technique. Further, we proposed another method of radiometric correction in frequency domain, Pseudo-Invariant Feature regression and this process removed landscape elements such as vegetation whose reflectance values are not constant over time. It takes advantage of vegetation being typically high frequency area, can be removed by low pass filter. Results: The quality of radiometric normalization is statistically assessed by R2 value and Root Mean Square Error (RMSE between each pair of analogous band. Further we verified that difference

  15. Effective delineation of urban flooded areas based on aerial ortho-photo imagery

    Science.gov (United States)

    Zhang, Ying; Guindon, Bert; Raymond, Don; Hong, Gang

    2016-10-01

    The combination of rapid global urban growth and climate change has resulted in increased occurrence of major urban flood events across the globe. The distribution of flooded area is one of the key information layers for applications of emergency planning and response management. While SAR systems and technologies have been widely used for flood area delineation, radar images suffer from range ambiguities arising from corner reflection effects and shadowing in dense urban settings. A new mapping framework is proposed for the extraction and quantification of flood extent based on aerial optical multi-spectral imagery and ancillary data. This involves first mapping of flood areas directly visible to the sensor. Subsequently, the complete area of submergence is estimated from this initial mapping and inference techniques based on baseline data such as land cover and GIS information such as available digital elevation models. The methodology has been tested and proven effective using aerial photography for the case of the 2013 flood in Calgary, Canada.

  16. Direct determination of surface albedos from satellite imagery

    Science.gov (United States)

    Mekler, Y.; Joseph, J. H.

    1983-01-01

    An empirical method to measure the spectral surface albedo of surfaces from Landsat imagery is presented and analyzed. The empiricism in the method is due only to the fact that three parameters of the solution must be determined for each spectral photograph of an image on the basis of independently known albedos at three points. The approach is otherwise based on exact solutions of the radiative transfer equation for upwelling intensity. Application of the method allows the routine construction of spectral albedo maps from satelite imagery, without requiring detailed knowledge of the atmospheric aerosol content, as long as the optical depth is less than 0.75, and of the calibration of the satellite sensor.

  17. Sugarcane Land Classification with Satellite Imagery using Logistic Regression Model

    Science.gov (United States)

    Henry, F.; Herwindiati, D. E.; Mulyono, S.; Hendryli, J.

    2017-03-01

    This paper discusses the classification of sugarcane plantation area from Landsat-8 satellite imagery. The classification process uses binary logistic regression method with time series data of normalized difference vegetation index as input. The process is divided into two steps: training and classification. The purpose of training step is to identify the best parameter of the regression model using gradient descent algorithm. The best fit of the model can be utilized to classify sugarcane and non-sugarcane area. The experiment shows high accuracy and successfully maps the sugarcane plantation area which obtained best result of Cohen’s Kappa value 0.7833 (strong) with 89.167% accuracy.

  18. A semi-automated single day image differencing technique to identify animals in aerial imagery.

    Directory of Open Access Journals (Sweden)

    Pat Terletzky

    Full Text Available 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.

  19. A semi-automated single day image differencing technique to identify animals in aerial imagery.

    Science.gov (United States)

    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.

  20. Combining satellite imagery and machine learning to predict poverty.

    Science.gov (United States)

    Jean, Neal; Burke, Marshall; Xie, Michael; Davis, W Matthew; Lobell, David B; Ermon, Stefano

    2016-08-19

    Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolution satellite imagery. Using survey and satellite data from five African countries--Nigeria, Tanzania, Uganda, Malawi, and Rwanda--we show how a convolutional neural network can be trained to identify image features that can explain up to 75% of the variation in local-level economic outcomes. Our method, which requires only publicly available data, could transform efforts to track and target poverty in developing countries. It also demonstrates how powerful machine learning techniques can be applied in a setting with limited training data, suggesting broad potential application across many scientific domains.

  1. Assessing Usefulness of High-Resolution Satellite Imagery (HRSI) for Re-Survey of Cadastral Maps

    Science.gov (United States)

    Rao, S. S.; Sharma, J. R.; Rajashekar, S. S.; Rao, D. S. P.; Arepalli, A.; Arora, V.; Kuldeep; Singh, R. P.; Kanaparthi, M.

    2014-11-01

    The Government of India has initiated "National Land Records Modernization Programme (NLRMP)" with emphasis to modernize management of land records, minimize scope of land/property disputes, enhance transparency in the land records maintenance system, and facilitate moving eventually towards guaranteed conclusive titles to immovable properties in the country. One of the major components of the programme is survey/re-survey and updating of all survey and settlement records including creation of original cadastral records wherever necessary. The use of ETS/GPS, Aerial or High Resolution Satellite Images (HRSI) and hybrid method of images are suggested for re-survey in the guidelines. The emerging new satellite technologies enabling earth observation at a spatial resolution of 1.0m or 0.5m or even 0.41m have brought revolutionary changes in the field of cadastral survey. The highresolution satellite imagery (HRSI) is showing its usefulness for cadastral surveys in terms of clear identification of parcel boundaries and other cultural features due to which traditional cadastre and land registration systems have been undergoing major changes worldwide. In the present research study, cadastral maps are derived from ETS/GPS, HRSI of 1.0m and 0.5m and used for comparison. The differences in areas, perimeter and position of parcels derived from HRSI are compared vis-a-vis ETS/GPS boundaries. An assessment has been made on the usefulness of HRSI for re-survey of cadastral maps vis-a-vis conventional ground survey.

  2. Measurement of sea ice and icebergs topography using satellite imagery

    Science.gov (United States)

    Zakharov, I.; Power, D.; Prasad, S.

    2016-12-01

    Sea ice topography represents geospatial information on the three-dimensional geometrical attributes of the ice surface including height and shape of various ice features. The features interest consist of deformed (pressure ridges, rubbles and hummocks) and level sea ice as well as glacial ice. Sea ice topography is important for scientific research and climate studies because it helps characterise ice volume and thickness and it influences the near-surface atmospheric transport by impacting the drag coefficients. It also represents critical information to marine operational applications, such as ships navigation and risks assessment for offshore infrastructures. The several methods were used to measure sea ice topography from a single satellite image as well as multiple images. The techniques based on the single image, acquired by optical or synthetic aperture radar (SAR) satellites, derive the height and shape information from shadow and shading. Optical stereo images acquired by very high resolution (0.5 m) satellites were used to extract highly detailed digital elevation model (DEM). SAR imagery allowed extraction of DEM using stereo-radargrammetry and interferometry. The images from optical satellites WorldView, Pleiades, GeoEye, Spot, and Landsat-8 were used to measure topography of sea ice deformation features and glacial ice including icebergs and ice islands. These features were mapped in regions of the Central Arctic, Baffin Bay and the coast of Greenland. SAR imagery including interferometric TanDEM-X data and full polarimetric Radarsat-2 were used to extract ridge frequency and measure spatial parameters of glacial features. The accuracy was evaluated by comparison of the results from different methods demonstrating their strengths and limitations. Ridge height and frequency were also compared with the high resolution results from the Los Alamos sea ice model (CICE), regionally implemented for Baffin Bay and the Labrador Sea.

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

    Science.gov (United States)

    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

  4. INFLUENCE OF GSD FOR 3D CITY MODELING AND VISUALIZATION FROM AERIAL IMAGERY

    Directory of Open Access Journals (Sweden)

    M. Alrajhi

    2016-06-01

    Full Text Available 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

  5. Aerial Photography and Imagery, Ortho-Corrected, Black & White imagery flown in 2000 leaf-off season, countywide 400 scale imagery, 200 scale imagery in fast growing portion of the county in the south west, and 100 scale imagery in the towns and Lake Royale., Published in 2000, 1:4800 (1in=400ft) scale, Franklin County G.I.S..

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  6. Using satellite imagery to assess the influence of urban development on the impacts of extreme rainfall

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin; Madsen, Henrik;

    We investigate the applicability of medium resolution Landsat satellite imagery for mapping temporal changes in urban land cover for direct use in urban flood models. The overarching aim is to provide accurate and cost- and resource-efficient quantification of temporal changes in risk towards...... the impacts of pluvial flooding. Initial results show that satellite imagery may have considerable potential in this respect....

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

    Science.gov (United States)

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

    2016-01-01

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

  8. Rays in the northern Gulf of Mexico: Aerial Survey and Satellite Telemetry 2008-2012 (NCEI Accession 0129495)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains distribution and abundance data for rays in the Gulf of Mexico collected through aerial surveys and satellite telemetry. Aerial survey data...

  9. Vegetation habitat units derived from 2011 aerial imagery and field data for the Elwha River estuary, Washington

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Estuary vegetation cover delineated from 3 September 2011 0.3-meter-resolution aerial imagery (Microsoft/Digital Globe) at a scale of 1:1500. Image date of 3-Sep...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Shorter, Nicholas Sven

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

  12. Vertical Accuracy Comparison of Digital Elevation Model from LIDAR and Multitemporal Satellite Imagery

    Science.gov (United States)

    Octariady, J.; Hikmat, A.; Widyaningrum, E.; Mayasari, R.; Fajari, M. K.

    2017-05-01

    Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo satellite imagery DEM. Multitemporal stereo satellite imagery generated semi-automatically by using 3 scene stereo satellite imagery with acquisition 2013-2014. The high value given each of DEM serve as the basis for calculating high accuracy DEM respectively. The results showed the high value differences in the fraction of the meter between LiDAR DEM and multitemporal stereo satellite imagery DEM.

  13. USGS Imagery Overlay Map Service from The National Map - National Geospatial Data Asset (NGDA) High Resolution Orthoimagery

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — USGS_EROS_Ortho_SCALE service contains orthorectified digital aerial photographs and satellite imagery that are commonly referred to as orthoimagery. The imagery in...

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

    Science.gov (United States)

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

    2017-04-01

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

  15. Does the Data Resolution/origin Matter? Satellite, Airborne and Uav Imagery to Tackle Plant Invasions

    Science.gov (United States)

    Müllerová, Jana; Brůna, Josef; Dvořák, Petr; Bartaloš, Tomáš; Vítková, Michaela

    2016-06-01

    Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.

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

    Science.gov (United States)

    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.

  17. Quantifying River Widths of North America from Satellite Imagery

    Science.gov (United States)

    Allen, G. H.; Pavelsky, T.; Miller, Z.

    2013-12-01

    River width is a fundamental predictor variable in many hydrologic, geomorphic, and biogeochemical models, yet current large-scale models rely on theoretical hydraulic geometry relationships that do not fully capture natural variability in river form. Here we present the first high-resolution dataset of long-term mean width of North American rivers wider than 30 m. The dataset contains 7.93 million georeferenced width measurements derived from Landsat TM and ETM+ imagery that were acquired when rivers were most likely to be at mean discharge. We built the dataset by developing an automated procedure that selects and downloads raw imagery, creates cloud-free normalized difference water index images, histogram balances and mosaics them together, and produces a water mask using a dynamic water-land threshold technique. We then visually inspected and corrected the mask for errors and used RivWidth software to calculate river width at each river centerline pixel. We validated our dataset using >1000 United States Geological Survey and Water Survey of Canada in situ gauge station measurements. Error analysis shows a robust relationship between the remotely sensed widths and in situ gauge measurements with an r 2 = 0.86 (Spearman's = 0.81) and a mean absolute error of 27.5 m. We find that North American river widths lie on logarithmic frequency curve with some notable exceptions at widths SWOT) satellite mission.

  18. Surface Characteristics of Green Island Wakes from Satellite Imagery

    Science.gov (United States)

    Cheng, Kai-Ho; Hsu, Po-Chun; Ho, Chung-Ru

    2017-04-01

    Characteristics of an island wake induced by the Kuroshio Current flows pass by Green Island, a small island 40 km off southeast of Taiwan is investigated by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. The MODIS sea surface temperature (SST) and chlorophyll-a (chl-a) imagery is produced at 250-meter resolution from 2014 to 2015 using the SeaDAS software package which is developed by the National Aeronautics and Space Administration. The wake occurrence is 59% observed from SST images during the data span. The average cooling area is 190 km2, but the area is significantly changed with wind directions. The wake area is increased during southerly winds and is reduced during northerly winds. Besides, the average cooling SST was about 2.1 oC between the front and rear island. Comparing the temperature difference between the wake and its left side, the difference is 1.96 oC. In addition, the wakes have 1 3 times higher than normal in chlorophyll concentration. The results indicate the island mass effect makes the surface water of Green island wake colder and chl-a higher.

  19. Automatic detection of ship tracks in ATSR-2 satellite imagery

    Directory of Open Access Journals (Sweden)

    E. Campmany

    2009-03-01

    Full Text Available Ships modify cloud microphysics by adding cloud condensation nuclei (CCN to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. An algorithm has been developed to automate the detection of ship tracks in Along Track Scanning Radiometer 2 (ATSR-2 imagery. The scheme has been integrated into the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of their neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR-2 data. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both West Africa and South-Western Europe. The global distribution of ship tracks shows strong seasonality, little inter-annual variability and a similar spatial pattern to the distribution of ship emissions.

  20. Efficient Algorithm for Railway Tracks Detection Using Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Ali Javed

    2012-10-01

    Full Text Available Satellite imagery can produce maps including roads, railway tracks, buildings, bridges, oceans, lakes, rivers, etc. In developed countries like USA, Canada, Australia, Europe, images produced by Google map are of high resolution and good quality. On the other hand, mostly images of the third world countries like Pakistan, Asian and African countries are of poor quality and not clearly visible. Similarly railway tracks of these countries are hardly visible in Google map. We have developed an efficient algorithm for railway track detection from a low quality image of Google map. This would lead to detect damaged railway track, railway crossings and help to schedule/divert locomotive movements in order to avoid catastrophe.

  1. Estimation of Satellite Orientation from Space Surveillance Imagery Measured with an Adaptive Optics Telescope

    Science.gov (United States)

    1996-12-01

    SATELLITE ORIENTATION FROM SPACE SURVEILLANCE IMAGERY MEASURED WITH AN ADAPTIVE OPTICS TELESCOPE THESIS Gregory E. Wood Lieutenant, USAF AFIT/GSO/ENP...the official policy or position of the Department of Defense or the U. S. Government. AFIT/GSO/ENP/96D-02 ESTIMATION OF SATELLITE ORIENTATION FROM...surveillance operations. xii ESTIMATION OF SATELLITE ORIENTATION FROM SPACE SURVEILLANCE IMAGERY MEASURED WITH AN ADAPTIVE OPTICS TELESCOPE

  2. Multi-decadal record of ice dynamics on Daugaard Jensen Gletscher, East Greenland, from satellite imagery and terrestrial measurements

    DEFF Research Database (Denmark)

    Stearns, L.A.; Hamilton, G.S.; Reeh, Niels

    2005-01-01

    The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained...... in approximately the same position over the past similar to 50 years. There is no evidence of a change in ice motion between 1968 and 2001, based on a comparison of velocities derived from terrestrial surveying and feature tracking using sequential satellite images. Estimates of flux near the entrance to the fjord...... vs snow accumulation in the interior catchment show that Daugaard Jensen Gletscher has a small negative mass balance. This result is consistent with other mass-balance estimates for the inland region of the glacier....

  3. Mosaicking of Unmanned Aerial Vehicle Imagery in the Absence of Camera Poses

    Directory of Open Access Journals (Sweden)

    Yuhua Xu

    2016-03-01

    Full Text Available The mosaicking of Unmanned Aerial Vehicle (UAV imagery usually requires information from additional sensors, such as Global Position System (GPS and Inertial Measurement Unit (IMU, to facilitate direct orientation, or 3D reconstruction approaches (e.g., structure-from-motion to recover the camera poses. In this paper, we propose a novel mosaicking method for UAV imagery in which neither direct nor indirect orientation procedures are required. Inspired by the embedded deformation model, a widely used non-rigid mesh deformation model, we present a novel objective function for image mosaicking. Firstly, we construct a feature correspondence energy term that minimizes the sum of the squared distances between matched feature pairs to align the images geometrically. Secondly, we model a regularization term that constrains the image transformation parameters directly by keeping all transformations as rigid as possible to avoid global distortion in the final mosaic. Experimental results presented herein demonstrate that the accuracy of our method is twice as high as an existing (purely image-based approach, with the associated benefits of significantly faster processing times and improved robustness with respect to reference image selection.

  4. Deploying a quantum annealing processor to detect tree cover in aerial imagery of California

    Science.gov (United States)

    Basu, Saikat; Ganguly, Sangram; Michaelis, Andrew; Mukhopadhyay, Supratik; Nemani, Ramakrishna R.

