WorldWideScience

Sample records for based satellite image

  1. Biogeography based Satellite Image Classification

    CERN Document Server

    Panchal, V K; Kaur, Navdeep; Kundra, Harish

    2009-01-01

    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternative strategies for satellite image classification so that they may be prepared to select the most appropriate technique for the feature extraction task in hand. This paper is focused on classification of the satellite image of a particular land cover using the theory of Biogeography based Optimization. The original BBO algorithm does not have the inbuilt property of clustering which is required during image classification. Hence modifications have been proposed to the original algorithm and...

  2. Forest inventory improvement based on satellite images

    OpenAIRE

    Jonikavičius, Donatas

    2012-01-01

    The aim of the study – improvement of on-going in Lithuania forest inventories based on satellite images and GIS databases. Specific objective of the study – to explore the possibilities of methods applied for the collection of information from satellite images and GIS databases and its processing in order to determine various Lithuanian forest characteristics, focusing on a variety of forest inventory schemes. 4 The goals of the study: 1. To discuss methodological assumptions for...

  3. Wavelet Based Resolution Enhancement for Low Resolution Satellite Images

    OpenAIRE

    Garg, Akansha; Vardhan Naidu, Sashi; Yahia, Hussein; Singh, Darmendra

    2014-01-01

    Satellite images play a major role in the analysis of land cover, topographic analysis, geosciences etc. There has always existed a tradeoff between the image resolution and the image cost. In this paper, a modified discrete wavelet transform and interpolation based technique is proposed for enhancing the resolution of satellite images having low resolution in such a way that a highly resolved satellite image can be obtained without losing any image information. The advent of DWT has given a ...

  4. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg;

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

  5. Wind Statistics Offshore based on Satellite Images

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete;

    2009-01-01

    Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy......’s Master Environmental Library. At CLS the a priori wind direction is taken from the ECMWF (European Centre of Medium-range Weather Forecasting). It is also possible to use other sources of wind direction e.g. the satellite-based ASCAT wind directions as demonstrated by CLS. The wind direction has to known...... and Irish Seas. Results comparing satellite scatterometer winds to offshore meteorological observations have shown good results, and more comparisons are planned in this respect during the Norsewind project....

  6. Moving Target Information Extraction Based on Single Satellite Image

    Directory of Open Access Journals (Sweden)

    ZHAO Shihu

    2015-03-01

    Full Text Available The spatial and time variant effects in high resolution satellite push broom imaging are analyzed. A spatial and time variant imaging model is established. A moving target information extraction method is proposed based on a single satellite remote sensing image. The experiment computes two airplanes' flying speed using ZY-3 multispectral image and proves the validity of spatial and time variant model and moving information extracting method.

  7. Wind Statistics Offshore based on Satellite Images

    OpenAIRE

    Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete; Nielsen, Morten; Astrup, Poul; Karagali, Ioanna

    2009-01-01

    Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy’s Master Environmental Library. At CLS the a priori wind direction is taken from the ECMWF (European Centre of Medium-range Weather Forecasting). It is also possible to use other sources of wind direc...

  8. Entropy-Based Block Processing for Satellite Image Registration

    Directory of Open Access Journals (Sweden)

    Ikhyun Lee

    2012-11-01

    Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

  9. Superpixel-Based Roughness Measure for Multispectral Satellite Image Segmentation

    Directory of Open Access Journals (Sweden)

    César Antonio Ortiz Toro

    2015-11-01

    Full Text Available The new generation of artificial satellites is providing a huge amount of Earth observation images whose exploitation can report invaluable benefits, both economical and environmental. However, only a small fraction of this data volume has been analyzed, mainly due to the large human resources needed for that task. In this sense, the development of unsupervised methodologies for the analysis of these images is a priority. In this work, a new unsupervised segmentation algorithm for satellite images is proposed. This algorithm is based on the rough-set theory, and it is inspired by a previous segmentation algorithm defined in the RGB color domain. The main contributions of the new algorithm are: (i extending the original algorithm to four spectral bands; (ii the concept of the superpixel is used in order to define the neighborhood similarity of a pixel adapted to the local characteristics of each image; (iii and two new region merged strategies are proposed and evaluated in order to establish the final number of regions in the segmented image. The experimental results show that the proposed approach improves the results provided by the original method when both are applied to satellite images with different spectral and spatial resolutions.

  10. An entropy-based approach to automatic image segmentation of satellite images

    Science.gov (United States)

    Barbieri, Andre L.; de Arruda, G. F.; Rodrigues, Francisco A.; Bruno, Odemir M.; Costa, Luciano da Fontoura

    2011-02-01

    An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation.

  11. An entropy-based approach to automatic image segmentation of satellite images

    CERN Document Server

    Barbieri, A L; Rodrigues, F A; Bruno, O M; Costa, L da F

    2009-01-01

    An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation.

  12. Satellite Image Time Series Decomposition Based on EEMD

    Directory of Open Access Journals (Sweden)

    Yun-long Kong

    2015-11-01

    Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.

  13. 2D Satellite Image Registration Using Transform Based and Correlation Based Methods

    Directory of Open Access Journals (Sweden)

    Dr. H.B. Kekre, Dr. Tanuja K. Sarode, Ms. Ruhina B. Karani

    2012-05-01

    Full Text Available Image registration is the process of geometrically aligning one image to another image of the same scene taken from different viewpoints or by different sensors. It is a fundamental image processing technique and is very useful in integrating information from different sensors, finding changes in images taken at different times and inferring three-dimensional information from stereo images. Image registration can be done by using two matching method: transform based methods and correlation based methods. When image registration is done using correlation based methods like normalized cross correlation, the results are slow. They are also computationally complex and sensitive to the image intensity changes which are caused by noise and varying illumination. In this paper, an unusual form of image registration is proposed which focuses upon using various transforms for fast and accurate image registration. The data set can be a set of photographs, data from various sensors, from different times, or from different viewpoints. The applications of image registration are in the field of computer vision, medical imaging, military automatic target recognition, and in analyzing images and data from satellites. The proposed technique works on satellite images. It tries to find out area of interest by comparing the unregistered image with source image and finding the part that has highest similarity matching. The paper mainly works on the concept of seeking water or land in the stored image. The proposed technique uses different transforms like Discrete Cosine Transform, Discrete Wavelet Transform, HAAR Transform and Walsh transform to achieve accurate image registration. The paper also focuses upon using normalized cross correlation as an area based technique of image registration for the purpose of comparison. The root mean square error is used as similarity measure. Experimental results show that the proposed algorithm can successfully register the

  14. Satellite Imaging System

    Directory of Open Access Journals (Sweden)

    AA Somaie

    2013-06-01

    Full Text Available The aim of this paper is to present the essential elements of the electro-optical imaging system EOIS for space applications and how these elements can affect its function. After designing a spacecraft for low orbiting missions during day time, the design of an electro-imaging system becomes an important part in the satellite because the satellite will be able to take images of the regions of interest. An example of an electro-optical satellite imaging system will be presented through this paper where some restrictions have to be considered during the design process. Based on the optics principals and ray tracing techniques the dimensions of lenses and CCD (Charge Coupled Device detector are changed matching the physical satellite requirements. However, many experiments were done in the physics lab to prove that the resizing of the electro optical elements of the imaging system does not affect the imaging mission configuration. The procedures used to measure the field of view and ground resolution will be discussed through this work. Examples of satellite images will be illustrated to show the ground resolution effects.

  15. Studying Satellite Image Quality Based on the Fusion Techniques

    CERN Document Server

    Al-Wassai, Firouz Abdullah; Al-Zaky, Ali A

    2011-01-01

    Various and different methods can be used to produce high-resolution multispectral images from high-resolution panchromatic image (PAN) and low-resolution multispectral images (MS), mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its original images. There is also a lack of measures for assessing the objective quality of the spatial resolution for the fusion methods. Therefore, an objective quality of the spatial resolution assessment for fusion images is required. So, this study attempts to develop a new qualitative assessment to evaluate the spatial quality of the pan sharpened images by many spatial quality metrics. Also, this paper deals with a comparison of various image fusion techniques based on pixel and feature fusion techniques.

  16. Biomass prediction model in maize based on satellite images

    Science.gov (United States)

    Mihai, Herbei; Florin, Sala

    2016-06-01

    Monitoring of crops by satellite techniques is very useful in the context of precision agriculture, regarding crops management and agricultural production. The present study has evaluated the interrelationship between maize biomass production and satellite indices (NDVI and NDBR) during five development stages (BBCH code), highlighting different levels of correlation. Biomass production recorded was between 2.39±0.005 t ha-1 (12-13 BBCH code) and 51.92±0.028 t ha-1 (83-85 BBCH code), in relation to vegetation stages studied. Values of chlorophyll content ranged from 24.1±0.25 SPAD unit (12-13 BBCH code) to 58.63±0.47 SPAD unit (71-73 BBCH code), and the obtained satellite indices ranged from 0.035641±0.002 and 0.320839±0.002 for NDVI indices respectively 0.035095±0.034 and 0.491038±0.018 in the case of NDBR indices. By regression analysis it was possible to obtain predictive models of biomass in maize based on the satellite indices, in statistical accurate conditions. The most accurate prediction was possible based on NDBR index (R2 = 0.986, F = 144.23, p<0.001, RMSE = 1.446), then based on chlorophyll content (R2 = 0.834, F = 16.14, p = 0.012, RMSE = 6.927) and NDVI index (R2 = 0.682, F = 3.869, p = 0.116, RMSE = 12.178).

  17. Region of Interest Detection Based on Histogram Segmentation for Satellite Image

    Science.gov (United States)

    Kiadtikornthaweeyot, Warinthorn; Tatnall, Adrian R. L.

    2016-06-01

    High resolution satellite imaging is considered as the outstanding applicant to extract the Earth's surface information. Extraction of a feature of an image is very difficult due to having to find the appropriate image segmentation techniques and combine different methods to detect the Region of Interest (ROI) most effectively. This paper proposes techniques to classify objects in the satellite image by using image processing methods on high-resolution satellite images. The systems to identify the ROI focus on forests, urban and agriculture areas. The proposed system is based on histograms of the image to classify objects using thresholding. The thresholding is performed by considering the behaviour of the histogram mapping to a particular region in the satellite image. The proposed model is based on histogram segmentation and morphology techniques. There are five main steps supporting each other; Histogram classification, Histogram segmentation, Morphological dilation, Morphological fill image area and holes and ROI management. The methods to detect the ROI of the satellite images based on histogram classification have been studied, implemented and tested. The algorithm is be able to detect the area of forests, urban and agriculture separately. The image segmentation methods can detect the ROI and reduce the size of the original image by discarding the unnecessary parts.

  18. Autonomous Sub-Pixel Satellite Track Endpoint Determination for Space Based Images

    Energy Technology Data Exchange (ETDEWEB)

    Simms, L M

    2011-03-07

    An algorithm for determining satellite track endpoints with sub-pixel resolution in spaced-based images is presented. The algorithm allows for significant curvature in the imaged track due to rotation of the spacecraft capturing the image. The motivation behind the subpixel endpoint determination is first presented, followed by a description of the methodology used. Results from running the algorithm on real ground-based and simulated spaced-based images are shown to highlight its effectiveness.

  19. Detecting Anomaly Regions in Satellite Image Time Series Based on Sesaonal Autocorrelation Analysis

    Science.gov (United States)

    Zhou, Z.-G.; Tang, P.; Zhou, M.

    2016-06-01

    Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they are generally designed for detecting inter-annual or abrupt land cover changes, but are not focusing on detecting spatial-temporal changes in continuous images. In order to identify spatial-temporal dynamic processes of unexpected changes of land cover, this study proposes a method for detecting anomaly regions in each image of satellite image time series based on seasonal autocorrelation analysis. The method was validated with a case study to detect spatial-temporal processes of a severe flooding using Terra/MODIS image time series. Experiments demonstrated the advantages of the method that (1) it can effectively detect anomaly regions in each of satellite image time series, showing spatial-temporal varying process of anomaly regions, (2) it is flexible to meet some requirement (e.g., z-value or significance level) of detection accuracies with overall accuracy being up to 89% and precision above than 90%, and (3) it does not need time series smoothing and can detect anomaly regions in noisy satellite images with a high reliability.

  20. An Image-Based Sensor System for Autonomous Rendez-Vous with Uncooperative Satellites

    CERN Document Server

    Miravet, Carlos; Krouch, Eloise; del Cura, Juan Manuel

    2008-01-01

    In this paper are described the image processing algorithms developed by SENER, Ingenieria y Sistemas to cope with the problem of image-based, autonomous rendez-vous (RV) with an orbiting satellite. The methods developed have a direct application in the OLEV (Orbital Life Extension Extension Vehicle) mission. OLEV is a commercial mission under development by a consortium formed by Swedish Space Corporation, Kayser-Threde and SENER, aimed to extend the operational life of geostationary telecommunication satellites by supplying them control, navigation and guidance services. OLEV is planned to use a set of cameras to determine the angular position and distance to the client satellite during the complete phases of rendez-vous and docking, thus enabling the operation with satellites not equipped with any specific navigational aid to provide support during the approach. The ability to operate with un-equipped client satellites significantly expands the range of applicability of the system under development, compar...

  1. Radiation exposure near Chernobyl based on analysis of satellite images

    International Nuclear Information System (INIS)

    Radiation-induced damage in conifers adjacent to the damaged Chernobyl nuclear power plant has been evaluated using LANDSAT Thematic Mapper satellite images. Eight images acquired between April 22, 1986 and May 15, 1987 were used to assess the extent and magnitude of radiation effects on pine trees within 10 km of the reactor site. The timing and spatial extent of vegetation damaged was used to estimate the radiation doses in the near field around the Chernobyl nuclear power station and to derive dose rates as a function of time during and after the accident. A normalized vegetation index was developed from the TM spectral band data to visually demonstrate the damage and mortality to nearby conifer stands. The earliest date showing detectable injury 1 km west of the reactor unit was June 16, 1986. Subsequent dates revealed continued expansion of the affected areas to the west, north, and south. The greatest aerial expansion of this area occurred by October 15, 1986, with vegetation changes evident up to 5 km west, 2 km south, and 2 km north of the damaged Reactor Unit 4. By May 11, 1987, further scene changes were due principally to removal and mitigation efforts by the Soviet authorities. Areas showing spectral evidence of vegetation damage during the previous growing season do not show evidence of recovery and reflectance in the TM Bands 4 and 3 remain higher than surrounding vegetation, which infers that the trees are dead. The patterns of spectral change indicative of vegetation stress are consistent with changes expected for radiation injury and mortality. The extent and the timing of these effects enabled developing an integrated radiation dose estimate, which was combined with the information regarding the characteristics of radionuclide mix to provide an estimate of maximum dose rates during the early period of the accident. The derived peak dose rates during the 10-day release in the accident are high and are estimated at about 0.5 to 1 rad per hour. These

  2. Rule extraction based on neural networks for satellite image interpretation

    Science.gov (United States)

    Mascarilla, Laurent

    1994-12-01

    In the frame of an image interpretation system for automatic cartography based on remote sensing image classification improved by a photo interpreter knowledge, we propose a system using neural networks to produce fuzzy production rules. These rules are intended to describe class vegetation context relatively to out image data (generally a G.I.S.) as a human expert could do. In the system, the expert only gives samples of concerned classes via a G.U.I. (Graphic User Interface) connected to a G.I.S. In a first stage, a Kohonen neural network is used to found clusters and membership functions, and then to compute a first set of fuzzy 'IF-THEN' rules with certainty factors. The human expert then updates these rules, and the given samples, according to his own experience. Once satisfying and discriminating classification rules are found, a second kind of neural network using back propagation is used to tune the final set of rules. At the same time, it produces neural nets able to give for each pixel and each class, the realisation degree of the favourable context relatively to the knowledge inferred by the samples.

  3. Studying Satellite Image Quality Based on the Fusion Techniques

    OpenAIRE

    Al-Wassai, Firouz Abdullah; Kalyankar, N. V.; Al-Zaky, Ali A.

    2011-01-01

    Various and different methods can be used to produce high-resolution multispectral images from high-resolution panchromatic image (PAN) and low-resolution multispectral images (MS), mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its original images. There is also a lack of measures for assessing the objective quality of the spatial resolution for the fusion methods. Therefore, an objective quality of the spatial resolution assessment for...

  4. Image sets for satellite image processing systems

    Science.gov (United States)

    Peterson, Michael R.; Horner, Toby; Temple, Asael

    2011-06-01

    The development of novel image processing algorithms requires a diverse and relevant set of training images to ensure the general applicability of such algorithms for their required tasks. Images must be appropriately chosen for the algorithm's intended applications. Image processing algorithms often employ the discrete wavelet transform (DWT) algorithm to provide efficient compression and near-perfect reconstruction of image data. Defense applications often require the transmission of images and video across noisy or low-bandwidth channels. Unfortunately, the DWT algorithm's performance deteriorates in the presence of noise. Evolutionary algorithms are often able to train image filters that outperform DWT filters in noisy environments. Here, we present and evaluate two image sets suitable for the training of such filters for satellite and unmanned aerial vehicle imagery applications. We demonstrate the use of the first image set as a training platform for evolutionary algorithms that optimize discrete wavelet transform (DWT)-based image transform filters for satellite image compression. We evaluate the suitability of each image as a training image during optimization. Each image is ranked according to its suitability as a training image and its difficulty as a test image. The second image set provides a test-bed for holdout validation of trained image filters. These images are used to independently verify that trained filters will provide strong performance on unseen satellite images. Collectively, these image sets are suitable for the development of image processing algorithms for satellite and reconnaissance imagery applications.

  5. Topic Modelling for Object-Based Classification of Vhr Satellite Images Based on Multiscale Segmentations

    Science.gov (United States)

    Shen, Li; Wu, Linmei; Li, Zhipeng

    2016-06-01

    Multiscale segmentation is a key prerequisite step for object-based classification methods. However, it is often not possible to determine a sole optimal scale for the image to be classified because in many cases different geo-objects and even an identical geo-object may appear at different scales in one image. In this paper, an object-based classification method based on mutliscale segmentation results in the framework of topic modelling is proposed to classify VHR satellite images in an entirely unsupervised fashion. In the stage of topic modelling, grayscale histogram distributions for each geo-object class and each segment are learned in an unsupervised manner from multiscale segments. In the stage of classification, each segment is allocated a geo-object class label by the similarity comparison between the grayscale histogram distributions of each segment and each geo-object class. Experimental results show that the proposed method can perform better than the traditional methods based on topic modelling.