    2017-01-01

    Quantum annealing is an experimental and potentially breakthrough computational technology for handling hard optimization problems, including problems of computer vision. We present a case study in training a production-scale classifier of tree cover in remote sensing imagery, using early-generation quantum annealing hardware built by D-wave Systems, Inc. Beginning within a known boosting framework, we train decision stumps on texture features and vegetation indices extracted from four-band, one-meter-resolution aerial imagery from the state of California. We then impose a regulated quadratic training objective to select an optimal voting subset from among these stumps. The votes of the subset define the classifier. For optimization, the logical variables in the objective function map to quantum bits in the hardware device, while quadratic couplings encode as the strength of physical interactions between the quantum bits. Hardware design limits the number of couplings between these basic physical entities to five or six. To account for this limitation in mapping large problems to the hardware architecture, we propose a truncation and rescaling of the training objective through a trainable metaparameter. The boosting process on our basic 108- and 508-variable problems, thus constituted, returns classifiers that incorporate a diverse range of color- and texture-based metrics and discriminate tree cover with accuracies as high as 92% in validation and 90% on a test scene encompassing the open space preserves and dense suburban build of Mill Valley, CA. PMID:28241028

  5. Detection of ship tracks in ATSR2 satellite imagery

    Directory of Open Access Journals (Sweden)

    E. Campmany

    2008-08-01

    Full Text Available Ships modify cloud microphysics by adding cloud condensation nuclei (CCN to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both west Africa and south-western Europe. In order to automate their detection within the Along Track Scanning Radiometer 2 (ATSR2 data set an algorithm was developed and integrated with the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of its neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR2 data. A month of results have been compared with other satellite datasets to validate the algorithm. There is a high ratio of false detections. Nevertheless the global distribution of ship tracks shows a similar pattern to the ship emissions distribution.

  6. Aerial Photography and Imagery, Ortho-Corrected, Color and NIR aerial orthoimagery 2006-07, Published in 2007, 1:2400 (1in=200ft) scale, Office of Management and Budget.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  7. Aerial Photography and Imagery, Ortho-Corrected, Aerial Photography for Emporia & Metro Planning Area, Published in 2007, 1:600 (1in=50ft) scale, City of Emporia/Lyon County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  8. Aerial Photography and Imagery, Ortho-Corrected, Lyon County Aerial Photography Rural:1', Black and White; Cities: 6", Color, Published in 2003, 1:4800 (1in=400ft) scale, City of Emporia/Lyon County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  9. Aerial Photography and Imagery, Ortho-Corrected, 4 inch aerial photography (color, infrared, and color oblique) in urban areas, 1 foot in national forest, Published in 2006, 1:600 (1in=50ft) scale, County of Los Angeles.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

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

    Science.gov (United States)

    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

  11. An ASIFT-Based Local Registration Method for Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiangjun Wang

    2015-05-01

    Full Text Available Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion. Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE and better distribution of feature points.

  12. Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV Imagery

    Directory of Open Access Journals (Sweden)

    Arko Lucieer

    2012-05-01

    Full Text Available Sensor miniaturisation, improved battery technology and the availability of low-cost yet advanced Unmanned Aerial Vehicles (UAV have provided new opportunities for environmental remote sensing. The UAV provides a platform for close-range aerial photography. Detailed imagery captured from micro-UAV can produce dense point clouds using multi-view stereopsis (MVS techniques combining photogrammetry and computer vision. This study applies MVS techniques to imagery acquired from a multi-rotor micro-UAV of a natural coastal site in southeastern Tasmania, Australia. A very dense point cloud ( < 1–3 cm point spacing is produced in an arbitrary coordinate system using full resolution imagery, whereas other studies usually downsample the original imagery. The point cloud is sparse in areas of complex vegetation and where surfaces have a homogeneous texture. Ground control points collected with Differential Global Positioning System (DGPS are identified and used for georeferencing via a Helmert transformation. This study compared georeferenced point clouds to a Total Station survey in order to assess and quantify their geometric accuracy. The results indicate that a georeferenced point cloud accurate to 25–40 mm can be obtained from imagery acquired from 50 m. UAV-based image capture provides the spatial and temporal resolution required to map and monitor natural landscapes. This paper assesses the accuracy of the generated point clouds based on field survey points. Based on our key findings we conclude that sub-decimetre terrain change (in this case coastal erosion can be monitored.

  13. Aerial Photography and Imagery, Ortho-Corrected, Published in 2005, 1:4800 (1in=400ft) scale, County of Grant.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  14. Aerial Photography and Imagery, Ortho-Corrected, Published in 2007, 1:2400 (1in=200ft) scale, Aiken County Govt.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  15. Aerial Photography and Imagery, Ortho-Corrected, National Agricultural Inventory Program - Orthoimagery Statewide, Published in 2005, 1:24000 (1in=2000ft) scale, Office of Shared Solutions.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Orthoimagery information as...

  16. Aerial Photography and Imagery, Ortho-Corrected, Published in 2007, 1:2400 (1in=200ft) scale, Chautauqua County/Elk County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  17. Aerial Photography and Imagery, Ortho-Corrected, June 2007 NAIP DOQQ, Published in 2007, 1:12000 (1in=1000ft) scale, Cochise County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  18. Aerial Photography and Imagery, Ortho-Corrected, Published in 2008, 1:2400 (1in=200ft) scale, City of Benson, Arizona.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  19. Aerial Photography and Imagery, Ortho-Corrected, Allegany County 1997 Orthophotography, Published in 1997, 1:2400 (1in=200ft) scale, Allegany County Government.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  20. Aerial Photography and Imagery, Ortho-Corrected, Published in 2005, 1:1200 (1in=100ft) scale, Walker County Government.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  1. Aerial Photography and Imagery, Ortho-Corrected, ortho05, Published in 2005, 1:1200 (1in=100ft) scale, Jasper County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Field Observation information...

  2. Aerial Photography and Imagery, Ortho-Corrected, 2007 6 Inch Color Orthophoto, Published in 2007, 1:1200 (1in=100ft) scale, Dunn County, WI.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  3. Aerial Photography and Imagery, Ortho-Corrected, Published in 2009, 1:4800 (1in=400ft) scale, Heart of Georgia Altamaha RC.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  4. Aerial Photography and Imagery, Ortho-Corrected, Published in 2008, 1:1200 (1in=100ft) scale, Johnson County, Iowa.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale as of 2008. Data by this publisher are often provided in State...

  5. Aerial Photography and Imagery, Oblique, 24" resolution for entire county, Published in 2010, 1:4800 (1in=400ft) scale, CLAY COUNTY.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of 2010. It...

  6. Aerial Photography and Imagery, Ortho-Corrected, Maui Digital Raster Graphic, Published in 2004, 1:24000 (1in=2000ft) scale, U.S. Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Orthoimagery information as...

  7. Aerial Photography and Imagery, Ortho-Corrected, Molokai Digital Raster Graphic, Published in 2004, 1:24000 (1in=2000ft) scale, U.S. Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Hardcopy Maps information as...

  8. Aerial Photography and Imagery, Ortho-Corrected, Maui County Digital Orthophoto Mosaic, Published in 2003, 1:24000 (1in=2000ft) scale, U.S. Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Hardcopy Maps information as...

  9. Aerial Photography and Imagery, Ortho-Corrected, Urban layer has 4" resolution, Published in 2009, 1:1200 (1in=100ft) scale, Cerro Gordo County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  10. Aerial Photography and Imagery, Ortho-Corrected, 2010 Orthophotography, Published in 2010, 1:2400 (1in=200ft) scale, Walworth County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Other information as of 2010....

  11. Aerial Photography and Imagery, Ortho-Corrected, Published in 2005, 1:4800 (1in=400ft) scale, Churchill County, NV.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  12. Aerial Photography and Imagery, Ortho-Corrected, 6-inch color orthoimagery, Published in 2007, 1:600 (1in=50ft) scale, Sheridan County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  13. Aerial Photography and Imagery, Ortho-Corrected, Oahu Digital Orthophoto Mosaic, Published in 2003, 1:24000 (1in=2000ft) scale, U.S. Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Orthoimagery information as...

  14. Aerial Photography and Imagery, Ortho-Corrected, true-color leaf-off orthophotography, Published in 2007, 1:2400 (1in=200ft) scale, Rockingham County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  15. Aerial Photography and Imagery, Ortho-Corrected, Horry County, SC 6" RGB orthophotography, Published in 2008, 1:2400 (1in=200ft) scale, Horry County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  16. Aerial Photography and Imagery, Ortho-Corrected, 2000 Color 1 Foot Orthoimagery, Published in 2000, 1:2400 (1in=200ft) scale, Winnebago County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  17. Aerial Photography and Imagery, Ortho-Corrected, USDA-NAIP, Published in 2006, 1:12000 (1in=1000ft) scale, Office of Geographic Information.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  18. Aerial Photography and Imagery, Ortho-Corrected, Published in 2006, 1:4800 (1in=400ft) scale, Thomas County BOC.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  19. Aerial Photography and Imagery, Ortho-Corrected, Published in 2009, 1:100000 (1in=8333ft) scale, City of Americus & Sumter County, GA GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:100000 (1in=8333ft) scale, was produced all or in part from Orthoimagery information as...

  20. Aerial Photography and Imagery, Ortho-Corrected, Color Orthophotography at 12-inch pixel resolution, Published in 2010, 1:1200 (1in=100ft) scale, Pierce County Wisconsin.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  1. Aerial Photography and Imagery, Ortho-Corrected, Harnett.Orthos_2008, Published in 2008, 1:2400 (1in=200ft) scale, Harnett County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Other information as of 2008....

  2. Aerial Photography and Imagery, Ortho-Corrected, USDA-NAIP, Published in 2004, 1:12000 (1in=1000ft) scale, Office of Geographic Information.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  3. Aerial Photography and Imagery, Ortho-Corrected, 6 inch pixel orthophotography by Pictometry, Published in 2008, 1:600 (1in=50ft) scale, Fulton County Government.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  4. Aerial Photography and Imagery, Ortho-Corrected, 6" Black and White Cities, Published in 2000, 1:1200 (1in=100ft) scale, Rice County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  5. Aerial Photography and Imagery, Ortho-Corrected, Orthoimagery for Oconee County, Georgia, Published in 2006, 1:4800 (1in=400ft) scale, Northeast Georgia Regional Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  6. Aerial Photography and Imagery, Ortho-Corrected, Mr. Sid file, Published in unknown, 1:600 (1in=50ft) scale, Board of Tax Assessors.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  7. Aerial Photography and Imagery, Ortho-Corrected, Oahu Digital Raster Graphic, Published in 2003, 1:24000 (1in=2000ft) scale, U.S. Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Hardcopy Maps information as...

  8. Aerial Photography and Imagery, Ortho-Corrected, Published in 2008, 1:600 (1in=50ft) scale, Weld County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  9. Aerial Photography and Imagery, Ortho-Corrected, Rural areas, Published in 2005, 1:4800 (1in=400ft) scale, Benton County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  10. Aerial Photography and Imagery, Ortho-Corrected, WROC 2010, Published in 2010, 1:4800 (1in=400ft) scale, Sawyer County Surveyors Department.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Field Observation information...

  11. Aerial Photography and Imagery, Ortho-Corrected, 6" ground resolution, black & white, Published in 2005, 1:1200 (1in=100ft) scale, Brown County, WI.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  12. Aerial Photography and Imagery, Ortho-Corrected, color infrared DOP washoe county, Published in 2006, 1:1200 (1in=100ft) scale, Washoe County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  13. Aerial Photography and Imagery, Ortho-Corrected, natural color DOP washoe county, Published in 2006, 1:1200 (1in=100ft) scale, Washoe County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  14. Aerial Photography and Imagery, Ortho-Corrected, 2008 Orthogonal Images from Pictometry, Published in 2008, 1:1200 (1in=100ft) scale, Jefferson County Land Information Office.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  15. Aerial Photography and Imagery, Ortho-Corrected, NAIP 2006, Published in 2006, 1:24000 (1in=2000ft) scale, Washington County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Other information as of 2006....

  16. Aerial Photography and Imagery, Ortho-Corrected, 1993 1 meter resolution 7.5 minute quadrangle, Published in 1993, Rock County Planning, Economic, and Community Development Agency.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, was produced all or in part from Orthoimagery information as of 1993. It is described as '1993 1 meter...

  17. Aerial Photography and Imagery, Ortho-Corrected, 6" Color Ortho for Elkhart. Rolla, Richfield, Published in 2007, 1:1200 (1in=100ft) scale, Morton County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  18. Aerial Photography and Imagery, Ortho-Corrected, Color Orthophotos for all of Dickinson County, Published in 2007, 1:2400 (1in=200ft) scale, Dickinson County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  19. Aerial Photography and Imagery, Ortho-Corrected, Urban areas, Published in 2006, 1:1200 (1in=100ft) scale, Carroll County, Iowa.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  20. Aerial Photography and Imagery, Ortho-Corrected, 1 meter rural and 6 inch urban, Published in 2009, 1:600 (1in=50ft) scale, Franklin County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  1. Aerial Photography and Imagery, Ortho-Corrected, 2006 NAIPs for all counties we serve., Published in 2006, Smaller than 1:100000 scale, Prairie Land Electric COOP, Inc..

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at Smaller than 1:100000 scale, was produced all or in part from Orthoimagery information as...

  2. Aerial Photography and Imagery, Ortho-Corrected, 2005 1-Foot Resolution Digital Imagery, Published in 2005, 1:2400 (1in=200ft) scale, Dane County Land Information Office.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  3. Aerial Photography and Imagery, Ortho-Corrected, Six-inch orthoimagery of Washburn County, Wisconsin. The imagery was collected May 5, 2004 by ImageAmerica, Published in 2004, 1:4800 (1in=400ft) scale, Washburn County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  4. Aerial Photography and Imagery, Ortho-Corrected, Color 1 meter NAIP --This data set contains imagery from the National Agricultural, Published in 2006, 1:24000 (1in=2000ft) scale, State of Utah Automated Geographic Reference Center.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Orthoimagery information as...

  5. Aerial Photography and Imagery, Oblique, Prince George's County Oblique Imagery captured through Pictometry International, Published in 2005, 1:2400 (1in=200ft) scale, Prince George's County Office of Information Technology and Communications.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Other information as of 2005. It is...

  6. Aerial Photography and Imagery, Ortho-Corrected, Effingham County Imagery - 1 pixel = 6 inches / We also have a MrSID, Published in 2008, 1:600 (1in=50ft) scale, Effingham County Board Of Commissioners.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  7. Aerial Photography and Imagery, Oblique, Prince George's County Oblique Imagery captured through Pictometry International, Published in 2009, 1:2400 (1in=200ft) scale, Prince George's County Office of Information Technology and Communications.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Other information as of 2009. It is...

  8. The development of a land use inventory for regional planning using satellite imagery

    Science.gov (United States)

    Hessling, A. H.; Mara, T. G.

    1975-01-01

    Water quality planning in Ohio, Kentucky, and Indiana is reviewed in terms of use of land use data and satellite imagery. A land use inventory applicable to water quality planning and developed through computer processing of LANDSAT-1 imagery is described.

  9. Casa Grande Ruins National Monument Vegetation Mapping Project - Quickbird Satellite Imagery

    Data.gov (United States)

    National Park Service, Department of the Interior — This imagery was acquired on December 3, 2007 by DigitalGlobe, Inc.'s Quickbird satellite. Its 4 multispectral bands (blue, green, red, near infrared), together with...

  10. Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Cloud-free Landsat satellite imagery mosaics of the islands of the main 8 Hawaiian Islands (Hawaii, Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau)....

  11. Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery (Draft)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Estimated shallow-water, depth maps were produced using rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations in the...

  12. Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Estimated shallow-water, depth maps were produced using rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations in the...

  13. Nearshore Benthic Habitats of Timor-Leste Derived from WorldView-2 Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Benthic habitat classes were derived for nearshore waters around Timor-Leste from WorldView-2 satellite imagery. Habitat classes include different combinations of...

  14. Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Cloud-free Landsat satellite imagery mosaics of the islands of the main 8 Hawaiian Islands (Hawaii, Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau). Landsat...

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

    Science.gov (United States)

    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.

  16. Use of satellite imagery to map and monitor vegetation in New Zealand

    OpenAIRE

    Stephens, P. R.; Dymond, J. R.; Brown, L J

    1995-01-01

    研究概要:Land resource and environmental decision makers require quantitative information on the spatial distribution of vegetation types and their condition, and changes in these over time. Such vegetation mapping and monitoring is often required to be undertaken quickly. Remotely-sensed satellite imagery, in conjunction with other data sources, have been used to satisfy this need. This paper describes the uses of satellite imagery by reference to three regional mapping projects in New Zealand. ...

  17. Detecting methane ebullition on thermokarst lake ice using high resolution optical aerial imagery

    Directory of Open Access Journals (Sweden)

    P. R. Lindgren

    2015-05-01

    Full Text Available Thermokarst lakes are important emitters of methane, a potent greenhouse gas. However, accurate estimation of methane flux from thermokarst lakes is difficult due to their remoteness and observational challenges associated with the heterogeneous nature of ebullition (bubbling. We used multi-temporal high-resolution (9–11 cm aerial images of an interior Alaskan thermokarst lake, Goldstream Lake, acquired 2 and 4 days following freeze-up in 2011 and 2012, respectively, to characterize methane ebullition seeps and to estimate whole-lake ebullition. Bubbles impeded by the lake ice sheet form distinct white patches as a function of bubbling rate vs. time as ice thickens. Our aerial imagery thus captured in a single snapshot the ebullition events that occurred before the image acquisition. Image analysis showed that low-flux A- and B-type seeps are associated with low brightness patches and are statistically distinct from high-flux C-type and Hotspot seeps associated with high brightness patches. Mean whole-lake ebullition based on optical image analysis in combination with bubble-trap flux measurements was estimated to be 174 ± 28 and 216 ± 33 mL gas m−2 d−1 for the years 2011 and 2012, respectively. A large number of seeps demonstrated spatio-temporal stability over our two-year study period. A strong inverse exponential relationship (R2 ≥ 0.79 was found between percent surface area of lake ice covered with bubble patches and distance from the active thermokarst lake margin. Our study shows that optical remote sensing is a powerful tool to map ebullition seeps on lake ice, to identify their relative strength of ebullition and to assess their spatio-temporal variability.