  6. Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD.

    Science.gov (United States)

    Bhandari, A K; Soni, V; Kumar, A; Singh, G K

    2014-07-01

    This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques. PMID:24893835

  7. Thermal Physical Property-Based Fusion of Geostationary Meteorological Satellite Visible and Infrared Channel Images

    Directory of Open Access Journals (Sweden)

    Lei Han

    2014-06-01

    Full Text Available Geostationary meteorological satellite infrared (IR channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties.

  8. Automatic registration of geometric distortions in satellite images based on control points

    International Nuclear Information System (INIS)

    This paper presents an automatic registration scheme to register geometric distortion in satellite images; A novel feature based matching scheme is proposed which establishes correspondence between the corner points in the reference and target images either by correlating the intensity values around a circular neighborhood of these corner points or by exploiting the relative orientation of lines connecting these corner points. Affine transformation model is used to estimate transformation parameters. Re-sampling is carried out by nearest neighborhood interpolation. The registration process is automatic and can efficiently serve as preprocessing stage for multitemporal analysis, image fusion, image mosaicking and change detection. The effectiveness of the algorithm has been verified by an intensive experiment on a large number of real images. Experimental results reveal high supremacy of the proposed registration method. (author)

  9. Multispectral satellite image understanding

    CERN Document Server

    Unsalan, Cem

    2011-01-01

    This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, this book describes a system for the effective detection of single houses and streets in very high resolution. It features a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center. This title provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a

  10. Image Fusion-Based Change Detection for Flood Extent Extraction Using Bi-Temporal Very High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Younggi Byun

    2015-08-01

    Full Text Available Change detection based on satellite images acquired from an area at different dates is of widespread interest, according to the increasing number of flood-related disasters. The images help to generate products that support emergency response and flood management at a global scale. In this paper, a novel unsupervised change detection approach based on image fusion is introduced. The approach aims to extract the reliable flood extent from very high-resolution (VHR bi-temporal images. The method takes an advantage of the spectral distortion that occurs during image fusion process to detect the change areas by flood. To this end, a change candidate image is extracted from the fused image generated with bi-temporal images by considering a local spectral distortion. This can be done by employing a universal image quality index (UIQI, which is a measure for local evaluation of spectral distortion. The decision threshold for the determination of changed pixels is set by applying a probability mixture model to the change candidate image based on expectation maximization (EM algorithm. We used bi-temporal KOMPSAT-2 satellite images to detect the flooded area in the city of N′djamena in Chad. The performance of the proposed method was visually and quantitatively compared with existing change detection methods. The results showed that the proposed method achieved an overall accuracy (OA = 75.04 close to that of the support vector machine (SVM-based supervised change detection method. Moreover, the proposed method showed a better performance in differentiating the flooded area and the permanent water body compared to the existing change detection methods.

  11. 2D Satellite Image Registration Using Transform Based and Correlation Based Methods

    OpenAIRE

    Dr. H.B. Kekre, Dr. Tanuja K. Sarode, Ms. Ruhina B. Karani

    2012-01-01

    Image registration is the process of geometrically aligning one image to another image of the same scene taken from different viewpoints or by different sensors. It is a fundamental image processing technique and is very useful in integrating information from different sensors, finding changes in images taken at different times and inferring three-dimensional information from stereo images. Image registration can be done by using two matching method: transform based methods and correlation ba...

  12. A data mining based approach to predict spatiotemporal changes in satellite images

    Science.gov (United States)

    Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben

    2011-06-01

    The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

  13. Simulation of seagrass bed mapping by satellite images based on the radiative transfer model

    Science.gov (United States)

    Sagawa, Tatsuyuki; Komatsu, Teruhisa

    2015-06-01

    Seagrass and seaweed beds play important roles in coastal marine ecosystems. They are food sources and habitats for many marine organisms, and influence the physical, chemical, and biological environment. They are sensitive to human impacts such as reclamation and pollution. Therefore, their management and preservation are necessary for a healthy coastal environment. Satellite remote sensing is a useful tool for mapping and monitoring seagrass beds. The efficiency of seagrass mapping, seagrass bed classification in particular, has been evaluated by mapping accuracy using an error matrix. However, mapping accuracies are influenced by coastal environments such as seawater transparency, bathymetry, and substrate type. Coastal management requires sufficient accuracy and an understanding of mapping limitations for monitoring coastal habitats including seagrass beds. Previous studies are mainly based on case studies in specific regions and seasons. Extensive data are required to generalise assessments of classification accuracy from case studies, which has proven difficult. This study aims to build a simulator based on a radiative transfer model to produce modelled satellite images and assess the visual detectability of seagrass beds under different transparencies and seagrass coverages, as well as to examine mapping limitations and classification accuracy. Our simulations led to the development of a model of water transparency and the mapping of depth limits and indicated the possibility for seagrass density mapping under certain ideal conditions. The results show that modelling satellite images is useful in evaluating the accuracy of classification and that establishing seagrass bed monitoring by remote sensing is a reliable tool.

  14. High Resolution Imaging of Satellites with Ground-Based 10-m Astronomical Telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Marois, C

    2007-01-04

    High resolution imaging of artificial satellites can play an important role in current and future space endeavors. One such use is acquiring detailed images that can be used to identify or confirm damage and aid repair plans. It is shown that a 10-m astronomical telescope equipped with an adaptive optics system (AO) to correct for atmospheric turbulence using a natural guide star can acquire high resolution images of satellites in low-orbits using a fast shutter and a near-infrared camera even if the telescope is not capable of tracking satellites. With the telescope pointing towards the satellite projected orbit and less than 30 arcsec away from a guide star, multiple images of the satellite are acquired on the detector using the fast shutter. Images can then be shifted and coadded by post processing to increase the satellite signal to noise ratio. Using the Keck telescope typical Strehl ratio and anisoplanatism angle as well as a simple diffusion/reflection model for a satellite 400 km away observed near Zenith at sunset or sunrise, it is expected that such system will produced > 10{sigma} K-band images at a resolution of 10 cm inside a 60 arcsec diameter field of view. If implemented, such camera could deliver the highest resolution satellite images ever acquired from the ground.

  15. Satellite Image Pansharpening Using a Hybrid Approach for Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Nguyen Thanh Hoan

    2012-10-01

    Full Text Available Intensity-Hue-Saturation (IHS, Brovey Transform (BT, and Smoothing-Filter-Based-Intensity Modulation (SFIM algorithms were used to pansharpen GeoEye-1 imagery. The pansharpened images were then segmented in Berkeley Image Seg using a wide range of segmentation parameters, and the spatial and spectral accuracy of image segments was measured. We found that pansharpening algorithms that preserve more of the spatial information of the higher resolution panchromatic image band (i.e., IHS and BT led to more spatially-accurate segmentations, while pansharpening algorithms that minimize the distortion of spectral information of the lower resolution multispectral image bands (i.e., SFIM led to more spectrally-accurate image segments. Based on these findings, we developed a new IHS-SFIM combination approach, specifically for object-based image analysis (OBIA, which combined the better spatial information of IHS and the more accurate spectral information of SFIM to produce image segments with very high spatial and spectral accuracy.

  16. Recognization of Satellite Images of Large Scale Data Based on Map- Reduce Framework

    Directory of Open Access Journals (Sweden)

    Vidya Jadhav,

    2014-03-01

    Full Text Available Today in the world of cloud and grid computing integration of data from heterogeneous databases is inevitable.This will become complex when size of the database is very large. M-R is a new framework specifically designed for processing huge datasets on distributed sources. Apache’s Hadoop is an implementation of M-R.Currently Hadoop has been applied successfully for file based datasets. This project proposes to utilize the parallel and distributed processing capability of Hadoop M-R for handling Images on large datasets.The presented methodology of land-cover recognition provides a scalable solution for automatic satellite imagery analysis, especially when GIS data is not readily available, or surface change may occur due to catastrophic events such as flooding, hurricane, and snow storm, etc.Here,we are using algorithms such as Image Differentiation,Image Duplication,Zoom-In,Gray-Scale.

  17. Object-based landslide mapping on satellite images from different sensors

    Science.gov (United States)

    Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens; Blaschke, Thomas

    2015-04-01

    Several studies have proven that object-based image analysis (OBIA) is a suitable approach for landslide mapping using remote sensing data. Mostly, optical satellite images are utilized in combination with digital elevation models (DEMs) for semi-automated mapping. The ability of considering spectral, spatial, morphometric and contextual features in OBIA constitutes a significant advantage over pixel-based methods, especially when analysing non-uniform natural phenomena such as landslides. However, many of the existing knowledge-based OBIA approaches for landslide mapping are rather complex and are tailored to specific data sets. These restraints lead to a lack of transferability of OBIA mapping routines. The objective of this study is to develop an object-based approach for landslide mapping that is robust against changing input data with different resolutions, i.e. optical satellite imagery from various sensors. Two study sites in Taiwan were selected for developing and testing the landslide mapping approach. One site is located around the Baolai village in the Huaguoshan catchment in the southern-central part of the island, the other one is a sub-area of the Taimali watershed in Taitung County near the south-eastern Pacific coast. Both areas are regularly affected by severe landslides and debris flows. A range of very high resolution (VHR) optical satellite images was used for the object-based mapping of landslides and for testing the transferability across different sensors and resolutions: (I) SPOT-5, (II) Formosat-2, (III) QuickBird, and (IV) WorldView-2. Additionally, a digital elevation model (DEM) with 5 m spatial resolution and its derived products (e.g. slope, plan curvature) were used for supporting the semi-automated mapping, particularly for differentiating source areas and accumulation areas according to their morphometric characteristics. A focus was put on the identification of comparatively stable parameters (e.g. relative indices), which could be

  18. Region-based urban road extraction from VHR satellite images using Binary Partition Tree

    Science.gov (United States)

    Li, Mengmeng; Stein, Alfred; Bijker, Wietske; Zhan, Qingming

    2016-02-01

    This paper provides a hierarchical method for urban road extraction. It consists of (1) obtaining the road region of interest from a VHR image, (2) hierarchically representing this road region of interest in a Binary Partition Tree (BPT), and extracting the roads based on this BPT at hierarchical levels. Besides using two existing geometrical features (i.e. compactness and elongation), we define two other structural features based on orientation histograms and morphological profiles to guide the region merging of BPT. The morphological profiles are constructed using a series of path openings, which facilitate modeling linear or curved structures. The proposed method was applied to two types of VHR images with different urban settings, corresponding to a Pléiades-B image of Wuhan, China, and a Quickbird image of Enschede, the Netherlands. Experimental results show that the proposed method was able to group adjacent small segments that have high spectral heterogeneity and low road-like geometrical properties to form more meaningful roads sections, and performed superior to the existing methods. Furthermore, we compared the proposed method with two other existing methods in the literature. We conclude that the proposed method can provide an effective means for extracting roads over densely populated urban areas from VHR satellite images.

  19. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  20. Super Resolution Reconstruction Based on Adaptive Detail Enhancement for ZY-3 Satellite Images

    Science.gov (United States)

    Zhu, Hong; Song, Weidong; Tan, Hai; Wang, Jingxue; Jia, Di

    2016-06-01

    Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

  1. An image based information system - Architecture for correlating satellite and topological data bases

    Science.gov (United States)

    Bryant, N. A.; Zobrist, A. L.

    1978-01-01

    The paper describes the development of an image based information system and its use to process a Landsat thematic map showing land use or land cover in conjunction with a census tract polygon file to produce a tabulation of land use acreages per census tract. The system permits the efficient cross-tabulation of two or more geo-coded data sets, thereby setting the stage for the practical implementation of models of diffusion processes or cellular transformation. Characteristics of geographic information systems are considered, and functional requirements, such as data management, geocoding, image data management, and data analysis are discussed. The system is described, and the potentialities of its use are examined.

  2. Satellite image classification using convolutional learning

    Science.gov (United States)

    Nguyen, Thao; Han, Jiho; Park, Dong-Chul

    2013-10-01

    A satellite image classification method using Convolutional Neural Network (CNN) architecture is proposed in this paper. As a special case of deep learning, CNN classifies classes of images without any feature extraction step while other existing classification methods utilize rather complex feature extraction processes. Experiments on a set of satellite image data and the preliminary results show that the proposed classification method can be a promising alternative over existing feature extraction-based schemes in terms of classification accuracy and classification speed.

  3. Top-Down Visual Saliency Detection in Optical Satellite Images Based on Local Adaptive Regression Kernel

    Directory of Open Access Journals (Sweden)

    Xiaoguang Cui

    2014-01-01

    Full Text Available This paper proposes a novel top-down visual saliency detection method for optical satellite images using local adaptive regression kernels. This method provides a saliency map by measuring the likeness of image patches to a given single template image. The local adaptive regression kernel (LARK is used as a descriptor to extract feature and compare against analogous feature from the target image. A multi-scale pyramid of the target image is constructed to cope with large-scale variations. In addition, accounting for rotation variations, the histogram of kernel orientation is employed to estimate the rotation angle of image patch, and then comparison is performed after rotating the patch by the estimated angle. Moreover, we use the bounded partial correlation (BPC to compare features between image patches and the template so as to rapidly generate the saliency map. Experiments were performed in optical satellite images to find airplanes, and experimental results demonstrate that the proposed method is effective and robust in complex scenes.

  4. THE ANALYSIS OF MOISTURE DEFICIT BASED ON MODIS AND LANDSAT SATELLITE IMAGES. CASE STUDY: THE OLTENIA PLAIN

    Directory of Open Access Journals (Sweden)

    ONȚEL IRINA

    2014-03-01

    Full Text Available Satellite images are an important source of information to identify and analyse some hazardous climatic phenomena such as the dryness and drought. These phenomena are characterized by scarce rainfall, increased evapotranspiration and high soil moisture deficit. The soil water reserve depletes to the wilting coefficient, soon followed by the pedological drought which has negative effects on vegetation and agricultural productivity. The MODIS satellite images (Moderate Resolution Imaging Spectroradiometer allow the monitoring of the vegetation throughout the entire vegetative period, with a frequency of 1-2 days and with a spatial resolution of 250 m, 500 m and 1 km away. Another useful source of information is the LANDSAT satellite images, with a spatial resolution of 30 m. Based on MODIS and Landsat satellite images, were calculated moisture monitoring index such as SIWSI (Shortwave Infrared Water Stress Index. Consequently, some years with low moisture such as 2000, 2002, 2007 and 2012 could be identified. Spatially, the areas with moisture deficit varied from one year to another all over the whole analised period (2000-2012. The remote sensing results was corelated with Standard Precipitation Anomaly, which gives a measure of the severity of a wet or dry event.

  5. Using PACS and wavelet-based image compression in a wide-area network to support radiation therapy imaging applications for satellite hospitals

    Science.gov (United States)

    Smith, Charles L.; Chu, Wei-Kom; Wobig, Randy; Chao, Hong-Yang; Enke, Charles

    1999-07-01

    An ongoing PACS project at our facility has been expanded to include providing and managing images used for routine clinical operation of the department of radiation oncology. The intent of our investigation has been to enable out clinical radiotherapy service to enter the tele-medicine environment through the use of a PACS system initially implemented in the department of radiology. The backbone for the imaging network includes five CT and three MR scanners located across three imaging centers. A PC workstation in the department of radiation oncology was used to transmit CT imags to a satellite facility located approximately 60 miles from the primary center. Chest CT images were used to analyze network transmission performance. Connectivity established between the primary department and satellite has fulfilled all image criteria required by the oncologist. Establishing the link tot eh oncologist at the satellite diminished bottlenecking of imaging related tasks at the primary facility due to physician absence. A 30:1 compression ratio using a wavelet-based algorithm provided clinically acceptable images treatment planning. Clinical radiotherapy images can be effectively managed in a wide- area-network to link satellite facilities to larger clinical centers.

  6. Satellite Images-based Obstacle Recognition and Trajectory Generation for Agricultural Vehicles

    Directory of Open Access Journals (Sweden)

    Mehmet Bodur

    2015-12-01

    Full Text Available In this study, a method for the generation of tracking trajectory points, detection and positioning of obstacles in agricultural fields have been presented. Our principal contribution is to produce traceable GPS trajectories for agricultural vehicles to be utilized by path planning algorithms, rather than a new path planning algorithm. The proposed system works with minimal initialization requirements, specifically, a single geographical coordinate entry of an agricultural field. The automation of agricultural plantation requires many aspects to be addressed, many of which have been covered in previous studies. Depending on the type of crop, different agricultural vehicles may be used in the field. However, regardless of their application, they all follow a specified trajectory in the field. This study takes advantage of satellite images for the detection and positioning of obstacles, and the generation of GPS trajectories in the agricultural realm. A set of image processing techniques is applied in Matlab for detection and positioning.

  7. Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

    Science.gov (United States)

    Osipov, Gennady

    2013-04-01

    We propose a solution to the problem of exploration of various mineral resource deposits, determination of their forms / classification of types (oil, gas, minerals, gold, etc.) with the help of satellite photography of the region of interest. Images received from satellite are processed and analyzed to reveal the presence of specific signs of deposits of various minerals. Course of data processing and making forecast can be divided into some stages: Pre-processing of images. Normalization of color and luminosity characteristics, determination of the necessary contrast level and integration of a great number of separate photos into a single map of the region are performed. Construction of semantic map image. Recognition of bitmapped image and allocation of objects and primitives known to system are realized. Intelligent analysis. At this stage acquired information is analyzed with the help of a knowledge base, which contain so-called "attention landscapes" of experts. Used methods of recognition and identification of images: a) combined method of image recognition, b)semantic analysis of posterized images, c) reconstruction of three-dimensional objects from bitmapped images, d)cognitive technology of processing and interpretation of images. This stage is fundamentally new and it distinguishes suggested technology from all others. Automatic registration of allocation of experts` attention - registration of so-called "attention landscape" of experts - is the base of the technology. Landscapes of attention are, essentially, highly effective filters that cut off unnecessary information and emphasize exactly the factors used by an expert for making a decision. The technology based on denoted principles involves the next stages, which are implemented in corresponding program agents. Training mode -> Creation of base of ophthalmologic images (OI) -> Processing and making generalized OI (GOI) -> Mode of recognition and interpretation of unknown images. Training mode

  8. Satellite Angular Velocity Estimation Based on Star Images and Optical Flow Techniques

    OpenAIRE

    Giancarmine Fasano; Giancarlo Rufino; Domenico Accardo; Michele Grassi

    2013-01-01

    An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares...