  18. Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

    Science.gov (United States)

    Husak, G.J.; Marshall, M. T.; Michaelsen, J.; Pedreros, Diego; Funk, Christopher C.; Galu, G.

    2008-01-01

    Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

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

    Science.gov (United States)

    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

  20. Aerial Photography and Imagery, Ortho-Corrected, 2003 NAIP Digital Orthophotographs of Rhode Island; This data set contains imagery from the National Agricultural Imagery Program (NAIP). NAIP acquires digital ortho imagery during the agricultural growing seasons in the continental U.S., Published in 2004, 1:24000 (1in=2000ft) scale, State of Rhode Island and Providence Plantations.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Orthoimagery information as...

  1. Eyes in the sky: a comparative spatial analysis of aerial and satellite surveillance of east coast Canadian oil pollution

    Energy Technology Data Exchange (ETDEWEB)

    Lieske, David J. [Mount Allison University (Canada)], email: dlieske@mta.ca; Mahoney, Matthew [Environment Canada (Canada); Wilhelm, Sabina I. [Canadian Wildlife Service, Environment Canada (Canada); Weir, Laurie [Marine and Ice Services, Meteorological Service of Canada, Environment Canada (Canada); O' Hara, Patrick [Canadian Wildlife Service, Institute of Ocean Science (canada)

    2011-07-01

    This study offers an insight into three different oil spill detection schemes used in Canadian waters: visually unaided aerial surveillance, SLAR-assisted aerial surveillance, and RADARSAT-based image processing. The main purpose of this study is to compare the effectiveness of these schemes with respect to spill surveillance methodology, and to make recommendations for future planning techniques. In order to quantify the surveillance capacity of each method, flight paths had to be generated, followed by calculating oil loading. Flight paths were generated manually from images and records for the first approach, while this information was extracted from digitalized records for the second and third approaches. Results showed that SLAR technology increased the efficiency of NASP aircraft in spill detection by increasing the area surveyed and by its not having to rely on naked-eye spotting of the spills. Moreover, ISTOP widened the aircraft coverage range due to its satellite-based imagery, which can operate at night as well as in daylight.

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

    Directory of Open Access Journals (Sweden)

    Jonathan Lisein

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

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

    Science.gov (United States)

    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.

  4. Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

    Science.gov (United States)

    Wu, Qiusheng; Lane, Charles R.

    2017-07-01

    In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling-spilling-merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

  5. Aerial_Shorelines_1940_2015.shp - Dauphin Island, Alabama Shoreline Data Derived from Aerial Imagery from 1940 to 2015

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Aerial_WDL_Shorelines.zip features digitized historic shorelines for the Dauphin Island coastline from October 1940 to November 2015. This dataset contains 10 Wet...

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    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%.

  8. Demonstrative potential of multitemporal satellite imagery in documenting urban dynamics: generalisation from the Bucharest city case

    Science.gov (United States)

    Aldea, Mihaela; Petrescu, Florian; Parlow, Eberhard; Iacoboaea, Cristina; Luca, Oana; Sercaianu, Mihai; Gaman, Florian

    2016-08-01

    The main objective of this paper is to demonstrate the potential of multitemporal satellite imagery to be processed and used in documenting urban changes that took place over time, with limited resources involved and taking advantage of the opportunity to be able to use the satellite imagery available as open data. The possibilities to analyse and compare the written literature regarding the chronological evolution of a city with the patterns of Land Use/Land Cover obtained from the processing of satellite remotely sensed images of the respective scenery were investigated based upon a case study of a selected city. The extent of the prospects of using remote sensing based methods and multitemporal satellite imagery is also expressed as a result of this investigation.

  9. Aerial Photography and Imagery, Uncorrected, as part of the original impervious surface project in 1993, Published in 1989, 1:2400 (1in=200ft) scale, City of Fort Wayne.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Uncorrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Uncorrected Imagery information as...

  10. Aerial Photography and Imagery, Oblique, Digital photos taken of PA's Lake Erie shoreline and Presque Isle at an oblique angle at about 1,500-2,000' altitude., Published in 2017, Not Applicable scale, Pennsylvania Coastal Resources Management Program.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at Not Applicable scale, was produced all or in part from Uncorrected Imagery information as of 2017....

  11. Aerial Photography and Imagery, Oblique, Digital photos taken of PA's Lake Erie shoreline and Presque Isle at an oblique angle at about 1,500-2,000' altitude., Published in 2015, Not Applicable scale, Pennsylvania Coastal Resources Management Program.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at Not Applicable scale, was produced all or in part from Uncorrected Imagery information as of 2015....

  12. Aerial Photography and Imagery, Uncorrected, various years are available, including 1948, 1954, 1967, and others from the 1970s, 80s and 90s, Published in 1976, 1:24000 (1in=2000ft) scale, Brown County, WI.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Uncorrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Uncorrected Imagery information...

  13. Aerial Photography and Imagery, Oblique, Oblique by Pictometry for Eastern Half of York County, Published in 2007, 1:2400 (1in=200ft) scale, York County Government, SC.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Uncorrected Imagery information as of...

  14. Aerial Photography and Imagery, Ortho-Corrected, True Color Orthophotography for Cambridge, Hurlock, Secretary, and Vienna - 4" pixles, 2006., Published in 2006, 1:600 (1in=50ft) scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC Regional | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2006. True Color Orthophotography for Cambridge, Hurlock, Secretary, and Vienna - 4" pixles,...

  15. A review of uses of satellite imagery in monitoring mangrove forests

    Science.gov (United States)

    Rhyma Purnamasayangsukasih, P.; Norizah, K.; Ismail, Adnan A. M.; Shamsudin, I.

    2016-06-01

    Satellite image could provide much information of earth surfaces in a large scale in a short time, thus saving time. With the evolution and development of sensors providing satellite image, resolution of object captured enhanced with advance image processing techniques. In forestry, satellite image has been widely used for resources management, planning, monitoring, predicting, etc. However, the uses of satellite image are reported to be moderate and sometimes poor for mangrove forests due to homogenous species existed in salty and inundation areas. Many researches had been carried out to improve the uses of satellite imagery of either optical or radar data for mangrove forests. This paper reviews the uses of satellite imagery data in mangrove with the main focus of the literature related to mangroves monitoring.

  16. High-resolution satellite imagery is an important yet underutilized resource in conservation biology.

    Science.gov (United States)

    Boyle, Sarah A; Kennedy, Christina M; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E; de la Sancha, Noé U

    2014-01-01

    Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making.

  17. High-Resolution Satellite Imagery Is an Important yet Underutilized Resource in Conservation Biology

    Science.gov (United States)

    Boyle, Sarah A.; Kennedy, Christina M.; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E.; de la Sancha, Noé U.

    2014-01-01

    Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making. PMID:24466287

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

    Science.gov (United States)

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

    2016-03-26

    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.

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Yalong Ma

    2016-03-01

    Full Text Available 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.

  1. Aerial Photography and Imagery, Ortho-Corrected, HOGARDC has MrSID NAIP Aerial Imagery for Appling, Bleckley, Candler, Dodge, Emanuel, Evans, Jeff Davis, Johnson, Laurens, Montgomery, Tattnall, Telfair, Toombs, Treutlen, Wayne, Wheeler, and Wilcox Counties., Published in 2007, 1:4800 (1in=400ft) scale, Heart of Georgia Altamaha RDC.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  2. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Cole NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  3. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 St. Charles NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  4. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 McDonald NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  5. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Phelps NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  6. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Nodaway NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  7. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Jasper NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  8. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Franklin County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Franklin County, FL. This 1"=200' scale imagery is comprised of 24 bit natural color orthophotography with...

  9. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Scotland NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  10. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 St. Louis NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  11. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Cass NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  12. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Liberty County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Liberty County, FL. This 1"=200' scale imagery is comprised of 24 bit natural color orthophotography with...

  13. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Christian NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  14. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Franklin NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  15. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Liberty County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Liberty County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  16. Aerial Photography and Imagery, Ortho-Corrected - 2008 Digital Orthophotos - Lake County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery for Lake County, FL. This 1":100' scale imagery is comprised of natural color orthophotography with a GSD (Ground...

  17. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Calhoun County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Calhoun and Gulf Counties, FL. This 1"=200' scale imagery is comprised of natural color orthoimagery with...

  18. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Franklin County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Franklin County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  19. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Gulf County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Gulf County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  20. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Bradford County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Bradford County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  1. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Glades County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Glades County, FL. This 1":200' scale imagery is comprised of natural color orthophotography with a GSD...

  2. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Gulf County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Calhoun and Gulf Counties, FL. This 1"=200' scale imagery is comprised of natural color orthoimagery with...

  3. Aerial Photography and Imagery, Ortho-Corrected - 2008 Digital Orthophotos - HIghlands County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery for Highlands County, FL. This 1":100' scale imagery is comprised of natural color orthophotography with a GSD...

  4. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Calhoun County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Calhoun County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  5. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Union County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Union County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  6. Aerial Photography and Imagery, Ortho-Corrected - 2008 Digital Orthophotos - Glades County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital ortho imagery covering Glades and Hendry Counties, FL. This 1":200' scale imagery is comprised of natural color orthophotography...

  7. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Gentry NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  8. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Cape Giradeau NIAP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  9. Aerial Photography and Imagery, Ortho-Corrected - MO 2012 Laclede NAIP (SHP)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set contains polygons delineating the seamline boundaries of imagery acquired as part of the National Agriculture Imagery Program (NAIP), and used in the...

  10. Satellite Imagery Cadastral Features Extractions using Image Processing Algorithms: A Viable Option for Cadastral Science

    Directory of Open Access Journals (Sweden)

    Usman Babawuro

    2012-07-01

    Full Text Available Satellite images are used for feature extraction among other functions. They are used to extract linear features, like roads, etc. These linear features extractions are important operations in computer vision. Computer vision has varied applications in photogrammetric, hydrographic, cartographic and remote sensing tasks. The extraction of linear features or boundaries defining the extents of lands, land covers features are equally important in Cadastral Surveying. Cadastral Surveying is the cornerstone of any Cadastral System. A two dimensional cadastral plan is a model which represents both the cadastral and geometrical information of a two dimensional labeled Image. This paper aims at using and widening the concepts of high resolution Satellite imagery data for extracting representations of cadastral boundaries using image processing algorithms, hence minimizing the human interventions. The Satellite imagery is firstly rectified hence establishing the satellite imagery in the correct orientation and spatial location for further analysis. We, then employ the much available Satellite imagery to extract the relevant cadastral features using computer vision and image processing algorithms. We evaluate the potential of using high resolution Satellite imagery to achieve Cadastral goals of boundary detection and extraction of farmlands using image processing algorithms. This method proves effective as it minimizes the human demerits associated with the Cadastral surveying method, hence providing another perspective of achieving cadastral goals as emphasized by the UN cadastral vision. Finally, as Cadastral science continues to look to the future, this research aimed at the analysis and getting insights into the characteristics and potential role of computer vision algorithms using high resolution satellite imagery for better digital Cadastre that would provide improved socio economic development.

  11. APPLYING SATELLITE IMAGERY TO TRIAGE ASSESSMENT OF ECOSYSTEM HEALTH

    Science.gov (United States)

    Considerable evidence documents that certain changes in vegetation and soils result in irreversibly degraded rangeland ecosystems. We used Advanced Very High Resolution Radiometer (AVHRR)imagery to develop calibration patterns of change in the Normalized Difference Vegetation Ind...

  12. Aerial Photography and Imagery, Ortho-Corrected, Digital orthophographs (DOPs) were derived from black and white aerial photographs taken in the spring of 2000. The DOP scale is 1:4800 (1" = 400') rectified to 18" pixels., Published in 2000, 1:4800 (1in=400ft) scale, Manitowoc County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2000. Digital orthophographs (DOPs) were derived from black and white aerial photographs taken...

  13. A thermodynamic geography: night-time satellite imagery as a proxy measure of emergy.

    Science.gov (United States)

    Coscieme, Luca; Pulselli, Federico M; Bastianoni, Simone; Elvidge, Christopher D; Anderson, Sharolyn; Sutton, Paul C

    2014-11-01

    Night-time satellite imagery enables the measurement, visualization, and mapping of energy consumption in an area. In this paper, an index of the "sum of lights" as observed by night-time satellite imagery within national boundaries is compared with the emergy of the nations. Emergy is a measure of the solar energy equivalent used, directly or indirectly, to support the processes that characterize the economic activity in a country. Emergy has renewable and non-renewable components. Our results show that the non-renewable component of national emergy use is positively correlated with night-time satellite imagery. This relationship can be used to produce emergy density maps which enable the incorporation of spatially explicit representations of emergy in geographic information systems. The region of Abruzzo (Italy) is used to demonstrate this relationship as a spatially disaggregate case.

  14. EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    S. Wittke

    2017-05-01

    Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

  15. Towards High-Definition 3D Urban Mapping: Road Feature-Based Registration of Mobile Mapping Systems and Aerial Imagery

    Directory of Open Access Journals (Sweden)

    Mahdi Javanmardi

    2017-09-01

    Full Text Available Various applications have utilized a mobile mapping system (MMS as the main 3D urban remote sensing platform. However, the accuracy and precision of the three-dimensional data acquired by an MMS is highly dependent on the performance of the vehicle’s self-localization, which is generally performed by high-end global navigation satellite system (GNSS/inertial measurement unit (IMU integration. However, GNSS/IMU positioning quality degrades significantly in dense urban areas with high-rise buildings, which block and reflect the satellite signals. Traditional landmark updating methods, which improve MMS accuracy by measuring ground control points (GCPs and manually identifying those points in the data, are both labor-intensive and time-consuming. In this paper, we propose a novel and comprehensive framework for automatically georeferencing MMS data by capitalizing on road features extracted from high-resolution aerial surveillance data. The proposed framework has three key steps: (1 extracting road features from the MMS and aerial data; (2 obtaining Gaussian mixture models from the extracted aerial road features; and (3 performing registration of the MMS data to the aerial map using a dynamic sliding window and the normal distribution transform (NDT. The accuracy of the proposed framework is verified using field data, demonstrating that it is a reliable solution for high-precision urban mapping.

  16. Aerial Photography and Imagery, Uncorrected, Scanned imagery dating back to 1944. The data is not always complete for all areas. The years were also not consistently flown., Published in 2003, 1:63360 (1in=1mile) scale, City of Emporia/Lyon County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Uncorrected dataset, published at 1:63360 (1in=1mile) scale, was produced all or in part from Uncorrected Imagery information as...

  17. Aerial Photography and Imagery, Ortho-Corrected, We have new imagery from Pictometry's AccuPlus flown in March 2010 and to be delivered in October 2010., Published in 2010, 1:600 (1in=50ft) scale, Augusta-Richmond County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2010. We have new imagery from Pictometry's AccuPlus flown in March 2010 and to be delivered in...

  18. Aerial Photography and Imagery, Ortho-Corrected, This dataset contains imagery of Prince George's County in RGB format. The primary goal was to acquire Countywide Digital Orthoimagery at 6" ground pixel resolution., Published in 2009, 1:1200 (1in=100ft) scale, Maryland National Capital Park and Planning Commission.

    Data.gov (United States)

    NSGIC Non-Profit | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. This dataset contains imagery of Prince George's County in RGB format. The primary goal...

  19. Aerial Photography and Imagery, Ortho-Corrected, This imagery was acquired through a Federal Grant with Pictometry International. The resolution is 6" in more densly populated areas and 1' in the other areas., Published in 2011, Not Applicable scale, Chippewa County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2011. This imagery was acquired through a Federal Grant with Pictometry International. The...

  20. Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

    Science.gov (United States)

    Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

    2016-12-16

    Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

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

    Science.gov (United States)

    Fernandez, Paz; Whitworth, Malcolm

    2016-10-01

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

  2. Satellite Imagery Measures of the Astronomically Aligned Megaliths at Nabta Playa

    Science.gov (United States)

    Brophy, T. G.; Rosen, P. A.

    2003-12-01

    Astronomically aligned megalithic structures described in field reports (Wendorf, F. and Malville, J.M., The Megalith Alignments, pp.489-502 in Holocene Settlement of the Egyptian Sahara, Vol.I, 2001.) are identified in newly acquired georectified 60 cm panchromatic satellite imagery of Nabta Playa, southern Egypt. The satellite images allow refinement, often significant, of the reported locations of the megaliths. The report that the primary megalithic alignment was constructed to point to the bright star Sirius, circa 4,820 BC, is reconsidered in light of the satellite data, new field data, radiocarbon, lithostratigraphic and geochronologic data, and the playa sedimentation history. Other possible archaeoastronomical interpretations are considered for that alignment, including the three stars of Orion's Belt circa 6,270 BC that are also implicated in the small Nabta Playa `calendar circle'. Other new features apparent in the satellite imagery are also considered.