  9. A Web-based Google-Earth Coincident Imaging Tool for Satellite Calibration and Validation

    Science.gov (United States)

    Killough, B. D.; Chander, G.; Gowda, S.

    2009-12-01

    The Group on Earth Observations (GEO) is coordinating international efforts to build a Global Earth Observation System of Systems (GEOSS) to meet the needs of its nine “Societal Benefit Areas”, of which the most demanding, in terms of accuracy, is climate. To accomplish this vision, satellite on-orbit and ground-based data calibration and validation (Cal/Val) of Earth observation measurements are critical to our scientific understanding of the Earth system. Existing tools supporting space mission Cal/Val are often developed for specific campaigns or events with little desire for broad application. This paper describes a web-based Google-Earth based tool for the calculation of coincident satellite observations with the intention to support a diverse international group of satellite missions to improve data continuity, interoperability and data fusion. The Committee on Earth Observing Satellites (CEOS), which includes 28 space agencies and 20 other national and international organizations, are currently operating and planning over 240 Earth observation satellites in the next 15 years. The technology described here will better enable the use of multiple sensors to promote increased coordination toward a GEOSS. The CEOS Systems Engineering Office (SEO) and the Working Group on Calibration and Validation (WGCV) support the development of the CEOS Visualization Environment (COVE) tool to enhance international coordination of data exchange, mission planning and Cal/Val events. The objective is to develop a simple and intuitive application tool that leverages the capabilities of Google-Earth web to display satellite sensor coverage areas and for the identification of coincident scene locations along with dynamic menus for flexibility and content display. Key features and capabilities include user-defined evaluation periods (start and end dates) and regions of interest (rectangular areas) and multi-user collaboration. Users can select two or more CEOS missions from a

  10. Patch-based image segmentation of satellite imagery using minimum spanning tree construction

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2010-01-01

    We present a method for hierarchical image segmentation and feature extraction. This method builds upon the combination of the detection of image spectral discontinuities using Canny edge detection and the image Laplacian, followed by the construction of a hierarchy of segmented images of successively reduced levels of details. These images are represented as sets of polygonized pixel patches (polygons) attributed with spectral and structural characteristics. This hierarchy forms the basis for object-oriented image analysis. To build fine level-of-detail representation of the original image, seed partitions (polygons) are built upon a triangular mesh composed of irregular sized triangles, whose spatial arrangement is adapted to the image content. This is achieved by building the triangular mesh on the top of the detected spectral discontinuities that form a network of constraints for the Delaunay triangulation. A polygonized image is represented as a spatial network in the form of a graph with vertices which correspond to the polygonal partitions and graph edges reflecting pairwise partitions relations. Image graph partitioning is based on the iterative graph oontraction using Boruvka's Minimum Spanning Tree algorithm. An important characteristic of the approach is that the agglomeration of partitions is constrained by the detected spectral discontinuities; thus the shapes of agglomerated partitions are more likely to correspond to the outlines of real-world objects.

  11. Post-earthquake road damage assessment using region-based algorithms from high-resolution satellite images

    Science.gov (United States)

    Haghighattalab, A.; Mohammadzadeh, A.; Valadan Zoej, M. J.; Taleai, M.

    2010-10-01

    Receiving accurate and comprehensive knowledge about the conditions of roads after earthquake strike are crucial in finding optimal paths and coordinating rescue missions. Continuous coverage of the disaster region and rapid access of high-resolution satellite images make this technology as a useful and powerful resource for post-earthquake damage assessment and the evaluation process. Along with this improved technology, object-oriented classification has become a promising alternative for classifying high-resolution remote sensing imagery, such as QuickBird, Ikonos. Thus, in this study, a novel approach is proposed for the automatic detection and assessment of damaged roads in urban areas based on object based classification techniques using post-event satellite image and vector map. The most challenging phase of the proposed region-based algorithm is the segmentation procedure. The extracted regions are then classified using nearest neighbor classifier making use of textural parameters. Then, an appropriate fuzzy inference system (FIS) is proposed for road damage assessment. Finally, the roads are correctly labeled as 'Blocked road' or 'Unblocked road' in the road damage assessment step. The proposed method was tested on QuickBird pan-sharpened image of Bam, Iran, concerning the devastating earthquake that occurred in December 2003. The visual investigation of the obtained results demonstrates the efficiency of the proposed approach.

  12. Using optical remote sensing model to estimate oil slick thickness based on satellite image

    International Nuclear Information System (INIS)

    An optical remote sensing model has been established based on two-beam interference theory to estimate marine oil slick thickness. Extinction coefficient and normalized reflectance of oil are two important parts in this model. Extinction coefficient is an important inherent optical property and will not vary with the background reflectance changed. Normalized reflectance can be used to eliminate the background differences between in situ measured spectra and remotely sensing image. Therefore, marine oil slick thickness and area can be estimated and mapped based on optical remotely sensing image and extinction coefficient

  13. Radiation exposure near Chernobyl based on analysis of conifer injury using thematic mapper satellite images

    International Nuclear Information System (INIS)

    Radiation-induced damage in conifers adjacent to the damaged Chernobyl nuclear power plant has been evaluated using LANDSAT Thematic Mapper (TM) satellite images. Eight images acquired between 22 April 1986 and 15 May 1987 were used to assess the extent and magnitude of radiation effects on pine trees within 10 km of the reactor site. The timing and spatial extent of vegetation damaged was used to estimate the radiation doses in the near field around the Chernobyl nuclear power station and to indirectly derive the dose rates as a function of time during and after the accident. A normalized vegetation index was developed from the TM band data to visually demonstrate the damage and mortality to nearby conifer stands. The patterns of spectral change indicative of vegetation stress are consistent with changes expected for radiation injury and mortality. The extent and timing of these effects permitted the development of an integrated dose estimate, which was combined with the information regarding the characteristics of radionuclide mix, to provide an estimate of maximum dose rates during the early period of the accident. The derived peak dose rates during the 10-day release in the accident are high and are estimated at about 0.5 to 1 rad per hour. These are not considered life-threatening and would therefore require prompt but not immediate evacuation; that is, no off-site fatalities would be likely under such conditions. The methodology employed to combine remote-sensing analyses and the estimates of source term release with the known radiation effects on conifers represent a unique integration of these scientific and technical tools. The results of the study show that remote-sensing techniques can be used to develop a quantitative methodology for dosimetric applications and for future monitoring activities related to reactor safety

  14. Learning-based roof style classification in 2D satellite images

    Science.gov (United States)

    Zang, Andi; Zhang, Xi; Chen, Xin; Agam, Gady

    2015-05-01

    Accurately recognizing building roof style leads to a much more realistic 3D building modeling and rendering. In this paper, we propose a novel system for image based roof style classification using machine learning technique. Our system is capable of accurately recognizing four individual roof styles and a complex roof which is composed of multiple parts. We make several novel contributions in this paper. First, we propose an algorithm that segments a complex roof to parts which enable our system to recognize the entire roof based on recognition of each part. Second, to better characterize a roof image, we design a new feature extracted from a roof edge image. We demonstrate that this feature has much better performance compared to recognition results generated by Histogram of Oriented Gradient (HOG), Scale-invariant Feature Transform (SIFT) and Local Binary Patterns (LBP). Finally, to generate a classifier, we propose a learning scheme that trains the classifier using both synthetic and real roof images. Experiment results show that our classifier performs well on several test collections.

  15. Heterogeneous computing system with GPU-based IDWT and CPU-based SPIHT and Reed-Solomon decoding for satellite image decompression

    Science.gov (United States)

    Song, Changhe; Li, Yunsong; Huang, Bormin

    2011-10-01

    The discrete wavelet transform (DWT)-based Set Partitioning in Hierarchical Trees (SPIHT) algorithm is widely used in many image compression systems. In order to perform real-time Reed-Solomon channel decoding and SPIHT+DWT source decoding on a massive bit stream of compressed images continuously down-linked from the satellite, we propose a novel graphic processing unit (GPU)-accelerated decoding system. In this system the GPU is used to compute the time-consuming inverse DWT, while multiple CPU threads are run in parallel for the remaining part of the system. Both CPU and GPU parts were carefully designed to have approximately the same processing speed to obtain the maximum throughput via a novel pipeline structure for processing continuous satellite images. Through the pipelined CPU and GPU heterogeneous computing, the entire decoding system approaches a speedup of 84x as compared to its single-threaded CPU counterpart.

  16. Satellite angular velocity estimation based on star images and optical flow techniques.

    Science.gov (United States)

    Fasano, Giancarmine; Rufino, Giancarlo; Accardo, Domenico; Grassi, Michele

    2013-01-01

    An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components. PMID:24072023

  17. Satellite Angular Velocity Estimation Based on Star Images and Optical Flow Techniques

    Directory of Open Access Journals (Sweden)

    Giancarmine Fasano

    2013-09-01

    Full Text Available An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.

  18. Designing fuzzy rule based classifier using self-organizing feature map for analysis of multispectral satellite images

    CERN Document Server

    Pal, Nikhil R; Das, J

    2009-01-01

    We propose a novel scheme for designing fuzzy rule based classifier. An SOFM based method is used for generating a set of prototypes which is used to generate a set of fuzzy rules. Each rule represents a region in the feature space that we call the context of the rule. The rules are tuned with respect to their context. We justified that the reasoning scheme may be different in different context leading to context sensitive inferencing. To realize context sensitive inferencing we used a softmin operator with a tunable parameter. The proposed scheme is tested on several multispectral satellite image data sets and the performance is found to be much better than the results reported in the literature.

  19. Detection of Convective Initiation Using Meteorological Imager Onboard Communication, Ocean, and Meteorological Satellite Based on Machine Learning Approaches

    Directory of Open Access Journals (Sweden)

    Hyangsun Han

    2015-07-01

    Full Text Available As convective clouds in Northeast Asia are accompanied by various hazards related with heavy rainfall and thunderstorms, it is very important to detect convective initiation (CI in the region in order to mitigate damage by such hazards. In this study, a novel approach for CI detection using images from Meteorological Imager (MI, a payload of the Communication, Ocean, and Meteorological Satellite (COMS, was developed by improving the criteria of the interest fields of Rapidly Developing Cumulus Areas (RDCA derivation algorithm, an official CI detection algorithm for Multi-functional Transport SATellite-2 (MTSAT-2, based on three machine learning approaches—decision trees (DT, random forest (RF, and support vector machines (SVM. CI was defined as clouds within a 16 × 16 km window with the first detection of lightning occurrence at the center. A total of nine interest fields derived from visible, water vapor, and two thermal infrared images of MI obtained 15–75 min before the lightning occurrence were used as input variables for CI detection. RF produced slightly higher performance (probability of detection (POD of 75.5% and false alarm rate (FAR of 46.2% than DT (POD of 70.7% and FAR of 46.6% for detection of CI caused by migrating frontal cyclones and unstable atmosphere. SVM resulted in relatively poor performance with very high FAR ~83.3%. The averaged lead times of CI detection based on the DT and RF models were 36.8 and 37.7 min, respectively. This implies that CI over Northeast Asia can be forecasted ~30–45 min in advance using COMS MI data.

  20. Web-based spatial analysis with the ILWIS open source GIS software and satellite images from GEONETCast

    Science.gov (United States)

    Lemmens, R.; Maathuis, B.; Mannaerts, C.; Foerster, T.; Schaeffer, B.; Wytzisk, A.

    2009-12-01

    This paper involves easy accessible integrated web-based analysis of satellite images with a plug-in based open source software. The paper is targeted to both users and developers of geospatial software. Guided by a use case scenario, we describe the ILWIS software and its toolbox to access satellite images through the GEONETCast broadcasting system. The last two decades have shown a major shift from stand-alone software systems to networked ones, often client/server applications using distributed geo-(web-)services. This allows organisations to combine without much effort their own data with remotely available data and processing functionality. Key to this integrated spatial data analysis is a low-cost access to data from within a user-friendly and flexible software. Web-based open source software solutions are more often a powerful option for developing countries. The Integrated Land and Water Information System (ILWIS) is a PC-based GIS & Remote Sensing software, comprising a complete package of image processing, spatial analysis and digital mapping and was developed as commercial software from the early nineties onwards. Recent project efforts have migrated ILWIS into a modular, plug-in-based open source software, and provide web-service support for OGC-based web mapping and processing. The core objective of the ILWIS Open source project is to provide a maintainable framework for researchers and software developers to implement training components, scientific toolboxes and (web-) services. The latest plug-ins have been developed for multi-criteria decision making, water resources analysis and spatial statistics analysis. The development of this framework is done since 2007 in the context of 52°North, which is an open initiative that advances the development of cutting edge open source geospatial software, using the GPL license. GEONETCast, as part of the emerging Global Earth Observation System of Systems (GEOSS), puts essential environmental data at the

  1. A neuromorphic approach to satellite image understanding

    Science.gov (United States)

    Partsinevelos, Panagiotis; Perakakis, Manolis

    2014-05-01

    Remote sensing satellite imagery provides high altitude, top viewing aspects of large geographic regions and as such the depicted features are not always easily recognizable. Nevertheless, geoscientists familiar to remote sensing data, gradually gain experience and enhance their satellite image interpretation skills. The aim of this study is to devise a novel computational neuro-centered classification approach for feature extraction and image understanding. Object recognition through image processing practices is related to a series of known image/feature based attributes including size, shape, association, texture, etc. The objective of the study is to weight these attribute values towards the enhancement of feature recognition. The key cognitive experimentation concern is to define the point when a user recognizes a feature as it varies in terms of the above mentioned attributes and relate it with their corresponding values. Towards this end, we have set up an experimentation methodology that utilizes cognitive data from brain signals (EEG) and eye gaze data (eye tracking) of subjects watching satellite images of varying attributes; this allows the collection of rich real-time data that will be used for designing the image classifier. Since the data are already labeled by users (using an input device) a first step is to compare the performance of various machine-learning algorithms on the collected data. On the long-run, the aim of this work would be to investigate the automatic classification of unlabeled images (unsupervised learning) based purely on image attributes. The outcome of this innovative process is twofold: First, in an abundance of remote sensing image datasets we may define the essential image specifications in order to collect the appropriate data for each application and improve processing and resource efficiency. E.g. for a fault extraction application in a given scale a medium resolution 4-band image, may be more effective than costly

  2. Satellite-Based Sunshine Duration for Europe

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-06-01

    Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

  3. Sharpening method of satellite thermal image based on the geographical statistical model

    Science.gov (United States)

    Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng

    2016-04-01

    To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

  4. Comparison Between Linear and Nonlinear Models of Mixed Pixels in Remote Sensing Satellite Images Based on Cierniewski Surface BRDF Model by Means of Monte Carlo Ray Tracing Simulation

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2013-04-01

    Full Text Available Comparative study on linear and nonlinear mixed pixel models of which pixels in remote sensing satellite images is composed with plural ground cover materials mixed together, is conducted for remote sensing satellite image analysis. The mixed pixel models are based on Cierniewski of ground surface reflectance model. The comparative study is conducted by using of Monte Carlo Ray Tracing: MCRT simulations. Through simulation study, the difference between linear and nonlinear mixed pixel models is clarified. Also it is found that the simulation model is validated.

  5. Geometric calibration of ERS satellite SAR images

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2001-01-01

    Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed and...... calibrated by using the European Space Agency (ESA) transponders at Flevoland. The resulting accuracy of the slant range images corresponds to 10 m horizontally on the ground. The results are verified by using runway intersections and corner reflectors surveyed with differential GPS techniques. Based on a...

  6. A Study on Retrieval Algorithm of Black Water Aggregation in Taihu Lake Based on HJ-1 Satellite Images

    Science.gov (United States)

    Lei, Zou; Bing, Zhang; Junsheng, Li; Qian, Shen; Fangfang, Zhang; Ganlin, Wang

    2014-03-01

    The phenomenon of black water aggregation (BWA) occurs in inland water when massive algal bodies aggregate, die, and react with the toxic sludge in certain climate conditions to deprive the water of oxygen. This process results in the deterioration of water quality and damage to the ecosystem. Because charge coupled device (CCD) camera data from the Chinese HJ environmental satellite shows high potential in monitoring BWA, we acquired four HJ-CCD images of Taihu Lake captured during 2009 to 2011 to study this phenomenon. The first study site was selected near the Shore of Taihu Lake. We pre-processed the HJ-CCD images and analyzed the digital number (DN) gray values in the research area and in typical BWA areas. The results show that the DN values of visible bands in BWA areas are obviously lower than those in the research areas. Moreover, we developed an empirical retrieving algorithm of BWA based on the DN mean values and variances of research areas. Finally, we tested the accuracy of this empirical algorithm. The retrieving accuracies were89.9%, 58.1%, 73.4%, and 85.5%, respectively, which demonstrates the efficiency of empirical algorithm in retrieving the approximate distributions of BWA.

  7. A Study on Retrieval Algorithm of Black Water Aggregation in Taihu Lake Based on HJ-1 Satellite Images

    International Nuclear Information System (INIS)

    The phenomenon of black water aggregation (BWA) occurs in inland water when massive algal bodies aggregate, die, and react with the toxic sludge in certain climate conditions to deprive the water of oxygen. This process results in the deterioration of water quality and damage to the ecosystem. Because charge coupled device (CCD) camera data from the Chinese HJ environmental satellite shows high potential in monitoring BWA, we acquired four HJ-CCD images of Taihu Lake captured during 2009 to 2011 to study this phenomenon. The first study site was selected near the Shore of Taihu Lake. We pre-processed the HJ-CCD images and analyzed the digital number (DN) gray values in the research area and in typical BWA areas. The results show that the DN values of visible bands in BWA areas are obviously lower than those in the research areas. Moreover, we developed an empirical retrieving algorithm of BWA based on the DN mean values and variances of research areas. Finally, we tested the accuracy of this empirical algorithm. The retrieving accuracies were89.9%, 58.1%, 73.4%, and 85.5%, respectively, which demonstrates the efficiency of empirical algorithm in retrieving the approximate distributions of BWA

  8. Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2007-01-01

    Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

  9. Virtual Satellite Construction and Application for Image Classification

    International Nuclear Information System (INIS)

    Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively

  10. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...... images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping....