  3. Speckle filtering in satellite SAR change detection imagery

    NARCIS (Netherlands)

    Dekker, R.J.

    1998-01-01

    Repeat-pass Synthetic Aperture Radar (SAR) imagery is useful for change detection. A disadvantage of SAR is the system-inherent speckle noise. This can be reduced by filtering. Various filter types and methods are described in the literature, but not one fits the speckle noise in change detection

  4. INTERGRATION OF LiDAR DATA WITH AERIAL IMAGERY FOR ESTIMATING ROOFTOP SOLAR PHOTOVOLTAIC POTENTIALS IN CITY OF CAPE TOWN

    Directory of Open Access Journals (Sweden)

    A. K. Adeleke

    2016-06-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  7. Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

    Science.gov (United States)

    AlShamsi, Meera R.

    2016-10-01

    Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

  8. Monitoring agricultural crop growth: comparison of high spatial-temporal satellite imagery versus UAV-based imaging spectrometer time series measurements

    Science.gov (United States)

    Mucher, Sander; Roerink, Gerbert; Franke, Jappe; Suomalainen, Juha; Kooistra, Lammert

    2014-05-01

    In 2012, the Dutch National Satellite Data Portal (NSD) was launched as a preparation to the launch of the European SENTINEL satellites in the framework of the Copernicus Programme. At the same time the Unmanned Aerial Remote Sensing Facility (UARSF: www.wageningenUR.nl/uarsf) has been established as research facility at Wageningen University and Research Centre. The NSD became available for the development of services and advice through an investment from the Dutch government in collaboration with the Netherlands Space Office (NSO) in order to develop new services for precision agriculture. The NSD contains Formosat, Radarsat as well as DMC satellite imagery. The processing of the DMC imagery resulted in the Greenmonitor service (www.groenmonitor.nl). The Greenmonitor is an unique product that covers the Netherlands with a high spatial and temporal resolution. The Greenmonitor is now being exploited for various applications, amongst others crop identification, crop phenology, and identification of management activities. The UARSF of Wageningen UR has three objectives: 1) to develop innovation in the field of remote sensing science using Unmanned Aerial Vehicles (UAV) by providing a platform for dedicated and high-quality experiments; 2) to support high quality UAV services by providing calibration facilities and disseminating processing procedures to the UAV user community; 3) to promote and test the use of UAV in a broad range of application fields such as precision agriculture and habitat monitoring. Through this coincidence of new developments the goal of our study was to compare the information for the measurements of spatial variation in crops and soils as derived from high spatial-temporal satellite imagery from the national data portal compared to the exploitation of UAVs, in our case an Altura octocopter with a hyperspectral camera. As such, the focus is on the applications in precision agriculture. Both primary producers and chain partners and service

  9. Reconstruction of an infrared band of meteorological satellite imagery with abductive networks

    Science.gov (United States)

    Singer, Harvey A.; Cockayne, John E.; Versteegen, Peter L.

    1995-01-01

    As the current fleet of meteorological satellites age, the accuracy of the imagery sensed on a spectral channel of the image scanning system is continually and progressively degraded by noise. In time, that data may even become unusable. We describe a novel approach to the reconstruction of the noisy satellite imagery according to empirical functional relationships that tie the spectral channels together. Abductive networks are applied to automatically learn the empirical functional relationships between the data sensed on the other spectral channels to calculate the data that should have been sensed on the corrupted channel. Using imagery unaffected by noise, it is demonstrated that abductive networks correctly predict the noise-free observed data.

  10. Identifying Hail Signatures in Satellite Imagery from the 9-10 August 2011 Severe Weather Event

    Science.gov (United States)

    Dryden, Rachel L.; Molthan, Andrew L.; Cole, Tony A.; Bell, Jordan R.

    2014-01-01

    Hail scars are identifiable in MODIS satellite imagery based on NDVI change, which was dominantly negative. Hail damage spatially correlates with SPC hail reports and MESH. This study developed a proxy for quantifying crop loss at varying thresholds to address the gap between SPC damage estimates and insurance payouts.

  11. Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

    Science.gov (United States)

    Jasinski, Michael F.; Crago, Richard

    1994-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  12. Detection of ZY-3 Satellite Platform Jitter Using Multi-spectral Imagery

    Directory of Open Access Journals (Sweden)

    ZHU Ying

    2015-04-01

    Full Text Available Satellite platform jitter is one of the factors that affect the quality of high resolution imagery, which can cause image blur and internal distortion. Taking ZiYuan-3 (ZY-3 multi-spectral camera as a prototype, this paper proposes a satellite platform jitter detection method by utilizing multi-spectral imagery. First, imaging characteristics of multispectral camera and the main factors affecting band-to-band registration error are introduced. Then the regularity of registration error caused by platform jitter is analyzed by theoretical derivation and simulation. Meanwhile, the platform jitter detection method based on high accuracy dense points matching is presented. Finally, the experiments were conducted by using ZY-3 multi-spectral imagery captured in different time. The result indicates that ZY-3 has a periodic platform jitter about 0.6 Hz in the imaging period of test data, and the jitter amplitude across track is greater than that along track, which causes periodic band-to-band registration error with the same frequency. The result shows the possibility of the improvement in geometric processing accuracy for ZY-3 imagery products and provides an important reference for satellite platform jitter source analysis and satellite platform design optimization.

  13. A data mining approach for sharpening satellite thermal imagery over land

    Science.gov (United States)

    Thermal infrared (TIR) imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes which are at significant...

  14. Fully automated procedure for ship detection using optical satellite imagery

    Science.gov (United States)

    Corbane, C.; Pecoul, E.; Demagistri, L.; Petit, M.

    2009-01-01

    Ship detection from remote sensing imagery is a crucial application for maritime security which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. In the framework of a European integrated project GMES-Security/LIMES, we developed an operational ship detection algorithm using high spatial resolution optical imagery to complement existing regulations, in particular the fishing control system. The automatic detection model is based on statistical methods, mathematical morphology and other signal processing techniques such as the wavelet analysis and Radon transform. This paper presents current progress made on the detection model and describes the prototype designed to classify small targets. The prototype was tested on panchromatic SPOT 5 imagery taking into account the environmental and fishing context in French Guiana. In terms of automatic detection of small ship targets, the proposed algorithm performs well. Its advantages are manifold: it is simple and robust, but most of all, it is efficient and fast, which is a crucial point in performance evaluation of advanced ship detection strategies.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Huawei Wan

    2014-01-01

    Full Text Available 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.

  17. Phase 2 Final Report. IAEA Safeguards: Implementation blueprint of commercial satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Christer [SSC Satellitbild AB, Solna (Sweden)

    2000-01-01

    This document - IAEA Safeguards: Implementation Blueprint of Commercial Satellite Imagery - constitutes the second report from SSC Satellitbild giving a structured view and solid guidelines on how to proceed with a conceivable implementation of satellite imagery to support Safeguards activities of the Agency. This Phase 2 report presents a large number of concrete recommendations regarding suggested management issues, work organisation, imagery purchasing and team building. The study has also resulted in several lists of actions and preliminary project plans with GANT schedules concerning training, hardware and software, as well as for the initial pilot studies. In both the Phase 1 and Phase 2 studies it is confirmed that the proposed concept of a relatively small Imagery Unit using high-resolution data will be a sound and feasible undertaking. Such a unit capable of performing advanced image processing as a tool for various safeguard tasks will give the Agency an effective instrument for reference, monitoring, verification, and detection of declared and undeclared activities. The total cost for implementing commercial satellite imagery at the Department for Safeguards, as simulated in these studies, is approximately MUSD 1,5 per year. This cost is founded on an activity scenario with a staff of 4 experts working in an IAEA Imagery Unit with a workload of three dossiers or issues per week. The imagery unit is built around an advanced PC image processing system capable of handling several hundreds of pre-processed images per year. Alternatively a Reduced Scenario with a staff of 3 would need a budget of approximately MUSD 0,9 per year, whereas an Enhanced Imagery Unit including 5 experts and a considerably enlarged capacity would cost MUSD 1,7 per year. The Imagery Unit should be organised so it clearly reflects the objectives and role as set by the Member States and the management of the Agency. We recommend the Imagery Unit to be organised into four main work

  18. Cedar Breaks National Monument Vegetation Mapping Project - True Color Aerial Imagery

    Data.gov (United States)

    National Park Service, Department of the Interior — Color aerial photography was collected, in stereo with 60 percent forward overlap and 40 percent side overlap on 6-27-02. The flight height was 20,000 feet above...

  19. Visualization and unsupervised classification of changes in multispectral satellite imagery

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2006-01-01

    The statistical techniques of multivariate alteration detection, minimum/maximum autocorrelation factors transformation, expectation maximization and probabilistic label relaxation are combined in a unified scheme to visualize and to classify changes in multispectral satellite data. The methods...

  20. Unsupervised classification of changes in multispectral satellite imagery

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2004-01-01

    The statistical techniques of multivariate alteration detection, maximum autocorrelation factor transformation, expectation maximization, fuzzy maximum likelihood estimation and probabilistic label relaxation are combined in a unified scheme to classify changes in multispectral satellite data...

  1. Visualization and unsupervised classification of changes in multispectral satellite imagery

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2006-01-01

    The statistical techniques of multivariate alteration detection, minimum/maximum autocorrelation factors transformation, expectation maximization and probabilistic label relaxation are combined in a unified scheme to visualize and to classify changes in multispectral satellite data. The methods...

  2. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Suwannee County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — The dataset consists of tiled orthogonal imagery produced from nadir images captured by Pictometry International during the period of December 30th, 2012 to March...

  3. Hurricane Ophelia Aerial Photography: High-Resolution Imagery of the North Carolina Coast After Landfall

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the North Carolina coast after Hurricane Ophelia made landfall. The regions photographed range from Hubert, North Carolina to...

  4. Coastal Bend Texas Benthic Habitat Mapping Reprocessed DOQQ Aerial Imagery (NODC Accession 0086051)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In 2006 and 2007 the NOAA Coastal Services Center purchased services to reprocess existing digital multi-spectral imagery (ADS-40) and create digital benthic habitat...

  5. Aerial Photography and Imagery, Ortho-Corrected - 2012 Digital Orthophotos - Okeechobee County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This file references a single orthogonal imagery tile produced from nadir images captured by Pictometry International during the period of January 12th, 2011 to...

  6. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Okaloosa County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This file references a single orthogonal imagery tile produced from nadir images captured by Pictometry International during the period of December 21st, 2012 to...

  7. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Hernando County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  8. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Hernando County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  9. Hurricane Wilma Aerial Photography: High-Resolution Imagery of the Florida Coast After Landfall

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the Florida coast after Hurricane Wilma made landfall. The regions photographed range from Key West to Sixmile Bend, Florida....

  10. Aerial Photography and Imagery, Ortho-Corrected - 2012 Digital Orthophotos - Monroe County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital orthoimagery covering Monroe County, FL. This 1"=100' scale imagery is comprised of natural color orthoimagery with a GSD (Ground...

  11. Aerial Photography and Imagery, Ortho-Corrected - 2011 Digital Orthophotos - Highlands County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital orthoimagery covering Highlands County, FL. This 1"=100' scale imagery is comprised of natural color orthoimagery with a GSD...

  12. Aerial Photography and Imagery, Ortho-Corrected - 2011 Digital Orthophotos - Hendry County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital orthoimagery covering Hendry County, FL. This 1"=200' scale imagery is comprised of natural color orthoimagery with a GSD (Ground...

  13. Aerial Photography and Imagery, Ortho-Corrected - 2012 Digital Orthophotos - Monroe County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This metadata describes the digital orthoimagery covering the area of the Everglades in Monroe County, FL as defined by the FL DOR. This 1"=100' scale imagery is...

  14. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Citrus County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  15. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Levy County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  16. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Marion County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  17. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Marion County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  18. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Pasco County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  19. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Lake County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  20. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Pasco County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  1. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Sumter County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  2. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Citrus County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  3. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Sumter County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  4. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Levy County

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  5. Hurricane Jeanne Aerial Photography: High-Resolution Imagery of the Atlantic Coast of Florida After Landfall

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is of the Atlantic coast of Florida after Hurricane Jeanne made landfall. The regions photographed range along a 100-mile stretch...

  6. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Suwannee County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — The dataset consists of tiled orthogonal imagery produced from nadir images captured by Pictometry International during the period of December 30th, 2012 to March...

  7. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Okaloosa County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This file references a single orthogonal imagery tile produced from nadir images captured by Pictometry International during the period of December 21st, 2012 to...

  8. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Lake County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set is one component of a digital orthophoto imagery (DOI) coverage over the Southwest Florida Water Management District (SWFWMD) North District Area, for...

  9. Epipolar Resampling of Cross-Track Pushbroom Satellite Imagery Using the Rigorous Sensor Model.

    Science.gov (United States)

    Jannati, Mojtaba; Valadan Zoej, Mohammad Javad; Mokhtarzade, Mehdi

    2017-01-11

    Epipolar resampling aims to eliminate the vertical parallax of stereo images. Due to the dynamic nature of the exterior orientation parameters of linear pushbroom satellite imagery and the complexity of reconstructing the epipolar geometry using rigorous sensor models, so far, no epipolar resampling approach has been proposed based on these models. In this paper for the first time it is shown that the orientation of the instantaneous baseline (IB) of conjugate image points (CIPs) in the linear pushbroom satellite imagery can be modeled with high precision in terms of the rows- and the columns-number of CIPs. Taking advantage of this feature, a novel approach is then presented for epipolar resampling of cross-track linear pushbroom satellite imagery. The proposed method is based on the rigorous sensor model. As the instantaneous position of sensors remains fixed, the digital elevation model of the area of interest is not required in the resampling process. Experimental results obtained from two pairs of SPOT and one pair of RapidEye stereo imagery with different terrain conditions shows that the proposed epipolar resampling approach benefits from a superior accuracy, as the remained vertical parallaxes of all CIPs in the normalized images are close to zero.

  10. Epipolar Resampling of Cross-Track Pushbroom Satellite Imagery Using the Rigorous Sensor Model

    Directory of Open Access Journals (Sweden)

    Mojtaba Jannati

    2017-01-01

    Full Text Available Epipolar resampling aims to eliminate the vertical parallax of stereo images. Due to the dynamic nature of the exterior orientation parameters of linear pushbroom satellite imagery and the complexity of reconstructing the epipolar geometry using rigorous sensor models, so far, no epipolar resampling approach has been proposed based on these models. In this paper for the first time it is shown that the orientation of the instantaneous baseline (IB of conjugate image points (CIPs in the linear pushbroom satellite imagery can be modeled with high precision in terms of the rows- and the columns-number of CIPs. Taking advantage of this feature, a novel approach is then presented for epipolar resampling of cross-track linear pushbroom satellite imagery. The proposed method is based on the rigorous sensor model. As the instantaneous position of sensors remains fixed, the digital elevation model of the area of interest is not required in the resampling process. Experimental results obtained from two pairs of SPOT and one pair of RapidEye stereo imagery with different terrain conditions shows that the proposed epipolar resampling approach benefits from a superior accuracy, as the remained vertical parallaxes of all CIPs in the normalized images are close to zero.

  11. Study of the Nevada Test Site using Landsat satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Zimmerman, P.D. [Georgetown Univ., Washington, DC (United States). Center for Strategic and International Studies

    1993-07-01

    In the period covered by the purchase order CSIS has obtained one Landsat image and determined that two images previously supplied to the principal investigator under a subcontract with George Washington University were inherently defective. We have negotiated with EOSAT over the reprocessing of those scenes and anticipate final delivery within the next few weeks. A critical early purchase during the subcontract period was of an EXABYTE tape drive, Adaptec SCSI interface, and the appropriate software with which to read Landsat images at CSIS. This gives us the capability of reading and manipulating imagery in house without reliance on outside services which have not proven satisfactory. In addition to obtaining imagery for the study, we have also performed considerable analytic work on the newly and previously purchased images. A technique developed under an earlier subcontract for identifying underground nuclear tests at Pahute Mesa has been significantly refined, and similar techniques were applied to the summit of Rainier Mesa and to the Yucca Flats area. An entirely new technique for enhancing the spectral signatures of different regions of NTS was recently developed, and appears to have great promise of success.

  12. Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery

    Science.gov (United States)

    Kit, Oleksandr; Lüdeke, Matthias

    2013-09-01

    This paper presents an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery. It relies upon a lacunarity-based slum detection algorithm, combined with Canny- and LSD-based imagery pre-processing routines. This method outputs plausible and spatially explicit slum locations for the whole urban agglomeration of Hyderabad in years 2003 and 2010. The results indicate a considerable growth of area occupied by slums between these years and allow identification of trends in slum development in this urban agglomeration.

  13. Satellite orientation and position for geometric correction of scanner imagery.

    Science.gov (United States)

    Salamonowicz, P.H.