  11. The Extraction Model of Paddy Rice Information Based on GF-1 Satellite WFV Images.

    Science.gov (United States)

    Yang, Yan-jun; Huang, Yan; Tian, Qing-jiu; Wang, Lei; Geng, Jun; Yang, Ran-ran

    2015-11-01

    In the present, using the characteristics of paddy rice at different phenophase to identify it by remote sensing images is an efficient way in the information extraction. According to the remarkably properties of paddy rice different from other vegetation, which the surface of paddy fields is with a large number of water in the early stage, NDWI (normalized difference water index) which is used to extract water information can reasonably be applied in the extraction of paddy rice at the early stage of the growth. And using NDWI ratio of two phenophase can expand the difference between paddy rice and other surface features, which is an important part for the extraction of paddy rice with high accuracy. Then using the variation of NDVI (normalized differential vegetation index) in different phenophase can further enhance accuracy of paddy rice information extraction. This study finds that making full advantage of the particularity of paddy rice in different phenophase and combining two indices (NDWI and NDVI) associated with paddy rice can establish a reasonable, accurate and effective extraction model of paddy rice. This is also the main way to improve the accuracy of paddy rice extraction. The present paper takes Lai'an in Anhui Province as the research area, and rice as the research object. It constructs the extraction model of paddy rice information using NDVI and NDWI between tillering stage and heading stage. Then the model was applied to GF1-WFV remote sensing image on July 12, 2013 and August 30, 2013. And it effectively extracted out of paddy rice distribution in Lai'an and carried on the mapping. At last, the result of extraction was verified and evaluated combined with field investigation data in the study area. The result shows that using the extraction model can quickly and accurately obtain the distribution of rice information, and it has the very good universality. PMID:26978945

  12. Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

    Science.gov (United States)

    Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

    2016-09-01

    Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

  13. Embedded Implementation of VHR Satellite Image Segmentation.

    Science.gov (United States)

    Li, Chao; Balla-Arabé, Souleymane; Ginhac, Dominique; Yang, Fan

    2016-01-01

    Processing and analysis of Very High Resolution (VHR) satellite images provide a mass of crucial information, which can be used for urban planning, security issues or environmental monitoring. However, they are computationally expensive and, thus, time consuming, while some of the applications, such as natural disaster monitoring and prevention, require high efficiency performance. Fortunately, parallel computing techniques and embedded systems have made great progress in recent years, and a series of massively parallel image processing devices, such as digital signal processors or Field Programmable Gate Arrays (FPGAs), have been made available to engineers at a very convenient price and demonstrate significant advantages in terms of running-cost, embeddability, power consumption flexibility, etc. In this work, we designed a texture region segmentation method for very high resolution satellite images by using the level set algorithm and the multi-kernel theory in a high-abstraction C environment and realize its register-transfer level implementation with the help of a new proposed high-level synthesis-based design flow. The evaluation experiments demonstrate that the proposed design can produce high quality image segmentation with a significant running-cost advantage. PMID:27240370

  14. Satellite Remote Sensing Image Analysis Technology Based on eCognition%基于eCognition的卫星遥感影像分析技术

    Institute of Scientific and Technical Information of China (English)

    孙悦

    2014-01-01

    The satellite remote sensing image analysis is a research hotspot in recent years. In this paper,the current progress of information extraction technology on satellite sensing images is analyzed,the advantage of object-oriented high-resolution image analysis is highlighted,and the application of target change detection of satellite sensing images in military field is introduced. In this paper,the object-oriented multiscale segmentation strategy is used in the field of satellite remote sensing image processing,and secondary develop-ment processes is implemented based on eCognition SDK. The results of multiple experiments show that the proposed satellite remote sensing image analysis technology can implement better information extraction and analysis.%卫星遥感影像分析技术是近年来的一个研究热点问题。归纳总结了遥感影像信息提取技术的发展现状,阐述了面向对象的高分辨率遥感影像分析技术的优势,介绍了遥感影像目标变化检测技术的应用情况。将面向对象的多尺度分割策略应用在卫星遥感影像处理领域,实现了基于eCognition SDK的二次开发流程,取得了良好的实验效果。

  15. Oil Spill Map for Indian Sea Region based on Bhuvan- Geographic Information System using Satellite Images

    OpenAIRE

    Vijaya kumar, L. J.; Kishore, J. K.; Kesava Rao, P.; Annadurai, M.; C. B. S. Dutt; K. Hanumantha Rao; Sasamal, S. K.; Arulraj, M.; Prasad, A. V. V.; Sita Kumari, E. V. S.; Satyanarayana, S. N.; Shenoy, H. P.

    2014-01-01

    Oil spills in the ocean are a serious marine disaster that needs regular monitoring for environmental risk assessment and mitigation. Recent use of Polarimetric SAR imagery in near real time oil spill detection systems is associated with attempts towards automatic and unambiguous oil spill detection based on decomposition methods. Such systems integrate remote sensing technology, geo information, communication system, hardware and software systems to provide key information for analy...

  16. Edge Detection in Satellite Image Using Cellular Neural Network

    Directory of Open Access Journals (Sweden)

    Osama Basil Gazi

    2014-10-01

    Full Text Available The present paper proposes a novel approach for edge detection in satellite images based on cellular neural networks. CNN based edge detector in used conjunction with image enhancement and noise removal techniques, in order to deliver accurate edge detection results, compared with state of the art approaches. Thus, considering the obtained results, a comparison with optimal Canny edge detector is performed. The proposed image processing chain deliver more details regarding edges than canny edge detector. The proposed method aims to preserve salient information, due to its importance in all satellite image processing applications.

  17. Satellite image georegistration from coast-line codification

    OpenAIRE

    Reig Bolaño, Ramon; Parisi Baradad, Vicenç; García-Ladona, Emilio; Martí Puig, Pere

    2008-01-01

    This paper presents a contour-based approach for automatic image registration in satellite oceanography. Accurate image georegistration is an essential step to increase the eff ectiveness of all the image processing methods that aggregate information from diff erent sources, i.e. applying data fusion techniques. In our approach the images description is based on main contours extracted from coast-line. Each contour is codifi ed by a modifi ed chain-code, and the result is ...

  18. Automatic Approach to Vhr Satellite Image Classification

    Science.gov (United States)

    Kupidura, P.; Osińska-Skotak, K.; Pluto-Kossakowska, J.

    2016-06-01

    In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture), which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the preliminary step

  19. Randomness-Based Scale-Chromatic Image Analysis for Interactive Mapping on Satellite-Roadway-Vehicle Network

    Directory of Open Access Journals (Sweden)

    Kohji Kamejima

    2007-08-01

    Full Text Available A new framework is presented for integrating satellite/avionics sensors with onboard vision to support information intensive maneuvering. Real time bindings of the bird's eye observation and the driver's view via GPS provides extit{as-is} basis for perception and decision. Randomness-based roadway pattern model is implemented by fractal coding scheme associating bird's eye and frontal views. The feasibility of the framework with resquirements for vison system is discussed through concept modeling and experimental studies.

  20. a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

    Science.gov (United States)

    Haigang, Sui; Zhina, Song

    2016-06-01

    Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

  1. Analysis Of Spiht Algorithm For Satellite Image Compression

    Directory of Open Access Journals (Sweden)

    K Nagamani

    2011-10-01

    Full Text Available Wavelets offer an elegant technique for representing the levels of details present in an image. When an image is decomposed using wavelets, the high pass component carry less information, and vice-versa. The possibility of elimination of the high pass components gives higher compression ratio in the case of wavelet based image compression. To achieve higher compression ratio, various coding schemes have been used. Some of the well known coding algorithms are EZW (Embedded Zero-tree Wavelet, SPIHT (Set Partitioning in Hierarchical Tree and EBCOT (Embedded Block Coding with Optimal Truncation. SPIHT has been one of the popular schemes used for image compression. In this paper the performance of the SPIHT (Set Partitioning in Hierarchical Trees compression technique for satellite images are studied. The satellite rural and urban images have been used for the present analysis. The standard Lena image is used for the purpose of comparison. For a given compression ratio, the PSNR (peak signal to noise ratio values are computed to evaluate the quality of the reconstructed image. The analysis carried out clearly suggests that the PSNR values increases with the level of decomposition. For the satellite images the PSNR values achievable are less compared to that of Standard Lena Image and the SPIHT Algorithm are better suited for compression of Satellite urban Images.

  2. Rotation-and-scale-invariant airplane detection in high-resolution satellite images based on deep-Hough-forests

    Science.gov (United States)

    Yu, Yongtao; Guan, Haiyan; Zai, Dawei; Ji, Zheng

    2016-02-01

    This paper proposes a rotation-and-scale-invariant method for detecting airplanes from high-resolution satellite images. To improve feature representation capability, a multi-layer feature generation model is created to produce high-order feature representations for local image patches through deep learning techniques. To effectively estimate airplane centroids, a Hough forest model is trained to learn mappings from high-order patch features to the probabilities of an airplane being present at specific locations. To handle airplanes with varying orientations, patch orientation is defined and integrated into the Hough forest to augment Hough voting. The scale invariance is achieved by using a set of scale factors embedded in the Hough forest. Quantitative evaluations on the images collected from Google Earth service show that the proposed method achieves a completeness, correctness, quality, and F1-measure of 0.968, 0.972, 0.942, and 0.970, respectively, in detecting airplanes with arbitrary orientations and sizes. Comparative studies also demonstrate that the proposed method outperforms the other three existing methods in accurately and completely detecting airplanes in high-resolution remotely sensed images.

  3. Extraction of Satellite Image using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Harish Kundra, V.K.Panchal, Sagar Arora, Karandeep Singh, Himashu Kaura, Jaspreet Singh Phool

    2010-04-01

    Full Text Available Of all tasks in photogrammetry the extraction of cartographic features is the most timeconsuming. Fully automatic acquisition of features like roads and buildings, however, appears tobe very difficult. The extraction of cartographic features form digital satellite imagery requiresinterpretation of this imagery. The knowledge one needs about the topographic objects and theirappearances in satellite images in order to recognize these objects and extract the relevantobject outlines is difficult to model and to implement in computer algorithms. This paperintroduces Particle Swarm Optimization based method of object extraction from Google Earthimage (satellite image. This paper deals with the land cover mapping by using swarm computingtechniques. The motivation of this paper is to explore the improved swarm computing algorithmsfor the satellite image object extraction.

  4. Satellite-based internet: A tutorial

    OpenAIRE

    Hu, Y.; Li, VOK

    2001-01-01

    In a satellite-based Internet system, satellites are used to interconnect heterogeneous network segments and to provide ubiquitous direct Internet access to homes and businesses. This article presents satellite-based Internet architectures and discusses multiple access control, routing, satellite transport, and integrating satellite networks into the global Internet.

  5. Monitoring objects orbiting earth using satellite-based telescopes

    Science.gov (United States)

    Olivier, Scot S.; Pertica, Alexander J.; Riot, Vincent J.; De Vries, Willem H.; Bauman, Brian J.; Nikolaev, Sergei; Henderson, John R.; Phillion, Donald W.

    2015-06-30

    An ephemeris refinement system includes satellites with imaging devices in earth orbit to make observations of space-based objects ("target objects") and a ground-based controller that controls the scheduling of the satellites to make the observations of the target objects and refines orbital models of the target objects. The ground-based controller determines when the target objects of interest will be near enough to a satellite for that satellite to collect an image of the target object based on an initial orbital model for the target objects. The ground-based controller directs the schedules to be uploaded to the satellites, and the satellites make observations as scheduled and download the observations to the ground-based controller. The ground-based controller then refines the initial orbital models of the target objects based on the locations of the target objects that are derived from the observations.

  6. Selective image encryption for Medical and Satellite Images

    OpenAIRE

    NaveenKumar S K; Panduranga H T

    2013-01-01

    Information security plays a very important role in fast growing information and communication technology. Few applications like medical image security and satellite image security needs to secure only selected portion of the image. This paper describes a concept of selective image encryption in two ways. First method divides the image in to sub blocks, then selected blocks are applied to encryption process. Second method automatically detects the positions of objects, and then selected objec...

  7. Mapping urban heat islands of arctic cities using combined data on field measurements and satellite images based on the example of the city of Apatity (Murmansk Oblast)

    Science.gov (United States)

    Konstantinov, P. I.; Grishchenko, M. Y.; Varentsov, M. I.

    2015-12-01

    This article presents the results of a study of the urban heat island (UHI) in the city of Apatity during winter that were obtained according to the data of field meteorological measurements and satellite images. Calculations of the surface layer temperature have been made based on the surface temperature data obtained from satellite images. The experimental data on air temperature were obtained as a result of expeditionary meteorological observations, and the experimental data on surface temperature were obtained based on the data of the space hyperspectral Moderate-Resolution Imaging Spectroradiometer (MODIS) system, channels 31 and 32 (10.78-11.28 and 11.77-12.27 micrometers, respectively). As a result of the analysis of temperature fields, an intensive heat island (up to 3.2°C) has been identified that was estimated based on the underlying surface temperature, and its mean intensity over the observation period significantly exceeds the representative data for European cities in winter. It has also been established that the air temperature calculated according to the MODIS data is systematically higher under winter conditions than the air temperature from direct measurement data.

  8. Satellite-based land use mapping: comparative analysis of Landsat-8, Advanced Land Imager, and big data Hyperion imagery

    Science.gov (United States)

    Pervez, Wasim; Uddin, Vali; Khan, Shoab Ahmad; Khan, Junaid Aziz

    2016-04-01

    Until recently, Landsat technology has suffered from low signal-to-noise ratio (SNR) and comparatively poor radiometric resolution, which resulted in limited application for inland water and land use/cover mapping. The new generation of Landsat, the Landsat Data Continuity Mission carrying the Operational Land Imager (OLI), has improved SNR and high radiometric resolution. This study evaluated the utility of orthoimagery from OLI in comparison with the Advanced Land Imager (ALI) and hyperspectral Hyperion (after preprocessing) with respect to spectral profiling of classes, land use/cover classification, classification accuracy assessment, classifier selection, study area selection, and other applications. For each data source, the support vector machine (SVM) model outperformed the spectral angle mapper (SAM) classifier in terms of class discrimination accuracy (i.e., water, built-up area, mixed forest, shrub, and bare soil). Using the SVM classifier, Hyperion hyperspectral orthoimagery achieved higher overall accuracy than OLI and ALI. However, OLI outperformed both hyperspectral Hyperion and multispectral ALI using the SAM classifier, and with the SVM classifier outperformed ALI in terms of overall accuracy and individual classes. The results show that the new generation of Landsat achieved higher accuracies in mapping compared with the previous Landsat multispectral satellite series.

  9. Selective image encryption for Medical and Satellite Images

    Directory of Open Access Journals (Sweden)

    NaveenKumar S K

    2013-02-01

    Full Text Available Information security plays a very important role in fast growing information and communication technology. Few applications like medical image security and satellite image security needs to secure only selected portion of the image. This paper describes a concept of selective image encryption in two ways. First method divides the image in to sub blocks, then selected blocks are applied to encryption process. Second method automatically detects the positions of objects, and then selected objects are applied to encryption process. Morphological techniques are used to detect the positions of the objects in given images. These two approaches are specifically developed to encrypt the portion of an image in medical images and satellite image.

  10. Satellite Image-based Estimates of Snow Water Equivalence in Restored Ponderosa Pine Forests in Northern Arizona

    Science.gov (United States)

    Sankey, T.; Springer, A. E.; O'Donnell, F. C.; Donald, J.; McVay, J.; Masek Lopez, S.

    2014-12-01

    The U.S. Forest Service plans to conduct forest restoration treatments through the Four Forest Restoration Initiative (4FRI) on hundreds of thousands of acres of ponderosa pine forest in northern Arizona over the next 20 years with the goals of reducing wildfire hazard and improving forest health. The 4FRI's key objective is to thin and burn the forests to create within-stand openings that "promote snowpack accumulation and retention which benefit groundwater recharge and watershed processes at the fine (1 to 10 acres) scale". However, little is known about how these openings created by restoration treatments affect snow water equivalence (SWE) and soil moisture, which are key parts of the water balance that greatly influence water availability for healthy trees and for downstream water users in the Sonoran Desert. We have examined forest canopy cover by calculating a Normalized Difference Vegetation Index (NDVI), a key indicator of green vegetation cover, using Landsat satellite data. We have then compared NDVI between treatments at our study sites in northern Arizona and have found statistically significant differences in tree canopy cover between treatments. The control units have significantly greater forest canopy cover than the treated units. The thinned units also have significantly greater tree canopy cover than the thin-and-burn units. Winter season Landsat images have also been analyzed to calculate Normalized Difference Snow Index (NDSI), a key indicator of snow water equivalence and snow accumulation at the treated and untreated forests. The NDSI values from these dates are examined to determine if snow accumulation and snow water equivalence vary between treatments at our study sites. NDSI is significantly greater at the treated units than the control units. In particular, the thinned forest units have significantly greater snow cover than the control units. Our results indicate that forest restoration treatments result in increased snow pack

  11. The contribution of high resolution satellite images to the production of base-maps and cartographies for archaeological research in Turkey and Iraq

    Science.gov (United States)

    Scardozzi, Giuseppe

    2009-09-01

    The paper concerns the contribution of high resolution satellite images to the production of base-maps and cartographies for archaeological research, using both during field work and in GIS dedicated to Cultural Heritage. Particularly, some experiences conducted during researches on Turkish and Iraqi archaeological sites are presented, where the use of satellite images was necessary because of both large scale cartographies and aero-photogrammetrical photos are not available. In the case of archaeological surveys in Hierapolis of Phrygia (south-western Turkey) they provided a fundamental tool for the research on the ground and for the analysis and management of data in the archaeological GIS of the territory. Ikonos-2 and QuickBird-2 images were ortho-rectified with the use of GCPs (taken with a differential GPS) and with DEMs and DSMs processed thanks different remote sensing data, radar (SRTM) and optical (Ikonos-2 and ASTER stereo-pairs), for the creation of space-maps and the extraction of cartographical elements: these (hydrology, modern topography, field boundaries, archaeological remains and traces, etc.) were used with the aims of the creation of new maps for archaeological purpose (the orography was extracted from DEMs) and the update of the existing ones. In the case of some ancient sites studied for the contextualization of the objects showed in the Virtual Museum of Iraq, high resolution images of the same satellites (and of WorldView-1) were ortho-rectified without GPCs and used for the creation or the update of the archaeological maps (generally very old), on which plans of excavated structures, recent discoveries, and archaeological traces and paleo-environmental elements were geo-referenced.