    1986-01-01

    The USGS Mini Image Processing System currently relies on a polynomial method for geometric correction of Landsat multispectral scanner (MSS) data. A large number of ground control points are required because polynomials do not model the sources of error. In order to reduce the number of necessary points, a set of mathematical equations modeling the Landsat satellite motions and MSS scanner has been derived and programmed. A best fit to the equations is obtained by using a least-squares technique that permits computation of the satellite orientation and position parameters based on only a few control points.-from Author

  14. a Detailed Study about Digital Surface Model Generation Using High Resolution Satellite Stereo Imagery

    Science.gov (United States)

    Gong, K.; Fritsch, D.

    2016-06-01

    Photogrammetry is currently in a process of renaissance, caused by the development of dense stereo matching algorithms to provide very dense Digital Surface Models (DSMs). Moreover, satellite sensors have improved to provide sub-meter or even better Ground Sampling Distances (GSD) in recent years. Therefore, the generation of DSM from spaceborne stereo imagery becomes a vivid research area. This paper presents a comprehensive study about the DSM generation of high resolution satellite data and proposes several methods to implement the approach. The bias-compensated Rational Polynomial Coefficients (RPCs) Bundle Block Adjustment is applied to image orientation and the rectification of stereo scenes is realized based on the Project-Trajectory-Based Epipolarity (PTE) Model. Very dense DSMs are generated from WorldView-2 satellite stereo imagery using the dense image matching module of the C/C++ library LibTsgm. We carry out various tests to evaluate the quality of generated DSMs regarding robustness and precision. The results have verified that the presented pipeline of DSM generation from high resolution satellite imagery is applicable, reliable and very promising.

  15. Characterization of surface oil thickness distribution patterns observed during the Deepwater Horizon (MC-252) oil spill with aerial and satellite remote sensing.

    Science.gov (United States)

    Svejkovsky, Jan; Hess, Mark; Muskat, Judd; Nedwed, Tim J; McCall, Jenifer; Garcia, Oscar

    2016-09-15

    Knowledge of the spatial distribution of oil thickness patterns within an on-water spill is of obvious importance for immediate spill response activities as well as for subsequent evaluation of the spill impacts. For long-lasting continuous spills like the 2010 3-month Deepwater Horizon (DWH) event in the Gulf of Mexico, it is also important to identify changes in the dominant oil features through time. This study utilized very high resolution (≤5m) aerial and satellite imagery acquired during the DWH spill to evaluate the shape, size and thickness of surface oil features that dominated the DWH slick. Results indicate that outside of the immediate spill source region, oil distributions did not encompass a broad, varied range of thicknesses. Instead, the oil separated into four primary, distinct characterizations: 1) invisible surface films detectable only with Synthetic Aperture Radar imaging because of the decreased surface backscatter, 2) thicker sheen & rainbow areas (oil (>1mm) that were consistently hundreds of meters long but most commonly only 10-50m wide. Where present within the slick footprint, each of the three distinct visible oil thickness classes maintained its shape characteristics both spatially (at different distances from the source and in different portions of the slick), and temporally (from mid-May through July 2010). The region over the source site tended to contain a more continuous range of oil thicknesses, however, our results indicate that the continuous injection of subsurface dispersants starting in late May significantly altered (lowered) that range. In addition to characterizing the oil thickness distribution patterns through the timeline of one of the world's largest oil spills, this paper also details the extension of using high resolution aerial imagery to calibrate medium resolution satellite data sources such as USA's Thematic Mapper (30m) to provide larger-scale spatial views of major spills, and discusses implications for

  16. A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery

    Directory of Open Access Journals (Sweden)

    Kaveh Shahi

    2015-06-01

    Full Text Available This research develops a spectral index to automatically extract asphalt road networks named road extraction index (REI. This index uses WorldView-2 (WV-2 imagery, which has high spatial resolution and is multispectral. To determine the best bands for WV-2, field spectral data using a field spectroradiometer were collected. These data were then analyzed statistically. The bands were selected through the methodology of stepwise discriminant analysis. The appropriate WV-2 bands were distinguished from one another as per significant wavelengths. The proposed index is based on this classification. By applying REI to WV-2 imagery, we can extract asphalt roads accurately. Results demonstrate that REI is automated, transferable, and efficient in asphalt road extraction from high-resolution satellite imagery.

  17. Aerial video and ladar imagery fusion for persistent urban vehicle tracking

    Science.gov (United States)

    Cho, Peter; Greisokh, Daniel; Anderson, Hyrum; Sandland, Jessica; Knowlton, Robert

    2007-04-01

    We assess the impact of supplementing two-dimensional video with three-dimensional geometry for persistent vehicle tracking in complex urban environments. Using recent video data collected over a city with minimal terrain content, we first quantify erroneous sources of automated tracking termination and identify those which could be ameliorated by detailed height maps. They include imagery misregistration, roadway occlusion and vehicle deceleration. We next develop mathematical models to analyze the tracking value of spatial geometry knowledge in general and high resolution ladar imagery in particular. Simulation results demonstrate how 3D information could eliminate large numbers of false tracks passing through impenetrable structures. Spurious track rejection would permit Kalman filter coasting times to be significantly increased. Track lifetimes for vehicles occluded by trees and buildings as well as for cars slowing down at corners and intersections could consequently be prolonged. We find high resolution 3D imagery can ideally yield an 83% reduction in the rate of automated tracking failure.

  18. The Application Achievements And Perspective Of CBERS Series Satellite Imagery

    Institute of Scientific and Technical Information of China (English)

    Li Xingchao; Qi Xueyong; Lu Yilin

    2009-01-01

    @@ Since the first China-Brazil Earth Resources Satellite (CBERS-1),launched in 1999,the CBERS data has been applied in many fields extensively.Remarkable social and economic benefits have been achieved.This article presents the application achievements during the past nine years,and gives a perspective for the future.All these applications demonstrate that the CBERS data has been an important data source for resources investigation and monitoring.

  19. Image Dodging Algorithm for GF-1 Satellite WFV Imagery

    Directory of Open Access Journals (Sweden)

    HAN Jie

    2016-12-01

    Full Text Available Image dodging method is one of the important processes that determines whether the mosaicking image can be used for remote sensing quantitative application. GF-1 satellite is the first satellite in CHEOS (Chinese high-resolution earth observation system. WFV multispectral sensor is one of the instruments onboard GF-1 satellite which consist of four cameras to mosaic imaging. According to the characteristics of WFV sensor, this paper proposes an image dodging algorithm based on cross/inter-radiometric calibration method. First, the traditional cross calibration method is applied to obtain the calibration coefficients of one WFV camera. Then statistical analysis and simulation methods are adopted to build the correlation models of DN and TOA (top of atmosphere radiances between adjacent cameras. The proposed method can not only accomplish the radiation performance transfer, but also can fulfill the image dodging. The experimental results show the cross/inter-radiometric calibration coefficients in this paper can effectively eliminate the radiation inconsistency problem of the adjacent camera image which realizes the image dodging. So our proposed dodging method can provide an important reference for other similar sensor in future.

  20. A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery

    Directory of Open Access Journals (Sweden)

    Philippe Lejeune

    2013-11-01

    Full Text Available The recent development of operational small unmanned aerial systems (UASs opens the door for their extensive use in forest mapping, as both the spatial and temporal resolution of UAS imagery better suit local-scale investigation than traditional remote sensing tools. This article focuses on the use of combined photogrammetry and “Structure from Motion” approaches in order to model the forest canopy surface from low-altitude aerial images. An original workflow, using the open source and free photogrammetric toolbox, MICMAC (acronym for Multi Image Matches for Auto Correlation Methods, was set up to create a digital canopy surface model of deciduous stands. In combination with a co-registered light detection and ranging (LiDAR digital terrain model, the elevation of vegetation was determined, and the resulting hybrid photo/LiDAR canopy height model was compared to data from a LiDAR canopy height model and from forest inventory data. Linear regressions predicting dominant height and individual height from plot metrics and crown metrics showed that the photogrammetric canopy height model was of good quality for deciduous stands. Although photogrammetric reconstruction significantly smooths the canopy surface, the use of this workflow has the potential to take full advantage of the flexible revisit period of drones in order to refresh the LiDAR canopy height model and to collect dense multitemporal canopy height series.

  1. Seasonal surface velocities of a Himalayan glacier derived by automated correlation of unmanned aerial vehicle imagery

    NARCIS (Netherlands)

    Kraaijenbrink, Philip; Meijer, Sander W.; Shea, Joseph M.; Pellicciotti, Francesca; De Jong, Steven M.; Immerzeel, Walter W.

    2016-01-01

    Debris-covered glaciers play an important role in the high-altitude water cycle in the Himalaya, yet their dynamics are poorly understood, partly because of the difficult fieldwork conditions. In this study we therefore deploy an unmanned aerial vehicle (UAV) three times (May 2013, October 2013 and

  2. Seasonal surface velocities of a Himalayan glacier derived by automated correlation of unmanned aerial vehicle imagery

    NARCIS (Netherlands)

    Kraaijenbrink, Philip; Meijer, Sander W.; Shea, Joseph M.; Pellicciotti, Francesca; De Jong, Steven M.|info:eu-repo/dai/nl/120221306; Immerzeel, Walter W.|info:eu-repo/dai/nl/290472113

    2016-01-01

    Debris-covered glaciers play an important role in the high-altitude water cycle in the Himalaya, yet their dynamics are poorly understood, partly because of the difficult fieldwork conditions. In this study we therefore deploy an unmanned aerial vehicle (UAV) three times (May 2013, October 2013 and

  3. Detecting inter-annual variability in the phenological characteristics of southern Africa’s vegetation using satellite imagery

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2011-01-01

    Full Text Available Vegetation phenology refers to the timing of seasonal biological events (for example, bud burst, leaf unfolding, vegetation growth and leaf senescence) and biotic and abiotic forces that control these. Daily, coarse-resolution satellite imagery...

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

    Science.gov (United States)

    Savelyev, Alexander; Sugumaran, Ramanathan

    2008-08-25

    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 pixelto-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.

  5. A geographic investigation of hazards, disasters and recovery using satellite imagery

    Science.gov (United States)

    Keys-Mathews, Lisa D.

    Disaster recovery is depicted on the landscape by change through time. Given the classic uses of remote sensing for detecting change, this dissertation assessed the applicability of remote sensing image analysis to the study of long-term recovery from disasters. Because recovery is complex and dynamic a framework was that established that divided the recovery landscape into three components: the built, relief, and natural environments. Four study sites were selected for this research representing three types of hazard events (earthquakes, tsunami and hurricane), three climatic environments (tropical, dry and humid subtropical), and four cultures (Iran, Indonesia, Peru and the United States). The four disasters occurred between 2001 and 2005 with each a catastrophic event. To begin the research, a list of diagnostic features of recovery was created through field observations, reconnaissance reports, descriptions of disaster recovery case studies, and current literature. These features were then documented in the satellite imagery as examples of their portrayal on the landscape. Second, elements of each environment (built, relief, and natural) were explored through application of digital image processing techniques including: principal components analysis, texture analysis, normalized differenced vegetation index, and digital image classification. Each of these techniques was applied to the imagery with the final results being a digital analysis through time. Finally, the analysis was integrated to determine if differential recovery was visible through the analysis of satellite imagery. This neighborhood scale investigation compared satellite imagery findings to a rapid visual assessment in Gulfport and synthesized the findings toward an understanding of differential recovery. This dissertation determined that satellite imagery and remote sensing techniques supported by fieldwork are appropriate and valuable tools in the study of disaster recovery. Features and

  6. Identifying Hail Signatures in Satellite Imagery from the 9-10 August 2011 Severe Weather Event

    Science.gov (United States)

    Dryden, Rachel L.; Molthan, Andrew L.; Cole, Tony A.; Bell, Jordan

    2014-01-01

    Severe thunderstorms can produce large hail that causes property damage, livestock fatalities, and crop failure. However, detailed storm surveys of hail damage conducted by the National Weather Service (NWS) are not required. Current gaps also exist between Storm Prediction Center (SPC) hail damage estimates and crop-insurance payouts. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra and Aqua satellites can be used to support NWS damage assessments, particularly to crops during the growing season. The two-day severe weather event across western Nebraska and central Kansas during 9-10 August 2011 offers a case study for investigating hail damage signatures by examining changes in Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery. By analyzing hail damage swaths in satellite imagery, potential economic losses due to crop damage can be quantified and further improve the estimation of weather impacts on agriculture without significantly increasing manpower requirements.

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

    Science.gov (United States)

    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.

  8. Progress of research to identify rotating thunderstorms using satellite imagery

    Science.gov (United States)

    Anderson, Charles E.

    1988-01-01

    The possibility of detecting potentially tornadic thunderstorm cells from geosynchronous satelite imagery is determined. During the life of the contract, we examined eight tornado outbreak cases which had a total of 124 individual thunderstorm cells, 37 of which were tornadic.These 37 cells produced a total of 119 tornadoes. The outflow characteristics of all the cells were measured. Through the use of a 2-D flow field model, we were able to simulate the downstream developmemt of an anvil cloud plume which was emitted by the storm updraft at or near the tropopause. We used two parameters to characterize the anvil plume behavior: its speed of downstream propagation (U max) and the clockwise deviation of the centerline of the anvil plume from the storm relative ambient wind at the anvil plume outflow level (MDA). U max was the maximum U-component of the anvil wind parameter required to successfully maintain an envelope of translating particles at the tip of the expanding anvil cloud. MDA was the measured deviation angle acquired from McIDAS, between the storm relative ambient wind direction and the storm relative anvil plume outflow direction; tha latter being manipulated by controlling a tangential wind component to force the envelope of particles to maintain their position of surrounding the expanding outflow cloud.

  9. Needs for registration and rectification of satellite imagery for land use and land cover and hydrologic applications

    Science.gov (United States)

    Gaydos, L.

    1982-01-01

    The use of satellite imagery and data for registration of land use, land cover and hydrology was discussed. Maps and aggregations are made from existing the data in concert with other data in a geographic information system. Basic needs for registration and rectification of satellite imagery related to specifying, reformatting, and overlaying the data are noted. It is found that the data are sufficient for users who must expand much effort in registering data.

  10. Geospatial Information from Satellite Imagery for Geovisualisation of Smart Cities in India

    Science.gov (United States)

    Mohan, M.

    2016-06-01

    In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

  11. Commercial Imagery Satellite Threat: How Can U.S. Forces Protect Themselves?

    Science.gov (United States)

    2006-05-31

    10 Joint Chiefs of Staff, Joint Warfare of the Armed Forces of the United States, Appendix B. 11 Laurence Nardon, "The Dilemma of...January 2004]. Nardon, Laurence . "The Dilemma of Satellite Imagery Control." Military Technology, July 2002, 37-46. National Defense Panel...34 Fact Sheet. Washington DC: White House, 13 May 2003. <http://www.au.af.mil/au/awc/awcgate/space/ 2003remotesensing.htm> [3 December 2003]. Rees

  12. GEOSPATIAL INFORMATION FROM SATELLITE IMAGERY FOR GEOVISUALISATION OF SMART CITIES IN INDIA

    Directory of Open Access Journals (Sweden)

    M. Mohan

    2016-06-01

    Full Text Available In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

  13. Estimating Monthly Rainfall from Geostationary Satellite Imagery Over Amazonia, Brazil.

    Science.gov (United States)

    Cutrim, Elen Maria Camara

    The infrared regression and the grid-history satellite rainfall estimating techniques were utilized to estimate monthly rainfall in Amazonia during one month of the rainy season (March, 1980) and one month of the dry season (September, 1980). The estimates were based on 3-hourly SMS-II infrared and visible images. Three sets of coefficients for the grid history method (Marajo, Arabian Sea, and GATE) were used to estimate rainfall. The estimated rain was compared with gauge measurements over the region. The infrared regression technique overestimated by a factor of 1.5. The Marajo coefficients yielded the best estimate, especially for eastern Amazonia. In the wet month Marajo coefficients overestimated rain by 10% and in the dry month by 70%. The Arabian Sea coefficients overestimated rain and the GATE coefficients slightly underestimated rain for Amazonia. Two maps of monthly rainfall over Amazonia were constructed for March and September, 1980, combining the ground station and satellite inferred rainfall of the grid history method using the Marajo coefficients. The satellite observations and ground data were mutually compatible and were contourable on these final, composite maps. Monthly rainfall was found to be much more inhomogeneous than previously reported. In March there was a belt of high precipitation trending southwest, with higher values and sharpest gradients in the coastal area. The upper Amazon was also an area of high precipitation, both north and south of the equator. In Roraima rainfall decreased drastically to the north. In September, the area of highest precipitation was the northwestern part of Amazonas State (northern hemisphere). Rainfall elsewhere was very localized and in northeastern Amazonia varied from 0 to 150 mm. Even though the grid history method presented better results for estimating rainfall over Amazonia, the IR model could be utilized more efficiently and economically on an operational basis if the calibration were properly made

  14. Modelling tick abundance using machine learning techniques and satellite imagery

    DEFF Research Database (Denmark)

    Kjær, Lene Jung; Korslund, L.; Kjelland, V.

    satellite images to run Boosted Regression Tree machine learning algorithms to predict overall distribution (presence/absence of ticks) and relative tick abundance of nymphs and larvae in southern Scandinavia. For nymphs, the predicted abundance had a positive correlation with observed abundance...... the predicted distribution of larvae was mostly even throughout Denmark, it was primarily around the coastlines in Norway and Sweden. Abundance was fairly low overall except in some fragmented patches corresponding to forested habitats in the region. Machine learning techniques allow us to predict for larger...... the collected ticks for pathogens and using the same machine learning techniques to develop prevalence maps of the ScandTick region....

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

    Science.gov (United States)

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

    2009-01-01

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

  16. SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8

    Directory of Open Access Journals (Sweden)

    A. Fryskowska

    2016-06-01

    Full Text Available The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI and the Thermal Infrared Sensor (TIRS. What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands. Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5‐0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of Landsat 8 with data from the new high resolution panchromatic EROS B satellite are analyzed. The range of panchromatic band for EROS B is 0.4‐0.9 μm and spatial resolution is 0.7 m. Research relied on improving the spatial resolution of natural color band combinations (bands: 4,3,2 and of desired false color band composition of Landsat 8 satellite imagery. For this purpose, six algorithms have been tested: Brovey’s, Mulitplicative, PCA, IHS, Ehler's, HPF. On the basis of the visual assessment, it was concluded that the best results of multispectral and panchromatic image integration, regardless land cover, are obtained for the multiplicative method. These conclusions were confirmed by statistical analysis using correlation coefficient, ERGAS and R-RMSE indicators.

  17. Long-term evolution of Wink sinkholes in West Texas observed by high-resolution satellite imagery

    Science.gov (United States)

    Kim, J. W.; Lu, Z.

    2016-12-01

    Sinkhole is ground depression and/or collapse over the subsurface cavity in the karst terrain underlain by the carbonates, evaporites, and other soluble soils and rocks. The geohazards have been considered as a "hidden threat" to human life, infrastructures, and properties. The Delaware Basin of West Texas in the southwest part of the Permian Basin contains one of the greatest accumulations of evaporites in the United States. Sinkholes in West Texas have been developed by the dissolution of the subsurface evaporite deposits that come in contact with groundwater. Two Wink sinkholes in Wink, Texas, were developed in 1980 and 2002, respectively. However, monitoring the sinkholes in no man's lands has been challenging due to the lack of availability of high-resolution and temporally dense acquisitions. We employ aerial photography and radar satellite imagery to measure the long-term deformation from early 2000 and characterize the inherent hydrogeology that is closely related to sinkhole collapse and subsidence. Furthermore, data on oil/gas production and water injection into the subsurface as well as ground water level are analyzed to study their effects on the concurrent unstable ground surface in Wink sinkholes. Our study will provide invaluable information to understand the mechanism of sinkhole development and mitigate the catastrophic outcomes of the geohazards.

  18. Forests through the Eye of a Satellite: Understanding regional forest-cover dynamics using Landsat Imagery

    Science.gov (United States)

    Baumann, Matthias

    Forests are changing at an alarming pace worldwide. Forests are an important provider of ecosystem services that contribute to human wellbeing, including the provision of timber and non-timber products, habitat for biodiversity, recreation amenities. Most prominently, forests serve as a sink for atmospheric carbon dioxide that ultimately helps to mitigate changes in the global climate. It is thus important to understand where, how and why forests change worldwide. My dissertation provides answers to these questions. The overarching goal of my dissertation is to improve our understanding of regional forest-cover dynamics by analyzing Landsat satellite imagery. I answer where forests change following drastic socio-economic shocks by using the breakdown of the Soviet Union as a natural experiment. My dissertation provides innovative algorithms to answer why forests change---because of human activities or because of natural events such as storms. Finally, I will show how dynamic forests are within one year by providing ways to characterize green-leaf phenology from satellite imagery. With my findings I directly contribute to a better understanding of the processes on the Earth's surface and I highlight the importance of satellite imagery to learn about regional and local forest-cover dynamics.

  19. Plastic and Glass Greenhouses Detection and Delineation from WORLDVIEW-2 Satellite Imagery

    Science.gov (United States)

    Koc-San, D.; Sonmez, N. K.

    2016-06-01

    Greenhouse detection using remote sensing technologies is an important research area for yield estimation, sustainable development, urban and rural planning and management. An approach was developed in this study for the detection and delineation of greenhouse areas from high resolution satellite imagery. Initially, the candidate greenhouse patches were detected using supervised classification techniques. For this purpose, Maximum Likelihood (ML), Random Forest (RF), and Support Vector Machines (SVM) classification techniques were applied and compared. Then, sieve filter and morphological operations were performed for improving the classification results. Finally, the obtained candidate plastic and glass greenhouse areas were delineated using boundary tracing and Douglas Peucker line simplification algorithms. The proposed approach was implemented in the Kumluca district of Antalya, Turkey utilizing pan-sharpened WorldView-2 satellite imageries. Kumluca is the prominent district of Antalya with greenhouse cultivation and includes both plastic and glass greenhouses intensively. When the greenhouse classification results were analysed, it can be stated that the SVM classification provides most accurate results and RF classification follows this. The SVM classification overall accuracy was obtained as 90.28%. When the greenhouse boundary delineation results were considered, the plastic greenhouses were delineated with 92.11% accuracy, while glass greenhouses were delineated with 80.67% accuracy. The obtained results indicate that, generally plastic and glass greenhouses can be detected and delineated successfully from WorldView-2 satellite imagery.

  20. Phase 2 Final Report. IAEA Safeguards: Implementation blueprint of commercial satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Christer [SSC Satellitbild AB, Solna (Sweden)

    2000-01-01

    This document - IAEA Safeguards: Implementation Blueprint of Commercial Satellite Imagery - constitutes the second report from SSC Satellitbild giving a structured view and solid guidelines on how to proceed with a conceivable implementation of satellite imagery to support Safeguards activities of the Agency. This Phase 2 report presents a large number of concrete recommendations regarding suggested management issues, work organisation, imagery purchasing and team building. The study has also resulted in several lists of actions and preliminary project plans with GANT schedules concerning training, hardware and software, as well as for the initial pilot studies. In both the Phase 1 and Phase 2 studies it is confirmed that the proposed concept of a relatively small Imagery Unit using high-resolution data will be a sound and feasible undertaking. Such a unit capable of performing advanced image processing as a tool for various safeguard tasks will give the Agency an effective instrument for reference, monitoring, verification, and detection of declared and undeclared activities. The total cost for implementing commercial satellite imagery at the Department for Safeguards, as simulated in these studies, is approximately MUSD 1,5 per year. This cost is founded on an activity scenario with a staff of 4 experts working in an IAEA Imagery Unit with a workload of three dossiers or issues per week. The imagery unit is built around an advanced PC image processing system capable of handling several hundreds of pre-processed images per year. Alternatively a Reduced Scenario with a staff of 3 would need a budget of approximately MUSD 0,9 per year, whereas an Enhanced Imagery Unit including 5 experts and a considerably enlarged capacity would cost MUSD 1,7 per year. The Imagery Unit should be organised so it clearly reflects the objectives and role as set by the Member States and the management of the Agency. We recommend the Imagery Unit to be organised into four main work

  1. The Importance of CIR Aerial Imagery in Inventory, Monitoring and Predicting Forest Condition

    Directory of Open Access Journals (Sweden)

    Jelena Kolić

    2015-07-01

    Full Text Available Background and Purpose: The main goal of this paper was to highlight the importance of colour infrared (CIR aerial photographs for efficient inventory, monitoring and predicting the health status of forests in changed site conditions. CIR aerial photographs from two aerial surveys conducted in 1989 and 2008 were used to identify and analyze the damage in lowland pedunculated oak (Quercus robur L. forests during each period, as well as to obtain a dieback trend in the observed period. Material and Methods: The research was conducted in lowland pedunculated oak forests of Josip Kozarac management unit. CIR aerial photographs (1989 of the research area were taken with a classical camera, while aerial images in 2008 were taken with a digital camera and then converted from digital to analogue form (contact copy - photograph in order to perform photointerpretation with a SOKKIA MS27 Carl ZEISS Jena mirror stereoscope, magnified by 8x. The health status of particular trees (crowns was assessed by means of photointerpretation keys in a stereomodel over a systematic 100x100 m sample grid on both 1989 and 2008 aerial photographs. The degree of damage of 4 individual trees was assessed at every grid point in the surveying strips covering the surveyed area. Damage indicators were calculated and thematic maps were constructed on the basis of the interpretation of data for all the grid points. Results: For the research area a damage index (IO of 68.36% for oak was determined by photointerpreting individual trees (2008; in other words, this percentage of pedunculate oak trees in the surveyed area was found to be in the damage degree of 2.1 and more. Of 68.36% trees classified in the damage degree of 2.1 or more, mean damage (SO1 amounted to 52.16% and could be classified in the damage degree of 2.2. In 1989, the mean damage index (IO for pedunculate oak was 48.00%, and pedunculate oak trees with mean damage degree of 2.1 or more (SO1 amounted to 36.03%. The

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

    Science.gov (United States)

    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.

  3. Performance Evaluation of Data Compression Systems Applied to Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Lilian N. Faria

    2012-01-01

    Full Text Available Onboard image compression systems reduce the data storage and downlink bandwidth requirements in space missions. This paper presents an overview and evaluation of some compression algorithms suitable for remote sensing applications. Prediction-based compression systems, such as DPCM and JPEG-LS, and transform-based compression systems, such as CCSDS-IDC and JPEG-XR, were tested over twenty multispectral (5-band images from CCD optical sensor of the CBERS-2B satellite. Performance evaluation of these algorithms was conducted using both quantitative rate-distortion measurements and subjective image quality analysis. The PSNR, MSSIM, and compression ratio results plotted in charts and the SSIM maps are used for comparison of quantitative performance. Broadly speaking, the lossless JPEG-LS outperforms other lossless compression schemes, and, for lossy compression, JPEG-XR can provide lower bit rate and better tradeoff between compression ratio and image quality.

  4. Physical effect of cloud seeding revealed by NOAA satellite imagery

    Institute of Scientific and Technical Information of China (English)

    YU Xing; DAI Jin; LEI Hengchi; XU Xiaohong; FAN Peng; CHEN Zhengqi; DUAN Changhui; WANG Yong

    2005-01-01

    From 0615 to 0749 UTC, 14 March 2000, a precipitation enhancement operation with AgI using an aircraft was conducted at the middle part of Shaanxi Province, China. 80 min after cloud seeding (0735 UTC), NOAA-14 satellite data showed a vivid zigzag cloud track on the satellite image. Its length is 301 km, and its average and maximum width are 8.3 and 11 km. The cloud track is very similar in shape with, but different in position and width from that of cloud seeding line. In order to determine that the cloud track is indeed caused by cloud seeding, a three-dimensional numerical model of transport and diffusion of seeding material is used to simulate the shape of seeding material concentration distribution, the turning points, width and length of seeding line. The simulated results are compared with the features of cloud track at 0735 UTC. Every segment of the cloud track is consistent with the transport and diffusion of every segment of seeding line. The transport position, length, width and the variation trend of seeding line agree with those of cloud track. All suggest that the cloud track is the direct physical reflection of cloud seeding effect on the cloud top, which can respond to the transport and diffusion of seeding material. For this study case, the main effecting duration for every segment of seeding line is from 20 to 80 min, the time for each segment of seeding line diffusing to the maximum width is from about 50 to 70 min. This time is obtained from the appearing and disappearing time, width variation of the cloud track segments and simulated results. Also, the comparisons demonstrate that the numerical model of transport and diffusion can simulate the main characteristics of transport and diffusion of seeding material, and the simulating results are sound and trustworthy.

  5. The potential of aerial platforms in a ‘rapid’ emergency response context

    OpenAIRE

    Lemoine, Guido; SPRUYT Peter

    2013-01-01

    This report reflects on the potential use of aerial platforms in rapid emergency response contexts, typically following major disaster and crisis events. In Europe, a coordinated effort to provide mapping services to support emergency response operations after such events is part of the Copernicus programme, which facilitates the fast provision of thematic post-event map products based on satellite imagery. Increasingly imagery derived from aerial platforms are providing operational capacitie...

  6. Satellite and Aerial Remote Sensing in Support of Disaster Response Operations Conducted by the Texas Division of Emergency Management

    Science.gov (United States)

    Wells, G. L.; Tapley, B. D.; Bettadpur, S. V.; Howard, T.; Porter, B.; Smith, S.; Teng, L.; Tapley, C.

    2014-12-01

    The effective use of remote sensing products as guidance to emergency managers and first responders during field operations requires close coordination and communication with state-level decision makers, incident commanders and the leaders of individual strike teams. Information must be tailored to meet the needs of different emergency support functions and must contain current (ideally near real-time) data delivered in standard formats in time to influence decisions made under rapidly changing conditions. Since 2003, a representative of the University of Texas Center for Space Research (CSR) has served as a member of the Governor's Emergency Management Council and has directed the flow of information from remote sensing observations and high performance computing modeling and simulations to the Texas Division of Emergency Management in the State Operations Center. The CSR team has supported response and recovery missions resulting from hurricanes, tornadoes, flash floods, wildfires, oil spills and other natural and man-made disasters in Texas and surrounding states. Through web mapping services, state emergency managers and field teams have received threat model forecasts, real-time vehicle tracking displays and imagery to support search-and-clear operations before hurricane landfall, search-and-rescue missions following floods, tactical wildfire suppression, pollution monitoring and hazardous materials detection. Data servers provide near real-time satellite imagery collected by CSR's direct broadcast receiving system and post data products delivered during activations of the United Nations International Charter on Space and Major Disasters. In the aftermath of large-scale events, CSR is charged with tasking state aviation resources, including the Air National Guard and Texas Civil Air Patrol, to acquire geolocated aerial photography of the affected region for wide area damage assessment. A data archive for each disaster is available online for years following

  7. Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

    Directory of Open Access Journals (Sweden)

    Nahuel R. Peralta

    2016-10-01

    Full Text Available A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at mid-growing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington of Kansas (total of 457 ha. Three basic tests were conducted on the data: (1 spatial dependence on each of the yield and vegetation indices (VIs using Moran’s I test; (2 model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS and spatial econometric (SPL models; and (3 model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG was tested positive and statistically significant for most of the fields (p < 0.05, except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02 was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to

  8. River-ice and sea-ice velocity fields from near-simultaneous satellite imagery

    Science.gov (United States)

    Kaeaeb, A.; Leprince, S.; Prowse, T. D.; Beltaos, S.; Lamare, M.; Abrams, M.

    2013-12-01

    Satellite stereo and satellites that follow each other on similar orbits within short time periods produce near-simultaneous space imagery, a kind of data that is little exploited. In this study, we track river-ice and sea-ice motion over time periods of tens of seconds to several minutes, which is the typical time lag between the two or more images of such near-simultaneous acquisition constellations. Using this novel approach, we measure and visualize for the first time the almost complete two-dimensional minute-scale velocity fields over several thousand square-kilometers of sea ice cover or over up to several hundred kilometers long river reaches. We present the types of near-simultaneous imagery and constellations suitable for the measurements and discuss application examples, using a range of high and medium resolution imagery such as from ASTER, ALOS PRISM, Ikonos, WorldView-2, Landsat and EO-1. The river ice velocities obtained provide new insights into ice dynamics, river flow and river morphology, in particular during ice breakup. River-ice breakup and the associated downstream transport of ice debris is often the most important hydrological event of the year, producing flood levels that commonly exceed those for the open-water period and dramatic consequences for river infrastructure and ecology. We also estimate river discharge from ice/water surface velocities using near-simultaneous satellite imagery. Our results for sea ice complement velocity fields typically obtained over time-scales of days and can thus contribute to better understanding of a number of processes involved in sea ice drift, such as wind impact, tidal currents and interaction of ice floes with each other and with obstacles.

  9. Automated Generation of the Alaska Coastline Using High-Resolution Satellite Imagery

    Science.gov (United States)

    Roth, G.; Porter, C. C.; Cloutier, M. D.; Clementz, M. E.; Reim, C.; Morin, P. J.

    2015-12-01

    Previous campaigns to map Alaska's coast at high resolution have relied on airborne, marine, or ground-based surveying and manual digitization. The coarse temporal resolution, inability to scale geographically, and high cost of field data acquisition in these campaigns is inadequate for the scale and speed of recent coastal change in Alaska. Here, we leverage the Polar Geospatial Center (PGC) archive of DigitalGlobe, Inc. satellite imagery to produce a state-wide coastline at 2 meter resolution. We first select multispectral imagery based on time and quality criteria. We then extract the near-infrared (NIR) band from each processed image, and classify each pixel as water or land with a pre-determined NIR threshold value. Processing continues with vectorizing the water-land boundary, removing extraneous data, and attaching metadata. Final coastline raster and vector products maintain the original accuracy of the orthorectified satellite data, which is often within the local tidal range. The repeat frequency of coastline production can range from 1 month to 3 years, depending on factors such as satellite capacity, cloud cover, and floating ice. Shadows from trees or structures complicate the output and merit further data cleaning. The PGC's imagery archive, unique expertise, and computing resources enabled us to map the Alaskan coastline in a few months. The DigitalGlobe archive allows us to update this coastline as new imagery is acquired, and facilitates baseline data for studies of coastal change and improvement of topographic datasets. Our results are not simply a one-time coastline, but rather a system for producing multi-temporal, automated coastlines. Workflows and tools produced with this project can be freely distributed and utilized globally. Researchers and government agencies must now consider how they can incorporate and quality-control this high-frequency, high-resolution data to meet their mapping standards and research objectives.