  12. Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Yu Hsin Tsai

    2011-12-01

    Full Text Available The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1 post-classification comparison; and (2 bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated. Final map products representing new building objects were compared and assessed for accuracy using two object-based accuracy measures, completeness and correctness. The bi-temporal layerstack method generated more accurate results compared to the post-classification comparison method due to less confusion with background objects. The spectral/spatial contextual approach (Feature Analyst outperformed the true object-based feature delineation approach (ENVI Feature Extraction due to its ability to more reliably delineate individual buildings of various sizes. Semi-automated, object-based detection followed by manual editing appears to be a reliable and efficient approach for detecting and enumerating new building objects. A bivariate regression analysis was performed using neighborhood-level estimates of new building density regressed on a census-derived measure of socio-economic status, yielding an inverse relationship with R2 = 0.31 (n = 27; p = 0.00. The primary utility of the new building delineation results is to support spatial analyses of land cover and land use and demographic change.

  13. Satellite Imaging in the Study of Pennsylvania's Environmental Issues.

    Science.gov (United States)

    Nous, Albert P.

    This document focuses on using satellite images from space in the classroom. There are two types of environmental satellites routinely broadcasting: (1) Polar-Orbiting Operational Environmental Satellites (POES), and (2) Geostationary Operational Environmental Satellites (GOES). Imaging and visualization techniques provide students with a better…

  14. Quality of Life Assessment Based on Spatial and Temporal Analysis of the Vegetation Area Derived from Satellite Images

    Directory of Open Access Journals (Sweden)

    MARIA IOANA VLAD

    2011-01-01

    Full Text Available The quality of life in urban areas is a function of many parameters among which, one highly important is the number and quality of green areas for people and wildlife to thrive. The quality of life is also a political concept often used to describe citizen satisfaction within different residential locations. Only in the last decades green areas have suffered a progressive decrease in quality, pointing out the ecological urban risk with a negative impact on the standard of living and population health status. This paper presents the evolution of green areas in the cities of South-Eastern Romania within the last 20 years and sets forth the current state of quality of life from the perspective of vegetation reference. By using state-of-the-art processing tools applied on high-resolution satellite images, we have derived knowledge about the spatial and temporal expansion of urbanized regions. Our semi-automatic technologies for analysis of remote sensing data such as Landsat 7 ETM+, correlated with statistical information inferred from urban charts, demonstrate a negative trend in the distribution of green areas within the analyzed cities, with long-term implications on multiple areas in our lives.

  15. 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

    providers are involved in the consortium. First results show that the Greenmonitor is much more suitable for comparison in growth between fields at regional scale, while UAV based imagery is much more suitable for mapping variation in crop biochemistry (i.e., chlorophyll, nitrogen) within the fields, which requires in the Netherlands a spatial resolution of a few meters. Finally, the spatial and spectral dimension of satellite and UAV derived vegetation indices (i.e., weighted difference vegetation index, chlorophyll red-edge index) to evaluate to which extent UAV based image acquisition could be adopted to complement missing data in satellite time-series.

  16. Comparison of Satellite Image Enhancement Techniques in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    K. Narasimhan

    2012-12-01

    Full Text Available In this study, a comparison of various existing satellite image resolution enhancement techniques in wavelet domain is done. Each method is analysed quantitatively and visually. There are various wavelet domain based methods such as Wavelet Zero Padding, Dual Tree-Complex Wavelet Transform, Discrete Wavelet Transform, Cycle Spinning and Undecimated Wavelet Transform. On the basis of analysis, the most efficient method is proposed. The algorithms take the low resolution image as the input image and then wavelet transformation using daubechies (db3 is used to decompose the input image into different sub band images containing high and low frequency component. Then these subband images along with the input image are interpolated followed by combining all these images to generate a new resolution enhanced image by an inverse process.

  17. Simplified Flood Inundation Mapping Based On Flood Elevation-Discharge Rating Curves Using Satellite Images in Gauged Watersheds

    OpenAIRE

    Younghun Jung; Dongkyun Kim; Dongwook Kim; Munmo Kim; Seung Oh Lee

    2014-01-01

    This study suggests an approach to obtain flood extent boundaries using spatial analysis based on Landsat-5 Thematic Mapper imageries and the digital elevation model. The suggested approach firstly extracts the flood inundation areas using the ISODATA image-processing algorithm from four Landsat 5TM imageries. Then, the ground elevations at the intersections of the extracted flood extent boundaries and the specified river cross sections are read from the digital elevation to estimate the elev...

  18. Neural networks for meteorological satellite image interpretation

    OpenAIRE

    Brewer, Michael Robert.

    1997-01-01

    Meteorological satellite images at visible and infra-red wavelengths are an invaluable source of information on cloud systems because of their extensive coverage of the whole of the Earth's surface, providing data in areas that are only sparsely monitored, if at all, by other means. Although this information has been used subjectively by forecasters for many years, the lack of automatic, quantitative analysis techniques largely prevents its assimilation into numerical weather ...

  19. Geomorphology of coastal environments from satellite images

    International Nuclear Information System (INIS)

    This study aims at recognizing coastal environments supported by data from the Landsat Thematic Mapper (TM) satellite. The digital processing of images, System Information Geographic (SIG) techniques and field observation in one section of the “Província Costeira do Rio Grande do Sul” between the Rio Grande and the São Gonçalo channels - resulted in a geomorphologic profile and mapping

  20. Neural network-based segmentation of satellite imagery for estimating house cluster of an urban settlement from Google Earth images

    International Nuclear Information System (INIS)

    In this paper a backpropagation neural network is utilized to perform house cluster segmentation from Google Earth data. The algorithm is subjected to identify houses in the image based on the RGB pattern within each pixel. Training data is given through cropping selection for a target that is a house cluster and a non object. The algorithm assigns 1 to a pixel belong to a class of object and 0 to a class of non object. The resulting outcome, a binary image, is then utilized to perform quantification to estimate the number of house clusters. The number of the hidden layer is varying in order to find its effect to the neural network performance and total computational time

  1. Estimating seasonal evapotranspiration from temporal satellite images

    Science.gov (United States)

    Singh, Ramesh K.; Liu, Shu-Guang; Tieszen, Larry L.; Suyker, Andrew E.; Verma, Shashi B.

    2012-01-01

    Estimating seasonal evapotranspiration (ET) has many applications in water resources planning and management, including hydrological and ecological modeling. Availability of satellite remote sensing images is limited due to repeat cycle of satellite or cloud cover. This study was conducted to determine the suitability of different methods namely cubic spline, fixed, and linear for estimating seasonal ET from temporal remotely sensed images. Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model in conjunction with the wet METRIC (wMETRIC), a modified version of the METRIC model, was used to estimate ET on the days of satellite overpass using eight Landsat images during the 2001 crop growing season in Midwest USA. The model-estimated daily ET was in good agreement (R2 = 0.91) with the eddy covariance tower-measured daily ET. The standard error of daily ET was 0.6 mm (20%) at three validation sites in Nebraska, USA. There was no statistically significant difference (P > 0.05) among the cubic spline, fixed, and linear methods for computing seasonal (July–December) ET from temporal ET estimates. Overall, the cubic spline resulted in the lowest standard error of 6 mm (1.67%) for seasonal ET. However, further testing of this method for multiple years is necessary to determine its suitability.

  2. HJ-1-A/B optical satellite image geometric correction

    International Nuclear Information System (INIS)

    Small satellite constellation of environment and disaster's monitoring and predicting (shorted for HJ-1) is not a mapping satellite, and its parameters of attitude and orbit cannot satisfy the requirement of geometric correction using strict imaging model. On the other hand, due to the 12000 CCD detectors and large overlay of multispectral payload named CCD carried by HJ-1 satellite, the error caused by CCD distortion cannot be ignored. Aiming at these problems of HJ-1, this paper proposes a strict orbit model algorithm based on Ground Control Point (GCP) and collinear condition equations. Through the robust estimation of parameters, this algorithm can effectively set up imaging geometric model of CCD, and satisfy the requirement of high precision geometric correction

  3. Satellite-based laser windsounder

    International Nuclear Information System (INIS)

    This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project''s primary objective is to determine the technical feasibility of using satellite-based laser wind sensing systems for detailed study of winds, aerosols, and particulates around and downstream of suspected proliferation facilities. Extensive interactions with the relevant operational organization resulted in enthusiastic support and useful guidance with respect to measurement requirements and priorities. Four candidate wind sensing techniques were evaluated, and the incoherent Doppler technique was selected. A small satellite concept design study was completed to identify the technical issues inherent in a proof-of-concept small satellite mission. Use of a Mach-Zehnder interferometer instead of a Fabry-Perot would significantly simplify the optical train and could reduce weight, and possibly power, requirements with no loss of performance. A breadboard Mach-Zehnder interferometer-based system has been built to verify these predictions. Detailed plans were made for resolving other issues through construction and testing of a ground-based lidar system in collaboration with the University of Wisconsin, and through numerical lidar wind data assimilation studies

  4. Satellite-based laser windsounder

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, J.F.; Czuchlewski, S.J.; Quick, C.R. [and others

    1997-08-01

    This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project`s primary objective is to determine the technical feasibility of using satellite-based laser wind sensing systems for detailed study of winds, aerosols, and particulates around and downstream of suspected proliferation facilities. Extensive interactions with the relevant operational organization resulted in enthusiastic support and useful guidance with respect to measurement requirements and priorities. Four candidate wind sensing techniques were evaluated, and the incoherent Doppler technique was selected. A small satellite concept design study was completed to identify the technical issues inherent in a proof-of-concept small satellite mission. Use of a Mach-Zehnder interferometer instead of a Fabry-Perot would significantly simplify the optical train and could reduce weight, and possibly power, requirements with no loss of performance. A breadboard Mach-Zehnder interferometer-based system has been built to verify these predictions. Detailed plans were made for resolving other issues through construction and testing of a ground-based lidar system in collaboration with the University of Wisconsin, and through numerical lidar wind data assimilation studies.

  5. Simplified Flood Inundation Mapping Based On Flood Elevation-Discharge Rating Curves Using Satellite Images in Gauged Watersheds

    Directory of Open Access Journals (Sweden)

    Younghun Jung

    2014-05-01

    Full Text Available This study suggests an approach to obtain flood extent boundaries using spatial analysis based on Landsat-5 Thematic Mapper imageries and the digital elevation model. The suggested approach firstly extracts the flood inundation areas using the ISODATA image-processing algorithm from four Landsat 5TM imageries. Then, the ground elevations at the intersections of the extracted flood extent boundaries and the specified river cross sections are read from the digital elevation to estimate the elevation-discharge relationship. Lastly, the flood extent is generated based on the estimated elevation-discharge relationship. The methodology was tested over two river reaches in Indiana, United States. The estimated elevation-discharge relationship showed a good match with the correlation coefficients varying between 0.82 and 0.99. In addition, self-validation was also performed for the estimated spatial extent of the flood by comparing it to the waterbody extracted from the Landsat images used to develop the elevation-discharge relationship. The result indicated that the match between the estimated and the extracted flood extents was better with higher flood magnitude. We expect that the suggested methodology will help under-developed and developing countries to obtain flood maps, which have difficulties getting flood maps through traditional approaches based on computer modeling.

  6. Design and testing of the navigation model for three axis stabilized earth oriented satellites applied to the ATS-6 satellite image data base

    Science.gov (United States)

    Kuhlow, W. W.; Chatters, G. C.

    1977-01-01

    An earth edge methodology has been developed to account for the relative attitude changes between successive ATS-6 images which allows reasonable high quality wind sets to be produced. The method consists of measuring the displacements of the right and left infrared earth edges between successive ATS-6 images as a function of scan line; from these measurements the attitude changes can be deduced and used to correct the apparent cloud displacement measurements. The wind data sets generated from ATS-6 using the earth-edge methodology were compared with those derived from the SMS-1 images (and model) covering the same time period. Quantitative comparisons for low level trade cumuli were made at interpolated uniformly spaced grid points and for selected individual comparison clouds. Selected individual comparison clouds, the root-mean-square differences for the U and V components were 1.0 and 1.2 meters per second with a maximum wind direction difference of 15 deg.

  7. Image Resolution and Contrast Enhancement of Satellite Geographical Images with Removal of Noise using Wavelet Transforms

    OpenAIRE

    Khairnar, Prajakta P.; Manjare, C. A.

    2014-01-01

    In this paper the technique for resolution and contrast enhancement of satellite geographical images based on discrete wavelet transform (DWT), stationary wavelet transform (SWT) and singular value decomposition (SVD) has been proposed. In this, the noise is added in the input low resolution and low contrast image. The median filter is used remove noise from the input image. This low resolution, low contrast image without noise is decomposed into four sub-bands by using DWT and SWT. The resol...

  8. 14 CFR 141.91 - Satellite bases.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... assistant chief instructor is designated for each satellite base, and that assistant chief instructor...

  9. Two satellite image sets for the training and validation of image processing systems for defense applications

    Science.gov (United States)

    Peterson, Michael R.; Aldridge, Shawn; Herzog, Britny; Moore, Frank

    2010-04-01

    Many image processing algorithms utilize the discrete wavelet transform (DWT) to provide efficient compression and near-perfect reconstruction of image data. Defense applications often require the transmission of data at high levels of compression over noisy channels. In recent years, evolutionary algorithms (EAs) have been utilized to optimize image transform filters that outperform standard wavelets for bandwidth-constrained compression of satellite images. The optimization of these filters requires the use of training images appropriately chosen for the image processing system's intended applications. This paper presents two robust sets of fifty images each intended for the training and validation of satellite and unmanned aerial vehicle (UAV) reconnaissance image processing algorithms. Each set consists of a diverse range of subjects consisting of cities, airports, military bases, and landmarks representative of the types of images that may be captured during reconnaissance missions. Optimized algorithms may be "overtrained" for a specific problem instance and thus exhibit poor performance over a general set of data. To reduce the risk of overtraining an image filter, we evaluate the suitability of each image as a training image. After evolving filters using each image, we assess the average compression performance of each filter across the entire set of images. We thus identify a small subset of images from each set that provide strong performance as training images for the image transform optimization problem. These images will also provide a suitable platform for the development of other algorithms for defense applications. The images are available upon request from the contact author.

  10. Fuzzy Rules and Evidence Theory for Satellite Image Analysis

    CERN Document Server

    Laha, Arijit

    2011-01-01

    Design of a fuzzy rule based classifier is proposed. The performance of the classifier for multispectral satellite image classification is improved using Dempster- Shafer theory of evidence that exploits information of the neighboring pixels. The classifiers are tested rigorously with two known images and their performance are found to be better than the results available in the literature. We also demonstrate the improvement of performance while using D-S theory along with fuzzy rule based classifiers over the basic fuzzy rule based classifiers for all the test cases.

  11. Mapping Fish Community Variables by Integrating Field and Satellite Data, Object-Based Image Analysis and Modeling in a Traditional Fijian Fisheries Management Area

    Directory of Open Access Journals (Sweden)

    Stacy Jupiter

    2011-03-01

    Full Text Available The use of marine spatial planning for zoning multi-use areas is growing in both developed and developing countries. Comprehensive maps of marine resources, including those important for local fisheries management and biodiversity conservation, provide a crucial foundation of information for the planning process. Using a combination of field and high spatial resolution satellite data, we use an empirical procedure to create a bathymetric map (RMSE 1.76 m and object-based image analysis to produce accurate maps of geomorphic and benthic coral reef classes (Kappa values of 0.80 and 0.63; 9 and 33 classes, respectively covering a large (>260 km2 traditional fisheries management area in Fiji. From these maps, we derive per-pixel information on habitat richness, structural complexity, coral cover and the distance from land, and use these variables as input in models to predict fish species richness, diversity and biomass. We show that random forest models outperform five other model types, and that all three fish community variables can be satisfactorily predicted from the high spatial resolution satellite data. We also show geomorphic zone to be the most important predictor on average, with secondary contributions from a range of other variables including benthic class, depth, distance from land, and live coral cover mapped at coarse spatial scales, suggesting that data with lower spatial resolution and lower cost may be sufficient for spatial predictions of the three fish community variables.

  12. MODIS 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  13. ASTER 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  14. Quantitative and Qualitative Assessment of Soil Erosion Risk in Małopolska (Poland), Supported by an Object-Based Analysis of High-Resolution Satellite Images

    Science.gov (United States)

    Drzewiecki, Wojciech; Wężyk, Piotr; Pierzchalski, Marcin; Szafrańska, Beata

    2014-06-01

    In 2011 the Marshal Office of Małopolska Voivodeship decided to evaluate the vulnerability of soils to water erosion for the entire region. The quantitative and qualitative assessment of the erosion risk for the soils of the Małopolska region was done based on the USLE approach. The special work-flow of geoinformation technologies was used to fulfil this goal. A high-resolution soil map, together with rainfall data, a detailed digital elevation model and statistical information about areas sown with particular crops created the input information for erosion modelling in GIS environment. The satellite remote sensing technology and the object-based image analysis (OBIA) approach gave valuable support to this study. RapidEye satellite images were used to obtain the essential up-to-date data about land use and vegetation cover for the entire region (15,000 km2). The application of OBIA also led to defining the direction of field cultivation and the mapping of contour tillage areas. As a result, the spatially differentiated values of erosion control practice factor were used. Both, the potential and the actual soil erosion risk were assessed quantificatively and qualitatively. The results of the erosion assessment in the Małopolska Voivodeship reveal the fact that a majority of its agricultural lands is characterized by moderate or low erosion risk levels. However, high-resolution erosion risk maps show its substantial spatial diversity. According to our study, average or higher actual erosion intensity levels occur for 10.6 % of agricultural land, i.e. 3.6 % of the entire voivodeship area. In 20 % of the municipalities there is a very urgent demand for erosion control. In the next 23 % an urgent erosion control is needed. Our study showed that even a slight improvement of P-factor estimation may have an influence on modeling results. In our case, despite a marginal change of erosion assessment figures on a regional scale, the influence on the final prioritization of

  15. Flood-threat zoning map of the urban area of Chocó (Quibdó. A study based on interpreting radar, satellite and aerial photograph images

    Directory of Open Access Journals (Sweden)

    Zamir Maturana Córdoba

    2010-04-01

    Full Text Available A zoning map of areas which flood due to the Atrato River and its tributaries (the Cabí, Caraño and Yesca over-flowing in the urban area of Chocó (Quibdo was drawn up to be used by aid authorities and Quibdó city as a planning and control tool. This research relied on CIAF (Centro Interamericano de Fotointerpretación support and assessment. This entity is a subsidiary institution of the Instituto Geográfico Agustín Codazzi which provided their installations and the required geographical material. This research was initially based on interpreting radar (INTERA, satellite (LANDSAT and aerial photographic images; this was verified by field verification of the in-terpreted data. Other variables such as climatic, geological, temperature, topographic conditions, historic and hydrological series and facts regarding the region were studied as additional information required for drawing conclusions. Aerial photographs provided the most reliable images due to their scales, quantity and quality and the date of when they were taken. Radar images (INTERA were also important when visually analysing a sector’s topography as they were produced by an active microwave sensor (totally eliminating climatic obstacles. On the contrary, satellite images did not have great relevance due to the amount of clouds hampering any kind of analysis. Complementing these results, a calibration curve for analysing this section’s maximum flow values was based on historical series data regarding the Atrato River’s flows and maximum levels recorded at the Quibdo hydrographical station and the river-bed’s cross-section. Implications that the river would overflow or has over-flowed were statistically estimated on these results, thereby setting the limits (supported by cartographic data for the corresponding areas at risk of flooding. A map marking areas at risk of flooding in the urban zone of Quibdó was then designed and a document prepared concluding that

  16. Using Progressive Resolution to Visualize large Satellite Image dataset

    Science.gov (United States)

    ho, yuan; ramanmurthy, mohan

    2014-05-01

    Unidata's Integrated Data Viewer (IDV) is a Java-based software application that provides new and innovative ways of displaying satellite imagery, gridded data, and surface, upper air, and radar data within a unified interface. Progressive Resolution (PR) is a advanced feature newly developed in the IDV. When loading a large satellite dataset with PR turned on, the IDV calculates the resolution of the view window, sets the magnification factors dynamically, and loads a sufficient amount of the data to generate an image at the correct resolution. A rubber band box (RBB) interface allows the user to zoom in/out or change the projection, forcing the IDV to recalculate the magnification factors and get higher/lower resolution data. This new feature improves the IDV memory usage significantly. In the preliminary test, loading 100 time steps of GOES-East 1 km 0.65 visible image data (100 X 10904 X 6928) with PR, both memory and CPU usage are comparable to generating a single time-step display at full resolution (10904 X 6928), and the quality of the resulting image is not compromised. The PR feature is currently available for both satellite imagery and gridded datasets, and will be expanded to other datasets. In this presentation we will present examples of PR usage with large satellite datasets for academic investigations and scientific discovery.

  17. TecLines: A MATLAB-Based Toolbox for Tectonic Lineament Analysis from Satellite Images and DEMs, Part 1: Line Segment Detection and Extraction

    Directory of Open Access Journals (Sweden)

    Mehdi Rahnama

    2014-06-01

    Full Text Available Geological structures, such as faults and fractures, appear as image discontinuities or lineaments in remote sensing data. Geologic lineament mapping is a very important issue in geo-engineering, especially for construction site selection, seismic, and risk assessment, mineral exploration and hydrogeological research. Classical methods of lineaments extraction are based on semi-automated (or visual interpretation of optical data and digital elevation models. We developed a freely available Matlab based toolbox TecLines (Tectonic Lineament Analysis for locating and quantifying lineament patterns using satellite data and digital elevation models. TecLines consists of a set of functions including frequency filtering, spatial filtering, tensor voting, Hough transformation, and polynomial fitting. Due to differences in the mathematical background of the edge detection and edge linking procedure as well as the breadth of the methods, we introduce the approach in two-parts. In this first study, we present the steps that lead to edge detection. We introduce the data pre-processing using selected filters in spatial and frequency domains. We then describe the application of the tensor-voting framework to improve position and length accuracies of the detected lineaments. We demonstrate the robustness of the approach in a complex area in the northeast of Afghanistan using a panchromatic QUICKBIRD-2 image with 1-meter resolution. Finally, we compare the results of TecLines with manual lineament extraction, and other lineament extraction algorithms, as well as a published fault map of the study area.

  18. Polar-Orbiting Satellite (POES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from camera systems or radiometer instruments on satellites in orbit around the poles. Satellite campaigns include...

  19. Satellite based wind resource assessment over the South China Sea

    DEFF Research Database (Denmark)

    Badger, Merete; Astrup, Poul; Hasager, Charlotte Bay;

    2014-01-01

    modeling to develop procedures and best practices for satellite based wind resource assessment offshore. All existing satellite images from the Envisat Advanced SAR sensor by the European Space Agency (2002-12) have been collected over a domain in the South China Sea. Wind speed is first retrieved from...... description in order to calculate the mean wind climate at different levels up to 100 m. Time series from coarser-resolution satellite wind products i.e. the Special Sensor Microwave Imager (SSM/I) data are used to calculate the long-term temporal variability of the wind climate. This can be used...

  20. A stochastic ensemble-based model to predict crop water requirements from numerical weather forecasts and VIS-NIR high resolution satellite images in Southern Italy

    Science.gov (United States)

    Pelosi, Anna; Falanga Bolognesi, Salvatore; De Michele, Carlo; Medina Gonzalez, Hanoi; Villani, Paolo; D'Urso, Guido; Battista Chirico, Giovanni

    2015-04-01

    Irrigation agriculture is one the biggest consumer of water in Europe, especially in southern regions, where it accounts for up to 70% of the total water consumption. The EU Common Agricultural Policy, combined with the Water Framework Directive, imposes to farmers and irrigation managers a substantial increase of the efficiency in the use of water in agriculture for the next decade. Ensemble numerical weather predictions can be valuable data for developing operational advisory irrigation services. We propose a stochastic ensemble-based model providing spatial and temporal estimates of crop water requirements, implemented within an advisory service offering detailed maps of irrigation water requirements and crop water consumption estimates, to be used by water irrigation managers and farmers. The stochastic model combines estimates of crop potential evapotranspiration retrieved from ensemble numerical weather forecasts (COSMO-LEPS, 16 members, 7 km resolution) and canopy parameters (LAI, albedo, fractional vegetation cover) derived from high resolution satellite images in the visible and near infrared wavelengths. The service provides users with daily estimates of crop water requirements for lead times up to five days. The temporal evolution of the crop potential evapotranspiration is simulated with autoregressive models. An ensemble Kalman filter is employed for updating model states by assimilating both ground based meteorological variables (where available) and numerical weather forecasts. The model has been applied in Campania region (Southern Italy), where a satellite assisted irrigation advisory service has been operating since 2006. This work presents the results of the system performance for one year of experimental service. The results suggest that the proposed model can be an effective support for a sustainable use and management of irrigation water, under conditions of water scarcity and drought. Since the evapotranspiration term represents a staple

  1. Numerical simulations of imaging satellites with optical interferometry

    Science.gov (United States)

    Ding, Yuanyuan; Wang, Chaoyan; Chen, Zhendong

    2015-08-01

    Optical interferometry imaging system, which is composed of multiple sub-apertures, is a type of sensor that can break through the aperture limit and realize the high resolution imaging. This technique can be utilized to precisely measure the shapes, sizes and position of astronomical objects and satellites, it also can realize to space exploration and space debris, satellite monitoring and survey. Fizeau-Type optical aperture synthesis telescope has the advantage of short baselines, common mount and multiple sub-apertures, so it is feasible for instantaneous direct imaging through focal plane combination.Since 2002, the researchers of Shanghai Astronomical Observatory have developed the study of optical interferometry technique. For array configurations, there are two optimal array configurations proposed instead of the symmetrical circular distribution: the asymmetrical circular distribution and the Y-type distribution. On this basis, two kinds of structure were proposed based on Fizeau interferometric telescope. One is Y-type independent sub-aperture telescope, the other one is segmented mirrors telescope with common secondary mirror.In this paper, we will give the description of interferometric telescope and image acquisition. Then we will mainly concerned the simulations of image restoration based on Y-type telescope and segmented mirrors telescope. The Richardson-Lucy (RL) method, Winner method and the Ordered Subsets Expectation Maximization (OS-EM) method are studied in this paper. We will analyze the influence of different stop rules too. At the last of the paper, we will present the reconstruction results of images of some satellites.

  2. Tracking target objects orbiting earth using satellite-based telescopes

    Science.gov (United States)

    De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

    2014-10-14

    A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

  3. Physical aspects to consider in radiometric calibration of satellite images

    CERN Document Server

    Delgado-Correal, Camilo

    2012-01-01

    It does a revision about the physical principles involved in digital processing of satellite images, more specifically in radiometric calibration of them. It shows a conceptual description of the interaction between radiation and atmosphere and radiation and soil in order to help the reader understand in more detail which means the information contained in satellite images.

  4. Mapping Vineyard Areas Using WORLDVIEW-2 Satellite Images

    Science.gov (United States)

    Sertel, E.; Ozelkan, E.; Yay, I.; Seker, D. Z.; Ormeci, C.

    2011-12-01

    The observation of Earth surface from the space has lead to new research possibilities in many fields like agriculture, hydrology, geology, geodesy etc. Different satellite image data have been used for agricultural monitoring for different scales namely local, regional and global. It is important to monitor agricultural field in local scale to determine the crop yield, diseases, and to provide Farmer Registries. Worldview-2 is a new satellite system that could be used for agricultural applications especially in local scale. It is the first high resolution 8-band multispectral commercial satellite launched in October 2009. The satellite has an altitude of 770 kilometers and its spatial resolution for panchromatic mode and multispectral mode are 46 cm and 1.85 meter, respectively. In addition to red (630 - 690 nm), blue (450 - 510 nm), Green (510 - 580 nm) and Near Infrared (770 - 895 nm) bands, Worldview-2 has four new spectral bands lying on beginning of blue (400 - 450 nm), yellow (585 - 625 nm), red edge (705 - 745 nm) and Near Infrared (860 - 1040 nm) regions of the electromagnetic spectrum. Since Worldview-2 data are comparatively new, there have not been many studies in the literature about the usage of these new data for different applications. In this research, Worldview-2 data were used to delineate the vineyard areas and identify different grape types in Sarkoy, Turkey. Phenological observations of grape fields have been conducted for the last three years over a huge test area owned by the Government Viniculture Institute. Based on the phenological observations, it was found that July and August period is the best data acquisition time for satellite data since leaf area index is really higher. In August 2011, Worldview-2 data of the region were acquired and spectral measurements were collected in the field for different grape types using a spectroradiometer. Satellite image data and spectral measurements were correlated and satellite image data were

  5. Smoothing of Fused Spectral Consistent Satellite Images

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2006-01-01

    Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain spectral consistency of the fused high resolution image, which is of high importance to many of the applications based...... statistically meaningful way. The fusion method was called spectral consistent panshapen- ing (SC) and it was shown that spectral consistency was a direct consequence of imaging physics and hence guaranteed by the SCP. In this paper exploit this framework and investigate two smoothing methods of the fused image...... obtain by SCP. The first smoothing method is based on Markov random field (MRF) model, while the second method uses wavelet domain hidden Markov models (HMM) for smoothing of the SCP fused image....

  6. Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

    Science.gov (United States)

    Song, Huihui

    Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

  7. Spatial Data Exploring by Satellite Image Distributed Processing

    Science.gov (United States)

    Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

    2012-04-01

    Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands

  8. Detection of Barchan Dunes in High Resolution Satellite Images

    Science.gov (United States)

    Azzaoui, M. A.; Adnani, M.; El Belrhiti, H.; Chaouki, I. E.; Masmoudi, C.

    2016-06-01

    Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden's J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

  9. Accuracy assessment of topographic mapping using UAV image integrated with satellite images

    International Nuclear Information System (INIS)

    Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate. Furthermore, UAV images will be integrated with QuickBird images that are used as base maps. The objective of this study is to make accuracy assessment and comparison between topographic mapping using UAV images integrated with aerial photograph and satellite image. The main purpose of using UAV image is as a replacement for cloud covered area which normally exists in aerial photograph and satellite image, and for updating topographic map. Meanwhile, spatial resolution, pixel size, scale, geometric accuracy and correction, image quality and information contents are important requirements needed for the generation of topographic map using these kinds of data. In this study, ground control points (GCPs) and check points (CPs) were established using real time kinematic Global Positioning System (RTK-GPS) technique. There are two types of analysis that are carried out in this study which are quantitative and qualitative assessments. Quantitative assessment is carried out by calculating root mean square error (RMSE). The outputs of this study include topographic map and orthophoto. From this study, the accuracy of UAV image is ± 0.460 m. As conclusion, UAV image has the potential to be used for updating of topographic maps

  10. A spatial-temporal-spectral blending model using satellite images

    Science.gov (United States)

    Zhang, L.; Fu, D.; Sun, X.; Chen, H.; She, X.

    2016-04-01

    Due to the budget and technical limitations, remote sensing sensor designs trade spatial resolution, swath width and spectral resolution. Consequently, no sensor can provide high spatial resolution, high temporal resolution and high spectral resolution simultaneously. However, the ability of Earth observation at fine resolution is urgently needed for global change science. One possible solution is to “blend” the reflectance from a variety of satellite data sources, including those providing high spatial resolution and less frequent coverage (e.g., Landsat Thematic Mapper, TM), daily global data (e.g., Moderate Resolution Imaging Spectroradiometer, MODIS), and high spectral resolution and infrequent revisit cycle (e.g., Hyperion). However, the previous algorithms for blending multi-source remotely sensed data have some shortcomings, especially with regard to hyperspectral information. This study has developed a SPAtial-Temporal-Spectral blending model (SPATS) that can simulate surface reflectance with high spatial-temporal-spectral resolution. SPATS is based on an existing spatial-temporal image blending model and a spatial-spectral image blending model. The performance of SPATS was tested with both simulated and observed satellite data, using Landsat TM, Hyperion and MODIS data, as well as heterogeneous landscapes as examples. The results show that the high spatial-temporal-spectral resolution reflectance data can be applied to investigations of global landscapes that are changing at different temporal scales.

  11. Image Positioning Accuracy Analysis for the Super Low Altitude Remote Sensing Satellite

    OpenAIRE

    Ming Xu; Nan Zhou

    2012-01-01

    Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line‐of‐sight rebuilding of each detection element and this direction precisely intersecting with the Earth’s elliptical when the camera on the satellite is ima...

  12. Satellite image collection modeling for large area hazard emergency response

    Science.gov (United States)

    Liu, Shufan; Hodgson, Michael E.

    2016-08-01

    Timely collection of critical hazard information is the key to intelligent and effective hazard emergency response decisions. Satellite remote sensing imagery provides an effective way to collect critical information. Natural hazards, however, often have large impact areas - larger than a single satellite scene. Additionally, the hazard impact area may be discontinuous, particularly in flooding or tornado hazard events. In this paper, a spatial optimization model is proposed to solve the large area satellite image acquisition planning problem in the context of hazard emergency response. In the model, a large hazard impact area is represented as multiple polygons and image collection priorities for different portion of impact area are addressed. The optimization problem is solved with an exact algorithm. Application results demonstrate that the proposed method can address the satellite image acquisition planning problem. A spatial decision support system supporting the optimization model was developed. Several examples of image acquisition problems are used to demonstrate the complexity of the problem and derive optimized solutions.

  13. Kansas Satellite Image Database (KSID) 2004-2005

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID) 2004-2005 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM)...

  14. Landsat TM and ETM+ Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...

  15. Improving Quantitative Measurements using Different Segmentation Techniques for Satellite Images

    OpenAIRE

    Ravi Kumar, K.; K. Kavindra Kumar; R.S.V.M.Krishna; P. K. Bharadwaj

    2011-01-01

    Image segmentation is the most practical approach among all virtually automated image recognition systems. Feature extraction and recognition have numerous applications on telecommunication, weather forecasting, environment exploration and medical diagnosis. This paper deals with different image segmentation algorithms. The quality of satellite image is affected by atmosphere, temperature etc. By the usage of various segmentation techniques ,the image is divided into parts which have strong ...

  16. A low cost thermal infrared hyperspectral imager for small satellites

    Science.gov (United States)

    Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.; Wood, M.

    2012-06-01

    The growth of the small satellite market and launch opportunities for these satellites is creating a new niche for earth observations that contrasts with the long mission durations, high costs, and long development times associated with traditional space-based earth observations. Low-cost, short-lived missions made possible by this new approach provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off-the-shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCoR), to demonstrate ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power-efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable use of COTS electronics and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230 meter pixels with 20 wavenumber spectral resolution from a 400 km orbit. We are currently in the laboratory and airborne testing stage in order to demonstrate the spectro-radiometric quality of data that the instrument provides.