  10. Aerial Photography and Imagery, Ortho-Corrected, 1991 DOQQs in Grid format on CD-ROM, Published in 1991, 1:12000 (1in=1000ft) scale, Reno County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  11. Aerial Photography and Imagery, Ortho-Corrected, Lafayette County Mr. Sids and TIF files, Published in 2005, 1:24000 (1in=2000ft) scale, Lafayette County Land Records.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Orthoimagery information as...

  12. Aerial Photography and Imagery, Ortho-Corrected, True Color Orthophotography for Wicomico County, Maryland - 6" pixles, 2006., Published in 2006, 1:1200 (1in=100ft) scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  13. Aerial Photography and Imagery, Ortho-Corrected, 2005 natural color orthoimagery for alameda county geotiff format, Published in 2005, 1:2400 (1in=200ft) scale, US Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  14. Aerial Photography and Imagery, Ortho-Corrected, One meter black and white digital orthophotographs created in concert with the U.S.G.S., Published in 1992, 1:9600 (1in=800ft) scale, Manitowoc County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 1992. One meter black and white digital orthophotographs created in concert with the U.S.G.S..

  15. Aerial Photography and Imagery, Ortho-Corrected, Washburn County had ortho/oblique photography flight done in April of 2009. Pictometry was contracted for the project., Published in 2009, 1:4800 (1in=400ft) scale, Washburn County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  16. Aerial Photography and Imagery, Ortho-Corrected, True Color Orthophotography for Centerville, Grasonville, Kent Island, and Queenstown - 4" pixles, 2004., Published in 2004, 1:600 (1in=50ft) scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  17. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orhophotography - 1/2 foot resolution over selected areas, Published in 2009, 1:2400 (1in=200ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orhophotography - 1/2 foot resolution over selected areas.

  18. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orthophotography - 1/4 foot resolution over selected areas, Published in 2009, 1:1200 (1in=100ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orthophotography - 1/4 foot resolution over selected...

  19. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orthophotography - 1 foot resolution in the remainder of the county, Published in 2009, 1:4800 (1in=400ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orthophotography - 1 foot resolution in the remainder of...

  20. Aerial Photography and Imagery, Ortho-Corrected, Buffalo County, WI countywide orthoimagery flown April 14,17.2006, Published in 2006, 1:600 (1in=50ft) scale, Buffalo County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  1. Aerial Photography and Imagery, Ortho-Corrected, 2002 Buffalo County, WI Color orthophotography flown April 16/17, Published in 2002, 1:600 (1in=50ft) scale, Buffalo County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  2. Aerial Photography and Imagery, Ortho-Corrected, Have done 6" color resolution of entire County including the City of Ulysses, Published in 2007, 1:4800 (1in=400ft) scale, Grant County Emergency Management.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  3. Aerial Photography and Imagery, Ortho-Corrected, Chowan County, NC true color orthophotography - 1/4 foot resolution over selected areas, Published in 2009, 1:1200 (1in=100ft) scale, Chowan County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Chowan County, NC true color orthophotography - 1/4 foot resolution over selected areas.

  4. Aerial Photography and Imagery, Ortho-Corrected, Bertie County, NC true color orthophotography - 1 foot resolution over the remainder of the county, Published in 2009, 1:4800 (1in=400ft) scale, Bertie County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Bertie County, NC true color orthophotography - 1 foot resolution over the remainder of...

  5. Aerial Photography and Imagery, Oblique, Pictometry/Microsoft Virtual Earth is the source of most of this., Published in 2007, 1:12000 (1in=1000ft) scale, Brown County, WI.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Other information as of 2007. It is...

  6. Aerial Photography and Imagery, Ortho-Corrected, True Color Orthophotography for Cambridge, Hurlock, Secretary, and Vienna - 4" pixles, 2006., Published in 2006, 1:600 (1in=50ft) scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  7. Aerial Photography and Imagery, Ortho-Corrected, Gates County, NC true color orthophotography - 1/2 foot resolution over selected areas, Published in unknown, 1:2400 (1in=200ft) scale, Gates County Tax Department.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  8. Aerial Photography and Imagery, Ortho-Corrected, Frederick County, 6" pixel orthophotography, Maryland State Highway, Published in 2007, 1:600 (1in=50ft) scale, Frederick County, MD Enterprise GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:600 (1in=50ft) scale, was produced all or in part from Orthoimagery information as of...

  9. Aerial Photography and Imagery, Ortho-Corrected, 6 in orthophotography for cities of Lakin and Deerfield, Published in 2007, 1:1200 (1in=100ft) scale, Kearny County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Not Provided information as of...

  10. Aerial Photography and Imagery, Ortho-Corrected, Herford County, NC true color orthophotography - 1/4 foot resolution over selected areas, Published in 2009, 1:1200 (1in=100ft) scale, Herford County, NC Land Records.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  11. Aerial Photography and Imagery, Ortho-Corrected, 2005 Color 1 Foot and 6 Inch Orthoimagery, Published in 2005, 1:2400 (1in=200ft) scale, Winnebago County GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  12. Aerial Photography and Imagery, Ortho-Corrected, 1998 orthophotography for the city of Hutchinson in TIFF format. Obtained from the City of Hutchinson., Published in 1998, 1:1200 (1in=100ft) scale, Reno County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:1200 (1in=100ft) scale, was produced all or in part from Orthoimagery information as of...

  13. Aerial Photography and Imagery, Oblique, For rural areas Pictometry flown 11/2009, not yet delivered as of 2/2010, Published in 2009, 1:4800 (1in=400ft) scale, Greene County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Oblique dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of 2009....

  14. Aerial Photography and Imagery, Ortho-Corrected, NAIP 2007 Orthoimagery 1-meter natural color (RGBIR) Statewide coverage., Published in 2007, 1:12000 (1in=1000ft) scale, Arizona State Land Department.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  15. Aerial Photography and Imagery, Ortho-Corrected, USGS/USDA/State of Oklahoma partnership, Published in 1995, 1:12000 (1in=1000ft) scale, Office of Geographic Information.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  16. Aerial Photography and Imagery, Ortho-Corrected, Washburn County had ortho/oblique photography flight done in April of 2009. Pictometry was contracted for the project., Published in 2009, 1:4800 (1in=400ft) scale, Washburn County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washburn County had ortho/oblique photography flight done in April of 2009. Pictometry...

  17. Aerial Photography and Imagery, Oblique, Washburn County had oblique photography flight done in April of 2009. Pictometry was contracted for the project., Published in 2009, 1:4800 (1in=400ft) scale, Washburn County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Oblique dataset current as of 2009. Washburn County had oblique photography flight done in April of 2009. Pictometry was contracted...

  18. Aerial Photography and Imagery, Ortho-Corrected, Hawaii (Big Island) Digital Raster Graphic, Published in 2004, 1:24000 (1in=2000ft) scale, U.S. Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Hardcopy Maps information as...

  19. Aerial Photography and Imagery, Ortho-Corrected, Orthoimagery for Athens-Clarke County, Georgia, Published in 2005, 1:4800 (1in=400ft) scale, Northeast Georgia Regional Commission.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  20. Aerial Photography and Imagery, Ortho-Corrected, 2005 DOQQs in MrSID format obtained from DASC, Published in 2005, 1:12000 (1in=1000ft) scale, Reno County.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  1. Aerial Photography and Imagery, Ortho-Corrected, 2007 Color Orthophotos (MrSID and TIFF formats), Published in 2007, 1:2400 (1in=200ft) scale, CHATHAM COUNTY GIS.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  2. Aerial Photography and Imagery, Ortho-Corrected, True Color Orthos at 1:4800 & 1:2400 3/2006, Published in 2006, 1:4800 (1in=400ft) scale, Hyde County Emergency Management.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  3. Aerial Photography and Imagery, Ortho-Corrected, naturla color 1-ft orthoinagery for fresno urban area public domain, Published in 2007, 1:4800 (1in=400ft) scale, US Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  4. Aerial Photography and Imagery, Ortho-Corrected, Color orthophotos of Eastern York County and the municipalities of Urbanized Eastern York County flown at 200 scale, Published in 2000, 1:2400 (1in=200ft) scale, York County Government, SC.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  5. Aerial Photography and Imagery, Ortho-Corrected, san bernardino urban area natural color orthoimagery 2006, Published in 2006, 1:2400 (1in=200ft) scale, US Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  6. Aerial Photography and Imagery, Ortho-Corrected, NAIP statewide natural color geotiff image tiles, 2005, Published in 2005, 1:12000 (1in=1000ft) scale, US Geological Survey.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:12000 (1in=1000ft) scale, was produced all or in part from Orthoimagery information as...

  7. Aerial Photography and Imagery, Ortho-Corrected, Spring 2010 leaf-off natural color 12 inch ground pixel digital orthophotograpy, Published in 2010, 1:4800 (1in=400ft) scale, Vernon County Wisconsin.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  8. Aerial Photography and Imagery, Ortho-Corrected, Rural areas are 12 inch and urban areas are 6in, Published in 2007, 1:24000 (1in=2000ft) scale, Johnson County GIS Department.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Orthoimagery information as...

  9. Aerial Photography and Imagery, Ortho-Corrected, Bertie County, NC true color orthophotography - 1 foot resolution over the remainder of the county, Published in 2009, 1:4800 (1in=400ft) scale, Bertie County - Tax Mapping.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Orthoimagery information as of...

  10. Aerial Photography and Imagery, Ortho-Corrected, USGS High Resolution Orthoimage, Salt Lake City - Ogden, UT, Published in 2003, 1:24000 (1in=2000ft) scale, State of Utah Automated Geographic Reference Center.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:24000 (1in=2000ft) scale, was produced all or in part from Orthoimagery information as...

  11. Rice yield forecasting models using satellite imagery in Egypt

    Directory of Open Access Journals (Sweden)

    N.A. Noureldin

    2013-06-01

    Full Text Available Ability to make yield prediction before harvest using satellite remote sensing is important in many aspects of agricultural decision-making. In this study, canopy reflectance band and different band ratios in form of vegetation indices (VI with leaf area index (LAI were used to generate remotely sensed pre-harvest empirical rice yield prediction models. LAI measurements, spectral data derived from two SPOT data acquired on August 24, 2008 and August 23, 2009 and observed rice yield were used as main inputs for rice yield modeling. Each remotely sensed factor was used separately and in combination with LAI to generate the models. The results showed that green spectral band, middle infra-red spectral band and green vegetation index (GVI did not show sufficient capability as rice yield estimators while other inputs such as red spectral band, near infrared spectral band and vegetation indices that are algebraic ratios from these two spectral bands when used separately or in combined with leaf area index (LAI produced high accurate rice yield estimation models. The validation process was carried out using two statistical tests; standard error of estimate and the correlation coefficient between modeled and predicted yield. The validation results indicated that using normalized difference vegetation index (NDVI combined with leaf area index (LAI produced the model with highest accuracy and stability during the two rice seasons. The generated models are applicable 90 days after planting in any similar environmental conditions and agricultural practices.

  12. Man-made objects cuing in satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2009-01-01

    We present a multi-scale framework for man-made structures cuing in satellite image regions. The approach is based on a hierarchical image segmentation followed by structural analysis. A hierarchical segmentation produces an image pyramid that contains a stack of irregular image partitions, represented as polygonized pixel patches, of successively reduced levels of detail (LOOs). We are jumping off from the over-segmented image represented by polygons attributed with spectral and texture information. The image is represented as a proximity graph with vertices corresponding to the polygons and edges reflecting polygon relations. This is followed by the iterative graph contraction based on Boruvka's Minimum Spanning Tree (MST) construction algorithm. The graph contractions merge the patches based on their pairwise spectral and texture differences. Concurrently with the construction of the irregular image pyramid, structural analysis is done on the agglomerated patches. Man-made object cuing is based on the analysis of shape properties of the constructed patches and their spatial relations. The presented framework can be used as pre-scanning tool for wide area monitoring to quickly guide the further analysis to regions of interest.

  13. Environmental monitoring of El Hierro Island submarine volcano, by combining low and high resolution satellite imagery

    Science.gov (United States)

    Eugenio, F.; Martin, J.; Marcello, J.; Fraile-Nuez, E.

    2014-06-01

    El Hierro Island, located at the Canary Islands Archipelago in the Atlantic coast of North Africa, has been rocked by thousands of tremors and earthquakes since July 2011. Finally, an underwater volcanic eruption started 300 m below sea level on October 10, 2011. Since then, regular multidisciplinary monitoring has been carried out in order to quantify the environmental impacts caused by the submarine eruption. Thanks to this natural tracer release, multisensorial satellite imagery obtained from MODIS and MERIS sensors have been processed to monitor the volcano activity and to provide information on the concentration of biological, chemical and physical marine parameters. Specifically, low resolution satellite estimations of optimal diffuse attenuation coefficient (Kd) and chlorophyll-a (Chl-a) concentration under these abnormal conditions have been assessed. These remote sensing data have played a fundamental role during field campaigns guiding the oceanographic vessel to the appropriate sampling areas. In addition, to analyze El Hierro submarine volcano area, WorldView-2 high resolution satellite spectral bands were atmospherically and deglinted processed prior to obtain a high-resolution optimal diffuse attenuation coefficient model. This novel algorithm was developed using a matchup data set with MERIS and MODIS data, in situ transmittances measurements and a seawater radiative transfer model. Multisensor and multitemporal imagery processed from satellite remote sensing sensors have demonstrated to be a powerful tool for monitoring the submarine volcanic activities, such as discolored seawater, floating material and volcanic plume, having shown the capabilities to improve the understanding of submarine volcanic processes.

  14. Satellite Imagery Measures of the Astronomically Aligned Megalithis at Nabta Playa.

    Science.gov (United States)

    Brophy, T.; Rosen, P.

    The Nabta Playa megalithic complex consists of two types of features: first are the large stones, many of them shaped, placed on or in the sediments of an ancient seasonal lake bed that is now hyper-ariad, second are large sculpted bedrocks features underneath the sediments and associated with the surface megaliths (Wendorf et al. 1992). The astronomically aligned surface megalithic structures described in field reports (Wendorf and Malville, 2001) are identified in recent georectified 60cm panchromatic satellite imagery of Nabta Playa, Southern Egypt. The satellite images allow refinement, often significant of the reported locations of the megaliths (Malville et al 1998, and Wendorf and Malville 2001). The report that a primary megalithic alignment was constructed to point to the bright star Sirius, circa 4820BC, is reconsidered in light of the satellite data, new field, data, radiocarbon, lithostratigraphic and geochronological data, and the playa sedimentation history. Other possible archaeoastronomical interpretations are considered for that alignment, including the three star asterism (of Alnitak, Alniham and Mintaka) circa 6270BC that is also implicated in the small Nebta Playa "calendar circle". Signatures of other possible features apparent in the satellite imagery and a recent field study are also considered. Only a small number of the subsurface bedrock sculptures have been excavated. We recommend the use of ground penetrating imaging methods to illuminate the known but not yet excavated subsurface features. The problem of determining the astronomical intent of the builders of the megalithic structures is approached by considering the complex of features as a whole.

  15. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    KAUST Repository

    McCabe, Matthew

    2016-10-25

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-Agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  16. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    Science.gov (United States)

    McCabe, Matthew F.; Houborg, Rasmus; Lucieer, Arko

    2016-10-01

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  17. Low-altitude aerial imagery and related field observations associated with unmanned aerial systems (UAS) flights over Coast Guard Beach, Nauset Spit, Nauset Inlet, and Nauset Marsh, Cape Cod National Seashore, Eastham, Massachusetts on 1 March 2016

    Science.gov (United States)

    Sherwood, Christopher R.