  17. 基于AMPL的多成像卫星任务调度与规划%Multiple imaging satellites scheduling method based on AMPL modeling language

    Institute of Scientific and Technical Information of China (English)

    胡海洋; 张学庆; 刘喆; 葛宁

    2012-01-01

    The imaging reconnaissance satellite scheduling denotes a mission that optimizes the limited resources of several earth-observing satellites to observe the ground targets according to the demands of custo-mers. Because this mission involves the scheduling and optimization of multiple satellites, it is a challenging topic in the academic fields. After thoroughly investigating the working principles of earth-observing satellites and primary constraints in this scheduling mission, a mixed linear scheduling model that meets the requirements of multiple satellites and multiple monitoring targets in the imaging reconnaissance satellite system is proposed and the related data are used to verify the reasonableness of this newly proposed model. Then, a new method that adopts a mathematical programming language (AMPL) modeling language is employed to solve problems' I. E. , there are various algorithms to solve this kind of constraint satisfaction problem and it is hard to evaluate the efficiency of different algorithms uniformly. The data downloaded from the satellite tool kit (STK) are also experimented in AMPL modeling language to test this method. The AMPL language can adopt solvers that combine several efficient algorithms automatically. The experiment results demonstrate that, compared with normal methods, the proposed method can solve the middle and short term scheduling problem efficiently and concisely.%成像卫星调度问题是利用在太空中运行的多个对地观测卫星,根据用户的需要,最大限度利用卫星系统的资源实现对地面目标进行观测.该系统涉及多个成像卫星的调度和规划,因此一直以来都是一个富有挑战性的课题.在分析成像卫星工作原理和调度任务约束条件的基础上,首先建立了一个满足多卫星、多监测目标的混合线性模型,并对模型的合理性加以论证.其次,采用一种数学建模语言(a mathematical programming language,AMPL)解决该调度问题的

  18. Image Positioning Accuracy Analysis for the Super Low Altitude Remote Sensing Satellite

    Directory of Open Access Journals (Sweden)

    Ming Xu

    2012-10-01

    Full Text Available Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line‐of‐sight rebuilding of each detection element and this direction precisely intersecting with the Earth’s elliptical when the camera on the satellite is imaging are both ensured by the combined design of key parameters. These parameters include: orbit determination accuracy, attitude determination accuracy, camera exposure time, accurately synchronizing the reception of ephemeris with attitude data, geometric calibration and precise orbit verification. Precise simulation calculations show that image positioning accuracy of super low altitude remote sensing satellites is not obviously improved. The attitude determination error of a satellite still restricts its positioning accuracy.

  19. Multi-spectral band selection for satellite-based systems

    International Nuclear Information System (INIS)

    The design of satellite based multispectral imaging systems requires the consideration of a number of tradeoffs between cost and performance. The authors have recently been involved in the design and evaluation of a satellite based multispectral sensor operating from the visible through the long wavelength IR. The criteria that led to some of the proposed designs and the modeling used to evaluate and fine tune the designs will both be discussed. These criteria emphasized the use of bands for surface temperature retrieval and the correction of atmospheric effects. The impact of cost estimate changes on the final design will also be discussed

  20. A study on quality and availability of COCTS images of HY- 1 satellite by simulation

    Institute of Scientific and Technical Information of China (English)

    李淑菁; 毛天明; 潘德炉

    2002-01-01

    Hy-1 is a first China's ocean color satellite which will be launched as a piggyback satellite on FY- 1 satellite using Long March rocket. On the satellite there are two sensors: one is the China's ocean color and temperature scanner (COCTS), the other is CCD coastal zone imager (CZI).The COCTS is considered to be a main sensor to play a key role. In order to understand the characteristics of future ocean color images observed, a simulation and evaluation study on the quality and availability of the COCTS image has been done. First, the simulation models are introduced briefly, and typical simulated cases of radiance images at visible bands are introduced, in which the radiance distribution is based on geographic location, the satellite orbital parameters and sensor properties, the simulated method to evaluate the image quality and availability is developed by using the characteristics of image called the complex signal noise ratio ( CSNR ). Meanwhile, a series of the CSNR images are generated from the simulated radiance components for different cases, which can be used to evaluate the quality and availability of the COCTS images before the HY - 1 is placed in orbit. Finally, the quality and availability of the COCTS images are quantitatively analyzed with the simulated CSNR data. The results will be beneficial to all scientists who are in charge of the COCTS mission and to those who plan to use the data from the COCTS.

  1. Control of satellite imaging arrays in multi-body regimes

    Science.gov (United States)

    Millard, Lindsay Demoore

    In the current study, control strategies are investigated for spacecraft imaging formations in multi-body regimes. The specific focus of the analysis is spacecraft motion as modeled in the circular restricted three-body problem, where two large gravitational bodies affect the motion of spacecraft in their vicinity. Five equilibrium points, or libration points, exist as solutions to the differential equations of motion in the circular restricted three-body problem. A specific periodic solution to these equations is an orbit in the vicinity of a libration point, i.e., a halo orbit. Halo orbits are ideal locations for spacecraft imaging arrays as they remain at a nearly fixed distance from the larger, or primary, bodies in the system. For example, if the Sun and Earth are considered the primary bodies, a spacecraft array can be placed near a libration point on the far side of the Earth, protected from the harsh radiation of the Sun at all times. A model of image reconstruction is developed for two common satellite imaging platform designs: an interferometric sparse aperture array and an occulter-telescope formation. The resolution of an image produced by an array is largely determined by the corresponding coverage of the (u, v) plane. The (u, v) plane is not a physical plane, but rather a relationship between frequencies and amplitudes in the Fourier expansion of the electromagnetic signal from the object of interest. Coverage of the (u, v) plane is derived based on several characteristics of the spacecraft configuration and the motion in physical space. Therefore, to determine formation motion history that may be advantageous to imaging, a mathematical model relating spacecraft motion in physical space to coverage of the (u, v) plane, and thus image reconstruction, is necessary. From these models, two control algorithms are developed that increase the resolution of the images produced by the formation while exploiting multi-body dynamics to reduce satellite fuel

  2. Reducing uncertainty on satellite image classification through spatiotemporal reasoning

    Science.gov (United States)

    Partsinevelos, Panagiotis; Nikolakaki, Natassa; Psillakis, Periklis; Miliaresis, George; Xanthakis, Michail

    2014-05-01

    The natural habitat constantly endures both inherent natural and human-induced influences. Remote sensing has been providing monitoring oriented solutions regarding the natural Earth surface, by offering a series of tools and methodologies which contribute to prudent environmental management. Processing and analysis of multi-temporal satellite images for the observation of the land changes include often classification and change-detection techniques. These error prone procedures are influenced mainly by the distinctive characteristics of the study areas, the remote sensing systems limitations and the image analysis processes. The present study takes advantage of the temporal continuity of multi-temporal classified images, in order to reduce classification uncertainty, based on reasoning rules. More specifically, pixel groups that temporally oscillate between classes are liable to misclassification or indicate problematic areas. On the other hand, constant pixel group growth indicates a pressure prone area. Computational tools are developed in order to disclose the alterations in land use dynamics and offer a spatial reference to the pressures that land use classes endure and impose between them. Moreover, by revealing areas that are susceptible to misclassification, we propose specific target site selection for training during the process of supervised classification. The underlying objective is to contribute to the understanding and analysis of anthropogenic and environmental factors that influence land use changes. The developed algorithms have been tested upon Landsat satellite image time series, depicting the National Park of Ainos in Kefallinia, Greece, where the unique in the world Abies cephalonica grows. Along with the minor changes and pressures indicated in the test area due to harvesting and other human interventions, the developed algorithms successfully captured fire incidents that have been historically confirmed. Overall, the results have shown that

  3. Geo-Positioning Accuracy Using Multiple-Satellite Images: IKONOS, QuickBird, and KOMPSAT-2 Stereo Images

    OpenAIRE

    Jaehoon Jeong; Chansu Yang; Taejung Kim

    2015-01-01

    This paper investigates the positioning accuracy of image pairs achieved by integrating images from multiple satellites. High-resolution satellite images from IKONOS, QuickBird, and KOMPSAT-2 for Daejeon, Korea were combined to produce pairs of stereo images. From single-satellite stereo pairs to multiple-satellite image pairs, all available combinations were analyzed via a rational function model (RFM). The positioning accuracy of multiple-satellite pairs was compared to a typical single-sat...

  4. Soil moisture estimation using satellite microwave/imager satellite data over a grassland region

    International Nuclear Information System (INIS)

    The special sensor microwave/imager (SSM/I) is an instrument that has been a component of several satellite platforms since 1987. Although not designed for soil moisture sensing, it is possible based on theory to extract soil moisture information under some conditions. The limiting feature of the SSM/I for soil moisture-related studies is that the frequencies are quite high and are significantly affected by vegetation. However, other features of the data, such as the frequency of measurements, are very good for observing time-varying hydrologic variables such as soil moisture. There have been no quantitative evaluations of the SSM/I using observed soil moisture data. In this study, data collected in two large-scale experiments conducted over the Little Washita watershed, in Oklahoma were available for evaluating the capabilities of SSM/I data for soil moisture mapping. Physically based models were used to relate the satellite data to the ground observations. The results indicated that for this grass-dominated subhumid area a soil moisture-emissivity relationship with an error of estimate of 5.3% could be developed that incorporated the range of temperature and vegetation conditions encountered. An approach to adapting this approach for other vegetation regimes is still needed for wider application

  5. Lorentz Force Based Satellite Attitude Control

    Science.gov (United States)

    Giri, Dipak Kumar; Sinha, Manoranjan

    2016-07-01

    Since the inception of attitude control of a satellite, various active and passive control strategies have been developed. These include using thrusters, momentum wheels, control moment gyros and magnetic torquers. In this present work, a new technique named Lorentz force based Coulombic actuators for the active control is proposed. This method uses electrostatic charged shells, which interact with the time varying earth's magnetic field to establish a full three axes control of the satellite. It is shown that the proposed actuation mechanism is similar to a satellite actuated by magnetic coils except that the resultant magnetic moment vanishes under two different conditions. The equation for the required charges on the the Coulomb shells attached to the satellite body axes is derived, which is in turn used to find the available control torque for actuating the satellite along the orbit. Stability of the proposed system for very high initial angular velocity and exponential stability about the origin are proved for a proportional-differential control input. Simulations are carried out to show the efficacy of the proposed system for the attitude control of the earth-pointing satellite.

  6. Wavelet Analysis of Satellite Images for Coastal Watch

    Science.gov (United States)

    Liu, Antony K.; Peng, Chich Y.; Chang, Steve Y.-S.

    1997-01-01

    The two-dimensional wavelet transform is a very efficient bandpass filter, which can be used to separate various scales of processes and show their relative phase/location. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite imagery employing wavelet analysis are developed. The wavelet transform has been applied to satellite images, such as those from synthetic aperture radar (SAR), advanced very-high-resolution radiometer (AVHRR), and coastal zone color scanner (CZCS) for feature extraction. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ship wakes can be tracked by the wavelet analysis using satellite data from repeating paths. Several examples of the wavelet analysis applied to various satellite Images demonstrate the feasibility of this technique for coastal monitoring.

  7. A System to Detect Residential Area in Multispectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Seyfallah Bouraoui

    2011-11-01

    Full Text Available In this paper, we propose a new solution to extract complex structures from High-Resolution (HR remote-sensing images. We propose to represent shapes and there relations by using region adjacency graphs. They are generated automatically from the segmented images. Thus, the nodes of the graph represent shape like houses, streets or trees, while arcs describe the adjacency relation between them. In order to be invariant to transformations such as rotation and scaling, the extraction of objects of interest is done by combining two techniques: one based on roof color to detect the bounding boxes of houses, and one based on mathematical morphology notions to detect streets. To recognize residential areas, a model described by a regular language is built. The detection is achieved by looking for a path in the region adjacency graph, which can be recognized as a word belonging to the description language. Our algorithm was tested with success on images from the French satellite SPOT 5 representing the urban area of Strasbourg (France at different spatial resolution.

  8. Autonomous Planetary 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz

    1999-01-01

    A common task for many deep space missions is autonomous generation of 3-D representations of planetary surfaces onboard unmanned spacecrafts. The basic problem for this class of missions is, that the closed loop time is far too long. The closed loop time is defined as the time from when a human...... of seconds to a few minutes, the closed loop time effectively precludes active human control.The only way to circumvent this problem is to build an artificial feature extractor operating autonomously onboard the spacecraft.Different artificial feature extractors are presented and their efficiency...... is discussed.Based on such features, 3-D representations may be compiled from two or more 2-D satellite images. The main purposes of such a mapping system are extraction of landing sites, objects of scientific interest and general planetary surveying. All data processing is performed autonomously onboard...

  9. Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

    Directory of Open Access Journals (Sweden)

    Maocai Wang

    2014-01-01

    Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.

  10. Classification of Pansharpened Urban Satellite Images

    DEFF Research Database (Denmark)

    Palsson, Frosti; Sveinsson, Johannes R.; Benediktsson, Jon Atli;

    2012-01-01

    information from the panchromatic data. Random Forests (RF) and Support Vector Machines (SVM) will be used as classifiers. Experiments are done for three different datasets that have been obtained by two different imaging sensors, IKONOS and QuickBird. These sensors deliver multispectral images that have four...

  11. Recurrent neural networks for automatic clustering of multispectral satellite images

    Science.gov (United States)

    Koprinkova-Hristova, Petia; Alexiev, Kiril; Borisova, Denitsa; Jelev, Georgi; Atanassov, Valentin

    2013-10-01

    In the present work we applied a recently developed procedure for multidimensional data clustering to multispectral satellite images. The core of our approach lays in projection of the multidimensional image to a two dimensional space. For this purpose we used extensively investigated family of recurrent artificial neural networks (RNN) called "Echo state network" (ESN). ESN incorporates a randomly generated recurrent reservoir with sigmoid nonlinearities of neurons outputs. The procedure called Intrinsic Plasticity (IP) that is aimed at reservoir output entropy maximization was applied for adapting of reservoir steady states to the multidimensional input data. Next we consider all possible combinations between steady states of each two neurons in the reservoir as two-dimensional projections of the original multidimensional data. These low dimensional projections were subjected to subtractive clustering in order to determine number and position of data clusters. Two approaches to choose a proper projection among the all possible combinations between neurons were investigated. The first one is based on the calculation of two-dimensional density distributions of each projection, determination of number of their local maxima and choice of the projections with biggest number of these maxima. The second one applies clustering to all projections and chooses those with maximum number of clusters. Multispectral data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument are used in this work. The obtained number and position of clusters of a multi-spectral image of a mountain region in Bulgaria is compared with the regional landscape classification.

  12. Urban area extraction from a satellite image

    Science.gov (United States)

    Marthon, Philippe; Caron, Vincent; Cubero-Castan, Eliane

    1995-11-01

    In a SPOT image, urban areas generally appear as agglomerates of numerous little uniform regions. So, they have a typical feature which is a high edge density. In a single sweeping of the image, each edge pixel is tested: if all the surfaces of neighboring regions are less than a predetermined threshold, the current edge pixel is removed. At the end of sweeping, all the internal edges of urban regions are removed but the external boundary or silhouette is kept. This method has been successfully tested on SPOT XS3 images of the region of Bourges, France.

  13. Multiple Satellites Imaging Scheduling Based on Petri Net and Hybrid Ant Colony Algorithm%基于Petri网和混合蚁群算法的多星成像调度

    Institute of Scientific and Technical Information of China (English)

    龙运军; 陈宇宁; 陈英武; 邢立宁

    2013-01-01

    This paper proposes a multiple satellites imaging icheduling strategy based on Integrated Index Petri Net(IIPN) and hybrid ant colony algorithm, Index information dealing with concurrent observation of multiple satellites and conflict of using satellite resource are introduced into transition, which can also reflect energy and memory constraints, making the problem description more visual and complete. An ant colony algorithm combining with local search is designed to resolve the problem. Index information is integrated in heuristic information for guiding the ants for global search. Local search technique is to accelerate convergence. Experimental results show that the method of can solve the multiple imaging satellites scheduling problem effectively by reaching balance between global search technique and local search technique which is to accelerate convergence.%提出一种基于综合指标Petri网和混合蚁群算法的多星成像调度策略.在综合指标Petri网变迁中引入指标信息,处理多星并发观测和卫星资源竞争关系、反映卫星能量和存储等约束,使得问题描述更直观和完备.设计一种嵌入局部搜索技术的蚁群优化算法,通过启发式信息综合变迁中的指标,引导蚂蚁进行全局搜索.仿真实例结果表明,该策略能有效求解多墨成像调度问题,实现全局搜索和快速收敛的平衡.

  14. Satellite image analysis for surveillance, vegetation and climate change

    Energy Technology Data Exchange (ETDEWEB)

    Cai, D Michael [Los Alamos National Laboratory

    2011-01-18

    Recently, many studies have provided abundant evidence to show the trend of tree mortality is increasing in many regions, and the cause of tree mortality is associated with drought, insect outbreak, or fire. Unfortunately, there is no current capability available to monitor vegetation changes, and correlate and predict tree mortality with CO{sub 2} change, and climate change on the global scale. Different survey platforms (methods) have been used for forest management. Typical ground-based forest surveys measure tree stem diameter, species, and alive or dead. The measurements are low-tech and time consuming, but the sample sizes are large, running into millions of trees, covering large areas, and spanning many years. These field surveys provide powerful ground validation for other survey methods such as photo survey, helicopter GPS survey, and aerial overview survey. The satellite imagery has much larger coverage. It is easier to tile the different images together, and more important, the spatial resolution has been improved such that close to or even higher than aerial survey platforms. Today, the remote sensing satellite data have reached sub-meter spatial resolution for panchromatic channels (IKONOS 2: 1 m; Quickbird-2: 0.61 m; Worldview-2: 0.5 m) and meter spatial resolution for multi-spectral channels (IKONOS 2: 4 meter; Quickbird-2: 2.44 m; Worldview-2: 2 m). Therefore, high resolution satellite imagery can allow foresters to discern individual trees. This vital information should allow us to quantify physiological states of trees, e.g. healthy or dead, shape and size of tree crowns, as well as species and functional compositions of trees. This is a powerful data resource, however, due to the vast amount of the data collected daily, it is impossible for human analysts to review the imagery in detail to identify the vital biodiversity information. Thus, in this talk, we will discuss the opportunities and challenges to use high resolution satellite imagery and

  15. 基于岸线配准的海岛礁遥感影像几何纠正方法%Precision Rectification Method for Island Satellite Image Based on Registration of Coastline

    Institute of Scientific and Technical Information of China (English)

    张靓; 孟婵媛; 李军; 辛宪会; 叶秋果; 李海滨; 滕惠忠

    2011-01-01

    The precision rectification of satellite image of remote island is hard to perform for lack of reliable ground control points. In this paper, we present a promising geometric rectification method based on registration of coastline. Supposing the coastline of island is relative stable. Firstly, we retrieve the coastline from the satellite image based on spectrum analysis. Then, we retrieve the coastline from the chart based on the distinctive color of land. Finally, we fulfill the precision rectification by registration of two coastlines. Experiments show that the method is reasonable and results are satisfying.%由于缺少可靠的控制点,很难对遥远海岛进行几何精校正.在假定海岛岸线相对稳定的情况下,提出一种基于海岸线配准的几何校正方法.首先,基于波谱分析从卫星影像提取海岸线;接着,根据海图上陆地特定的颜色提取海岸线;最后,通过将两种岸线进行配准实现了几何精校正.试验表明这个方法可行,校正结果也令人满意.