    2016-01-01

    Low-altitude (approximately 120 meters above ground level) digital images were obtained from cameras mounted in a fixed-wing unmanned aerial vehicle (UAV) flown from the lawn adjacent to the Coast Guard Beach parking lot on 1 March, 2016. The UAV was a Skywalker X8 operated by Raptor Maps, Inc., contractors to the U.S. Geological Survey (USGS). Two consecutive unmanned aerial systems (UAS) missions were flown, each with two cameras, autopilot computer, radios, and a global satellite navigation system as payload. The first flight (f1) was launched at approximately 1112 Eastern Standard Time (EST), and followed north-south flight lines, landing at about 1226 EST. Two Canon Powershot SX280 12-mexapixel digital cameras, designated rgb1 and rgb2, recorded images during this flight. The second flight (f2) was launched at 1320 EST and followed east-west flight lines, landing at 1450 EST. Prior to f2, rgb2 was replaced with a Canon SX280 modified with a Schott BG 3 filter to emphasize light at near-infrared wavelengths, designated nir1. Rgb1 and nir1 made images during this second flight. Thus four series of images were collected, designated f1_rgb1, f1_rgb2, f2_rgb1, and f2_nir1.Low tide on the ocean beaches was forecast for approximately 1130 EST, and estimated low tide on the marsh was at least an hour later. Weather conditions were clear and sunny during the first flight. During the second flight, there were periods with high clouds. Winds (estimated by experienced observers) during the first flight were from the north-northeast at ~15 mph, with gusts to ~20 mph. Winds decreased beginning in early afternoon, and at the end of the second flight, estimated winds were 5 – 10 mph with gusts to 15 mph.USGS field technicians mapped the location of 32 ground control points and 144 independent points along cross-shore transects. These points were measured with a global positioning system (GPS) using real-time differential corrections from a base station set up near the

  18. Optimizing statistical classification accuracy of satellite remotely sensed imagery for supporting fast flood hydrological analysis

    Science.gov (United States)

    Alexakis, Dimitrios; Agapiou, Athos; Hadjimitsis, Diofantos; Retalis, Adrianos

    2012-06-01

    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. For this purpose, precipitation and ground spectroradiometric data have been collected and analyzed with innovative statistical analysis methods. Samples of regolith and construction material were in situ collected and examined in the spectroscopy laboratory for their spectral response under consecutive different conditions of humidity. Moreover, reflectance values were extracted from the same targets using Landsat TM/ETM+ images, for drought and humid time periods, using archived meteorological data. The comparison of the results showed that spectral responses for all the specimens were less correlated in cases of substantial humidity, both in laboratory and satellite images. These results were validated with the application of different classification algorithms (ISODATA, maximum likelihood, object based, maximum entropy) to satellite images acquired during time period when precipitation phenomena had been recorded.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  1. Swords into Ploughshares: Archaeological Applications of CORONA Satellite Imagery in the Near East

    Directory of Open Access Journals (Sweden)

    Jesse Casana

    2012-09-01

    Full Text Available Since their declassification in 1995, CORONA satellite images collected by the United States military from 1960-1972 have proved to be an invaluable resource in the archaeology of the Near East. Because CORONA images pre-date the widespread construction of reservoirs, urban expansion, and agricultural intensification the region has undergone in recent decades, these high-resolution, stereo images preserve a picture of archaeological sites and landscapes that have often been destroyed or obscured by modern development. Despite its widely recognised value, the application of CORONA imagery in archaeological research has remained limited to a small group of specialists, largely because of the challenges involved in correcting spatial distortions produced by the satellites' unusual panoramic cameras. This article presents results of an effort to develop new methods of efficiently orthorectifying CORONA imagery and to use these methods to produce geographically corrected images across the Near East, now freely available through an online database. Following an overview of our methods, we present examples of how recent development has affected the archaeological record, new discoveries that analysis of our CORONA imagery database has already made possible, and emerging applications of CORONA including stereo analysis and DEM extraction.

  2. Surface flow structure of the Gulf Stream from composite imagery and satellite-tracked drifters

    Directory of Open Access Journals (Sweden)

    C. P. Mullen

    1994-01-01

    Full Text Available A unique set of coutemporaneous satellite-tracked drifters and five-day composite Advanced Very High Resolution Radionmeter (AVHRR satellite imagery of the North Atlantic has been analyzed to examine the surface flow structure of the Gulf Stream. The study region was divided into two sections, greater than 37° N and less than 37° N, in order to answer the question of geographic variability. Fractal and spectral analyses methods were applied to the data. Fractal analysis of the Lagrangian trajectories showed a fractal dimension of 1.21 + 0.02 with a scaling range of 83 - 343 km. The fractal dimension of the temperature fronts of the composite imagery is similar for the two regions with D = 1.11 + 0.01 over a scaling range of 4 - 44 km. Spectral analysis also reports a fairly consistent value for the spectral slope and its scaling range. Therefore, we conclude there is no geographic variability in the data set. A suitable scaling range for this contemporaneous data set is 80 - 200 km which is consistent with the expected physical conditions in the region. Finally, we address the idea of using five-day composite imagery to infer the surface flow of the Gulf Stream. Close analyses of the composite thermal fronts and the Lagrangian drifter trajectories show that the former is not a good indicator of the latter.

  3. PlumeSat: A Micro-Satellite Based Plume Imagery Collection Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Ledebuhr, A.G.; Ng, L.C.

    2002-06-30

    This paper describes a technical approach to cost-effectively collect plume imagery of boosting targets using a novel micro-satellite based platform operating in low earth orbit (LEO). The plume collection Micro-satellite or PlueSat for short, will be capable of carrying an array of multi-spectral (UV through LWIR) passive and active (Imaging LADAR) sensors and maneuvering with a lateral divert propulsion system to different observation altitudes (100 to 300 km) and different closing geometries to achieve a range of aspect angles (15 to 60 degrees) in order to simulate a variety of boost phase intercept missions. The PlumeSat will be a cost effective platform to collect boost phase plume imagery from within 1 to 10 km ranges, resulting in 0.1 to 1 meter resolution imagery of a variety of potential target missiles with a goal of demonstrating reliable plume-to-hardbody handover algorithms for future boost phase intercept missions. Once deployed on orbit, the PlumeSat would perform a series phenomenology collection experiments until expends its on-board propellants. The baseline PlumeSat concept is sized to provide from 5 to 7 separate fly by data collects of boosting targets. The total number of data collects will depend on the orbital basing altitude and the accuracy in delivering the boosting target vehicle to the nominal PlumeSat fly-by volume.

  4. Satellite Hyperspectral Imagery to Support Tick-Borne Infectious Diseases Surveillance.

    Directory of Open Access Journals (Sweden)

    Gina Polo

    Full Text Available This study proposed the use of satellite hyperspectral imagery to support tick-borne infectious diseases surveillance based on monitoring the variation in amplifier hosts food sources. To verify this strategy, we used the data of the human rickettsiosis occurrences in southeastern Brazil, region in which the emergence of this disease is associated with the rising capybara population. Spatio-temporal analysis based on Monte Carlo simulations was used to identify risk areas of human rickettsiosis and hyperspectral moderate-resolution imagery was used to identify the increment and expansion of sugarcane crops, main food source of capybaras. In general, a pixel abundance associated with increment of sugarcane crops was detected in risk areas of human rickettsiosis. Thus, the hypothesis that there is a spatio-temporal relationship between the occurrence of human rickettsiosis and the sugarcane crops increment was verified. Therefore, due to the difficulty of monitoring locally the distribution of infectious agents, vectors and animal host's, satellite hyperspectral imagery can be used as a complementary tool for the surveillance of tick-borne infectious diseases and potentially of other vector-borne diseases.

  5. Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

    Science.gov (United States)

    Logan, T. L.; Huning, J. R.; Glackin, D. L.

    1983-01-01

    The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

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

    Science.gov (United States)

    Smaczyński, Maciej; Medyńska-Gulij, Beata

    2017-06-01

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

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

    OpenAIRE

    Huang, Huabing; Gong, Peng; CHENG, XIAO; Clinton, Nick; Li, Zengyuan

    2009-01-01

    Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to ...

  8. Blanding’s Turtle (Emydoidea blandingii Potential Habitat Mapping Using Aerial Orthophotographic Imagery and Object Based Classification

    Directory of Open Access Journals (Sweden)

    Douglas J. King

    2012-01-01

    Full Text Available Blanding’s turtle (Emydoidea blandingii is a threatened species under Canada’s Species at Risk Act. In southern Québec, field based inventories are ongoing to determine its abundance and potential habitat. The goal of this research was to develop means for mapping of potential habitat based on primary habitat attributes that can be detected with high-resolution remotely sensed imagery. Using existing spring leaf-off 20 cm resolution aerial orthophotos of a portion of Gatineau Park where some Blanding’s turtle observations had been made, habitat attributes were mapped at two scales: (1 whole wetlands; (2 within wetland habitat features of open water, vegetation (used for camouflage and thermoregulation, and logs (used for spring sun-basking. The processing steps involved initial pixel-based classification to eliminate most areas of non-wetland, followed by object-based segmentations and classifications using a customized rule sequence to refine the wetland map and to map the within wetland habitat features. Variables used as inputs to the classifications were derived from the orthophotos and included image brightness, texture, and segmented object shape and area. Independent validation using field data and visual interpretation showed classification accuracy for all habitat attributes to be generally over 90% with a minimum of 81.5% for the producer’s accuracy of logs. The maps for each attribute were combined to produce a habitat suitability map for Blanding’s turtle. Of the 115 existing turtle observations, 92.3% were closest to a wetland of the two highest suitability classes. High-resolution imagery combined with object-based classification and habitat suitability mapping methods such as those presented provide a much more spatially explicit representation of detailed habitat attributes than can be obtained through field work alone. They can complement field efforts to document and track turtle activities and can contribute to

  9. Aerial Photography and Imagery, Ortho-Corrected, RIGIS03/04 Digital Orthophotos of Rhode Island 2003-2004; For this dataset, the natural color orthoimages were produced at 2 foot pixel resolution. Each compressed and mosaiced orthoimage provides imagery for a 20000- by 20000-foot block on the ground., Published in 2005, 1:4800 (1in=400ft) scale, State of Rhode Island and Providence Plantations.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:4800 (1in=400ft) scale, was produced all or in part from Uncorrected Imagery information...

  10. Delineating Tree Types in a Complex Tropical Forest Setting Using High Resolution Multispectral Satellite Imagery

    Science.gov (United States)

    Cross, M.

    2016-12-01

    An improved process for the identification of tree types from satellite imagery for tropical forests is needed for more accurate assessments of the impact of forests on the global climate. La Selva Biological Station in Costa Rica was the tropical forest area selected for this particular study. WorldView-3 imagery was utilized because of its high spatial, spectral and radiometric resolution, its availability, and its potential to differentiate species in a complex forest setting. The first-step was to establish confidence in the high spatial and high radiometric resolution imagery from WorldView-3 in delineating tree types within a complex forest setting. In achieving this goal, ASD field spectrometer data were collected of specific tree species to establish solid ground control within the study site. The spectrometer data were collected from the top of each specific tree canopy utilizing established towers located at La Selva Biological Station so as to match the near-nadir view of the WorldView-3 imagery. The ASD data was processed utilizing the spectral response functions for each of the WorldView-3 bands to convert the ASD data into a band specific reflectivity. This allowed direct comparison of the ASD spectrometer reflectance data to the WorldView-3 multispectral imagery. The WorldView-3 imagery was processed to surface reflectance using two standard atmospheric correction procedures and the proprietary DigitalGlobe Atmospheric Compensation (AComp) product. The most accurate correction process was identified through comparison to the spectrometer data collected. A series of statistical measures were then utilized to access the accuracy of the processed imagery and which imagery bands are best suited for tree type identification. From this analysis, a segmentation/classification process was performed to identify individual tree type locations within the study area. It is envisioned the results of this study will improve traditional forest classification

  11. Scheduling satellite imagery acquisition for sequential assimilation of water level observation into flood modelling

    Science.gov (United States)

    García-Pintado, Javier; Neal, Jeff C.; Mason, David C.; Dance, Sarah L.; Bates, Paul D.

    2013-04-01

    Satellite-based imagery has proved useful for obtaining information on water levels in flood events. Microwave frequencies are generally more useful for flood detection than visible-band sensors because of its all-weather day-night capability. Specifically, the future SWOT mission, with Ka-band interferometry, will be able to provide direct Water Level Observations (WLOs), and current and future Synthetic Aperture Radar (SAR) sensors can provide information of flood extent, which, when intersected with a Digital Elevation Model (DEM) of the floodplain, provides indirect WLOs. By either means, satellite-based WLOs can be assimilated into a hydrodynamic model to decrease forecast uncertainty and further to estimate river discharge into the flooded domain. Operational scenarios can even make a combined use of imagery from different uncoordinated missions to sequentially estimate river discharge. Thus, with an increasing number of operational satellites with WLO capability, information on the relationship between satellite first visit, revisit times, and forecast performance is required to optimise the operational scheduling of satellite imagery. By using an Ensemble Transform Kalman Filter (ETKF) and a synthetic analysis with the 2D hydrodynamic model LISFLOOD-FP based on a real flooding case affecting an urban area (summer 2007, Tewkesbury, Southwest UK), we evaluate the sensitivity of the forecast performance to visit parameters. As an example, we use different scenarios of revisit times and observational errors expected from the current COSMO-Skymed (CSK) constellation, with X-band SAR. We emulate a generic hydrologic-hydrodynamic modelling cascade by imposing a bias and spatiotemporal correlations to the inflow error ensemble into the hydrodynamic domain. First, in agreement with previous research, estimation and correction for this bias leads to a clear improvement in keeping the forecast on track. Second, imagery obtained early in the flood is shown to have a

  12. AN EFFICIENT APPROACH FOR EXTRACTION OF LINEAR FEATURES FROM HIGH RESOLUTION INDIAN SATELLITE IMAGERIES

    Directory of Open Access Journals (Sweden)

    DK Bhattacharyya

    2010-07-01

    Full Text Available This paper presents an Object oriented feature extraction approach in order to classify the linear features like drainage, roads etc. from high resolution Indian satellite imageries. It starts with the multiresolution segmentations of image objects for optimal separation and representation of image regions or objects. Fuzzy membership functions were defined for a selected set of image object parameters such as mean, ratio, shape index, area etc. for representation of required image objects. Experiment was carried out for both panchromatic (CARTOSAT-I and multispectral (IRSP6 LISS IV Indiansatellite imageries. Experimental results show that the extractionof linear features can be achieved in a satisfactory level throughproper segmentation and appropriate definition & representationof key parameters of image objects.

  13. Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

    Science.gov (United States)

    Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

    2016-06-01

    Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

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

    Science.gov (United States)

    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

  15. Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

    Directory of Open Access Journals (Sweden)

    Dimitris G. Stavrakoudis

    2014-07-01

    Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

  16. On land-use modeling: A treatise of satellite imagery data and misclassification error

    Science.gov (United States)

    Sandler, Austin M.

    Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

  17. Calibration of Numerical Model for Shoreline Change Prediction Using Satellite Imagery Data

    Directory of Open Access Journals (Sweden)

    Sigit Sutikno

    2015-12-01

    Full Text Available This paper presents a method for calibration of numerical model for shoreline change prediction using satellite imagery data in muddy beach. Tanjung Motong beach, a muddy beach that is suffered high abrasion in Rangsang Island, Riau province, Indonesia was picked as study area. The primary numerical modeling tool used in this research was GENESIS (GENEralized Model for Simulating Shoreline change, which has been successfully applied in many case studies of shoreline change phenomena on a sandy beach.The model was calibrated using two extracted coastlines satellite imagery data, such as Landsat-5 TM and Landsat-8 OLI/TIRS. The extracted coastline data were analyzed by using DSAS (Digital Shoreline Analysis System tool to get the rate of shoreline change from 1990 to 2014. The main purpose of the calibration process was to find out the appropriate value for K 1 and K coefficients so that the predicted shoreline change had an acceptable correlation with the output of the satellite data processing. The result of this research showed that the shoreline change prediction had a good correlation with the historical evidence data in Tanjung Motong coast. It means that the GENESIS tool is not only applicable for shoreline prediction in sandy beach but also in muddy beach.

  18. Integrating satellite imagery with simulation modeling to improve burn severity mapping.

    Science.gov (United States)

    Karau, Eva C; Sikkink, Pamela G; Keane, Robert E; Dillon, Gregory K

    2014-07-01

    Both satellite imagery and spatial fire effects models are valuable tools for generating burn severity maps that are useful to fire scientists and resource managers. The purpose of this study was to test a new mapping approach that integrates imagery and modeling to create more accurate burn severity maps. We developed and assessed a statistical model that combines the Relative differenced Normalized Burn Ratio, a satellite image-based change detection procedure commonly used to map burn severity, with output from the Fire Hazard and Risk Model, a simulation model that estimates fire effects at a landscape scale. Using 285 Composite Burn Index (CBI) plots in Washington and Montana as ground reference, we found that an integrated model explained more variability in CBI (R (2) = 0.47) and had lower mean squared error (MSE = 0.28) than image (R (2) = 0.42 and MSE = 0.30) or simulation-based models (R (2) = 0.07 and MSE = 0.49) alone. Overall map accuracy was also highest for maps created with the Integrated Model (63 %). We suspect that Simulation Model performance would greatly improve with higher quality and more accurate spatial input data. Results of this study indicate the potential benefit of combining satellite image-based methods with a fire effects simulation model to create improved burn severity maps.

  19. Aerial Photography and Imagery, Ortho-Corrected, Polk County retained Ayres Associates to acquire digital aerial photography during the spring of 2010 suitable for the production of color orthophotography at a 12-inch ground pixel resolution (approximately 956 sq. miles). The photography was obtained du, Published in 2010, 1:2400 (1in=200ft) scale, Polk County, Wisconsin.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:2400 (1in=200ft) scale, was produced all or in part from Orthoimagery information as of...

  20. Aerial Photography and Imagery, Ortho-Corrected, Aerial photography and scans acquired for a 359 square mile area encompassing the City and County of Denver, City of Glendale, City of Littleton, and the Denver Water Service Area., Published in 2004, 1:7200 (1in=600ft) scale, City & County of Denver.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Aerial Photography and Imagery, Ortho-Corrected dataset, published at 1:7200 (1in=600ft) scale, was produced all or in part from Orthoimagery information as of...