  16. 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz

    1999-01-01

    The aim of this project has been to implement a software system, that is able to create a 3-D reconstruction from two or more 2-D photographic images made from different positions. The height is determined from the disparity difference of the images. The general purpose of the system is mapping of......, where various methods have been tested in order to optimize the performance. The match results are used in the reconstruction part to establish a 3-D digital representation and finally, different presentation forms are discussed....... treated individually. A detailed treatment of various lens distortions is required, in order to correct for these problems. This subject is included in the acquisition part. In the calibration part, the perspective distortion is removed from the images. Most attention has been paid to the matching problem...

  17. An Algorithm of Inter Satellite Two-Way Time Transfer Based on Mobile Satellite

    Directory of Open Access Journals (Sweden)

    Feijiang Huang

    2013-03-01

    Full Text Available Two-way time transfer is one of the most accurate time synchronization methods applied to spacecrafts and ground stations to carry out time transfer. As this method doesn’t require the knowledge of locations of two satellites in advance and it offsets the negative influence of transmission path and other additional delays, this method has boosted the time synchronization accuracy. However, in the process of time synchronization, this method demands that the aircrafts, who conduct time synchronization, could be relatively static. So it is mainly used in GEO satellites for satellite-ground two-way time transfer. Based on the establishment of mobile satellite mutual visual model, the simulation of satellite mutual visual time on mobile satellite, including IGSO (Inclined Geo Synchronous Orbit satellite and MEO (Medium Earth Orbit satellite, has been conducted. The visual time and the variation range of IGSO-MEO link distance have been gained. The characteristics of the propagation delay of two-way time transfer signals between IGSO satellite and MEO satellite varying with inter satellite range were analyzed and the rule of inter satellite clock offset varying with inter satellite range obtained with this algorithm was deduced. This study presents a inter satellite dynamic two-way time transfer algorithm based on mobile satellite. The high-accuracy inter satellite clock offset is solved through the combination of inter satellite pseudo-range polynomial fitting and clock-offset polynomial fitting. Simulation results showed that with the algorithm the inter satellite time transfer error can be controlled within 1ns. The algorithm can be used high-accuracy time transfer between mobile satellites.

  18. An SDR based AIS receiver for satellites

    DEFF Research Database (Denmark)

    Larsen, Jesper Abildgaard; Mortensen, Hans Peter; Nielsen, Jens Frederik Dalsgaard

    2011-01-01

    For a few years now, there has been a high interest in monitoring the global ship traffic from space. A few satellite, capable of listening for ship borne AIS transponders have already been launched, and soon the AAUSAT3, carrying two different types of AIS receivers will also be launched. One of...... the AIS receivers onboard AAUSAT3 is an SDR based AIS receiver. This paper serves to describe the background of the AIS system, and how the SDR based receiver has been integrated into the AAUSAT3 satellite. Amongst some of the benefits of using an SDR based receiver is, that due to its versatility......, new detection algorithms are easily deployed, and it is easily adapted the new proposed AIS transmission channels....

  19. The cradle of pyramids in satellite images

    OpenAIRE

    Sparavigna, Amelia Carolina

    2011-01-01

    We propose the use of image processing to enhance the Google Maps of some archaeological areas of Egypt. In particular we analyse that place which is considered the cradle of pyramids, where it was announced the discovery of a new pyramid by means of an infrared remote sensing.

  20. Mapping soil heterogeneity using RapidEye satellite images

    Science.gov (United States)

    Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane

    2016-04-01

    In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.

  1. TecLines: A MATLAB-Based Toolbox for Tectonic Lineament Analysis from Satellite Images and DEMs, Part 1: Line Segment Detection and Extraction

    OpenAIRE

    Mehdi Rahnama; Richard Gloaguen

    2014-01-01

    Geological structures, such as faults and fractures, appear as image discontinuities or lineaments in remote sensing data. Geologic lineament mapping is a very important issue in geo-engineering, especially for construction site selection, seismic, and risk assessment, mineral exploration and hydrogeological research. Classical methods of lineaments extraction are based on semi-automated (or visual) interpretation of optical data and digital elevation models. We developed a freely available M...

  2. Cirrus cloud characteristics derived from volume imaging lidar, high spectral resolution lidar, HIS radiometer, and satellite

    Science.gov (United States)

    Grund, Christian J.; Ackerman, Steven A.; Eloranta, Edwin W.; Knutsen, Robert O.; Revercomb, Henry E.; Smith, William L.; Wylie, Donald P.

    1990-01-01

    Preliminary measurement results are presented from the Cirrus Remote Sensing Pilot Experiment which used a unique suite of instruments to simultaneously retrieve cirrus cloud visible and IR optical properties, while addressing the disparities between satellite volume averages and local point measurements. The experiment employed a ground-based high resolution interferometer sounder (HIS) and a second Fourier transform spectrometer to measure the spectral radiance in the 4-20 micron band, a correlated high spectral resolution lidar, a volume imaging lidar, a CLASS radiosonde system, the Scripps Whole Sky Imager, and multispectral VAS, HIRS, and AVHRR satellite data from polar orbiting and geostationary satellites. Data acquired during the month long experiment included continuous daytime monitoring with the Whole Sky Imager.

  3. Supervised learning on graphs of spatio-temporal similarity in satellite image sequences

    CERN Document Server

    Héas, Patrick

    2007-01-01

    High resolution satellite image sequences are multidimensional signals composed of spatio-temporal patterns associated to numerous and various phenomena. Bayesian methods have been previously proposed in (Heas and Datcu, 2005) to code the information contained in satellite image sequences in a graph representation using Bayesian methods. Based on such a representation, this paper further presents a supervised learning methodology of semantics associated to spatio-temporal patterns occurring in satellite image sequences. It enables the recognition and the probabilistic retrieval of similar events. Indeed, graphs are attached to statistical models for spatio-temporal processes, which at their turn describe physical changes in the observed scene. Therefore, we adjust a parametric model evaluating similarity types between graph patterns in order to represent user-specific semantics attached to spatio-temporal phenomena. The learning step is performed by the incremental definition of similarity types via user-prov...

  4. Stellar Source Selections for Image Validation of Earth Observation Satellite

    Science.gov (United States)

    Yu, Jiwoong; Park, Sang-Young; Lim, Dongwook; Lee, Dong-Han; Sohn, Young-Jong

    2011-12-01

    A method of stellar source selection for validating the quality of image is investigated for a low Earth orbit optical remote sensing satellite. Image performance of the optical payload needs to be validated after its launch into orbit. The stellar sources are ideal source points that can be used to validate the quality of optical images. For the image validation, stellar sources should be the brightest as possible in the charge-coupled device dynamic range. The time delayed and integration technique, which is used to observe the ground, is also performed to observe the selected stars. The relations between the incident radiance at aperture and V magnitude of a star are established using Gunn & Stryker's star catalogue of spectrum. Applying this result, an appropriate image performance index is determined, and suitable stars and areas of the sky scene are selected for the optical payload on a remote sensing satellite to observe. The result of this research can be utilized to validate the quality of optical payload of a satellite in orbit.

  5. Identification of geostationary satellites using polarization data from unresolved images

    Science.gov (United States)

    Speicher, Andy

    In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. Since resolved images of geosynchronous satellites are not technically feasible with current technology, another method of distinguishing space objects was explored that exploits the polarization signature from unresolved images. The objective of this study was to collect and analyze visible-spectrum polarization data from unresolved images of geosynchronous satellites taken over various solar phase angles. Different collection geometries were used to evaluate the polarization contribution of solar arrays, thermal control materials, antennas, and the satellite bus as the solar phase angle changed. Since materials on space objects age due to the space environment, it was postulated that their polarization signature may change enough to allow discrimination of identical satellites launched at different times. The instrumentation used in this experiment was a United States Air Force Academy (USAFA) Department of Physics system that consists of a 20-inch Ritchey-Chretien telescope and a dual focal plane optical train fed with a polarizing beam splitter. A rigorous calibration of the system was performed that included corrections for pixel bias, dark current, and response. Additionally, the two channel polarimeter was calibrated by experimentally determining the Mueller matrix for the system and relating image intensity at the two cameras to Stokes parameters S0 and S1. After the system calibration, polarization data was collected during three nights on eight geosynchronous satellites built by various manufacturers and launched several years apart. Three pairs of the eight

  6. Contrast enhancement for satellite image segmentation with fuzzy cluster means using morphological filtering

    Science.gov (United States)

    Harsiti; Munandar, T. A.; Suhendar, A.; Abdullah, A. G.; Rohendi, D.

    2016-04-01

    Image segmentation is a stage in image processing, responsible for dividing an image into regions homogeneous, based on the similarity. Suppose the grey level of a pixel by pixel gray neighbors. The quality of image segmentation is generally influenced by the characteristics and the handling of images to be processed. This paper presents the results of satellite image segmentation using a fuzzy cluster region means (FCM). To improve the contrast of the image, conducted morphological filtering techniques. Satellite image analysis performed on five districts in the province of Banten Indonesia. Difference’s segmentation results evident when non-negative parameter value is converted to a 2 and 4. The higher the value of a non-negative parameter is given, then the details of the edges of objects clearer segmentation results. The combined use of a top-hat and boots-hat filtering on objects before satellite imagery analysed by FCM, indicating that it merges with the background object. Background object in the original image is the object of rice fields and is not part of observation in this study. It was identified to have the same gray level similarity with the object of building.

  7. An easy to use ArcMap based texture analysis program for extraction of flooded areas from TerraSAR-X satellite image

    Science.gov (United States)

    Pradhan, Biswajeet; Hagemann, Ulrike; Shafapour Tehrany, Mahyat; Prechtel, Nikolas

    2014-02-01

    Extraction of the flooded areas from synthetic aperture radar (SAR) and especially TerraSAR-X data is one of the most challenging tasks in the flood management and planning. SAR data due to its high spatial resolution and its capability of all weather conditions makes a proper choice for tropical countries. Texture is considered as an effective factor in distinguishing the classes especially in SAR imagery which records the backscatters that carry information of kind, direction, heterogeneity and relationship of the features. This paper put forward a computer program for texture analysis for high resolution radar data. Texture analysis program is introduced and discussed using the gray-level co-occurrence matrix (GLCM). To demonstrate the ability and correctness of this program, a test subset of TerraSAR-X imagery from Terengganu area, Malaysia was analyzed and pixel-based and object-based classification were attempted. The thematic maps derived by pixel-based method could not achieve acceptable visual interpretation and for that reason no accuracy assessment was performed on them. The overall accuracy achieved by object-based method was 83.63% with kappa coefficient of 0.8. Results on image texture classification showed that the proposed program is capable for texture analysis in TerraSAR-X image and the obtained textural analysis resulted in high classification accuracy. The proposed texture analysis program can be used in many applications such as land use/cover (LULC) mapping, hazard studies and many other applications.

  8. Improving multispectral satellite image compression using onboard subpixel registration

    Science.gov (United States)

    Albinet, Mathieu; Camarero, Roberto; Isnard, Maxime; Poulet, Christophe; Perret, Jokin

    2013-09-01

    Future CNES earth observation missions will have to deal with an ever increasing telemetry data rate due to improvements in resolution and addition of spectral bands. Current CNES image compressors implement a discrete wavelet transform (DWT) followed by a bit plane encoding (BPE) but only on a mono spectral basis and do not profit from the multispectral redundancy of the observed scenes. Recent CNES studies have proven a substantial gain on the achievable compression ratio, +20% to +40% on selected scenarios, by implementing a multispectral compression scheme based on a Karhunen Loeve transform (KLT) followed by the classical DWT+BPE. But such results can be achieved only on perfectly registered bands; a default of registration as low as 0.5 pixel ruins all the benefits of multispectral compression. In this work, we first study the possibility to implement a multi-bands subpixel onboard registration based on registration grids generated on-the-fly by the satellite attitude control system and simplified resampling and interpolation techniques. Indeed bands registration is usually performed on ground using sophisticated techniques too computationally intensive for onboard use. This fully quantized algorithm is tuned to meet acceptable registration performances within stringent image quality criteria, with the objective of onboard real-time processing. In a second part, we describe a FPGA implementation developed to evaluate the design complexity and, by extrapolation, the data rate achievable on a spacequalified ASIC. Finally, we present the impact of this approach on the processing chain not only onboard but also on ground and the impacts on the design of the instrument.

  9. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    OpenAIRE

    Marc Wieland; Massimiliano Pittore

    2014-01-01

    In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS) and very high resolution (WorldView-2, Quickbird, Ikonos) multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognitio...

  10. Assessing land-use and carbon stock in slash-and-burn ecosystems in tropical mountain of Laos based on time-series satellite images

    Science.gov (United States)

    Inoue, Yoshio; Kiyono, Yoshiyuki; Asai, Hidetoshi; Ochiai, Yukihito; Qi, Jiaguo; Olioso, Albert; Shiraiwa, Tatsuhiko; Horie, Takeshi; Saito, Kazuki; Dounagsavanh, Linkham

    2010-08-01

    In the tropical mountains of Southeast Asia, slash-and-burn (S/B) agriculture is a widely practiced and important food production system. The ecosystem carbon stock in this land-use is linked not only to the carbon exchange with the atmosphere but also with food and resource security. The objective of this study was to provide quantitative information on the land-use and ecosystem carbon stock in the region as well as to infer the impacts of alternative land-use and ecosystem management scenarios on the carbon sequestration potential at a regional scale. The study area was selected in a typical slash-and-burn region in the northern part of Laos. The chrono-sequential changes of land-use such as the relative areas of community age and cropping (C) + fallow (F) patterns were derived from the analysis of time-series satellite images. The chrono-sequential analysis showed that a consistent increase of S/B area during the past three decades and a rapid increase after 1990. Approximately 37% of the whole area was with the community age of 1-5 years, whereas 10% for 6-10 years in 2004. The ecosystem carbon stock at a regional scale was estimated by synthesizing the land-use patterns and semi-empirical carbon stock model derived from in situ measurements where the community age was used as a clue to the linkage. The ecosystem carbon stock in the region was strongly affected by the land-use patterns; the temporal average of carbon stock in 1C + 10F cycles, for example, was greater by 33 MgC ha -1 compared to that in 1C + 2F land-use pattern. The amount of carbon lost from the regional ecosystems during 1990-2004 periods was estimated to be 42 MgC ha -1. The study approach proved to be useful especially in such regions with low data-availability and accessibility. This study revealed the dynamic change of land-use and ecosystem carbon stock in the tropical mountain of Laos as affected by land-use. Results suggest the significant potential of carbon sequestration through

  11. ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    H. Kim

    2012-07-01

    Full Text Available High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF, Signal to Noise Ratio(SNR and Ground Sampling Distance(GSD are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD and National Imagery Interpretability Rating Scale(NIIRS need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.

  12. Object-Based Image Analysis of WORLDVIEW-2 Satellite Data for the Classification of Mangrove Areas in the City of SÃO LUÍS, MARANHÃO State, Brazil

    Science.gov (United States)

    Kux, H. J. H.; Souza, U. D. V.

    2012-07-01

    Taking into account the importance of mangrove environments for the biodiversity of coastal areas, the objective of this paper is to classify the different types of irregular human occupation on the areas of mangrove vegetation in São Luis, capital of Maranhão State, Brazil, considering the OBIA (Object-based Image Analysis) approach with WorldView-2 satellite data and using InterIMAGE, a free image analysis software. A methodology for the study of the area covered by mangroves at the northern portion of the city was proposed to identify the main targets of this area, such as: marsh areas (known locally as Apicum), mangrove forests, tidal channels, blockhouses (irregular constructions), embankments, paved streets and different condominiums. Initially a databank including information on the main types of occupation and environments was established for the area under study. An image fusion (multispectral bands with panchromatic band) was done, to improve the information content of WorldView-2 data. Following an ortho-rectification was made with the dataset used, in order to compare with cartographical data from the municipality, using Ground Control Points (GCPs) collected during field survey. Using the data mining software GEODMA, a series of attributes which characterize the targets of interest was established. Afterwards the classes were structured, a knowledge model was created and the classification performed. The OBIA approach eased mapping of such sensitive areas, showing the irregular occupations and embankments of mangrove forests, reducing its area and damaging the marine biodiversity.

  13. Implementation and experiences of a nationwide automatic satellite image registration system

    Science.gov (United States)

    Holm, Mikael; Parmes, Eija; Vuorela, Arto

    1994-12-01

    A system for automatic ground control point measurement and rectification of satellite images to a nationwide reference database has been developed at VTT. The method is based on feature based matching. The reference database consists of about two hundred thousand features covering the whole Finland. The features are islands and lakes extracted from the nationwide Land Use Classification, produced from Landsat TM - images by the National Land Survey of Finland. Lakes and islands are extracted from the satellite image to be rectified. Their attributes are compared to those in the reference database. Using feature based matching and robust estimation a few hundred ground control points of subpixel accuracy are selected to the rectifi-cation. Images of different resolution can be measured automatically using this system. It has been tested with SPOT, Landsat TM and NOAA AVHRR imagery. The search for control points takes only a few minutes per satellite image. The accuracy of the result has proved to be at least as good as when measuring the control points manually. The method is analysed by the parallaxes between the reference features and the rectified images.

  14. A Novel Method for Road Extraction from Satellite Images .

    OpenAIRE

    Premnath.P; Madava Krishnan.M; S.Arulselvi; Dr Kirankumar

    2013-01-01

    Extended Kalman filter (EKF) has previously been used to extract road maps in satellite images. The extended Kalman filter in general is not an optimal estimator, if the measurement and the state transition model are both linear. In addition, if the initial estimate of the state is wrong, or if the process is modeled incorrectly, the filter may quickly diverge, owing to its linearization. In our new approach, we have combined Unscented Kalman Filter with a special Particle Filter (LLPF) in or...

  15. Operational evapotranspiration based on Earth observation satellites

    Science.gov (United States)

    Gellens-Meulenberghs, Françoise; Ghilain, Nicolas; Arboleda, Alirio; Barrios, Jose-Miguel

    2016-04-01

    Geostationary satellites have the potential to follow fast evolving atmospheric and Earth surface phenomena such those related to cloud cover evolution and diurnal cycle. Since about 15 years, EUMETSAT has set up a network named 'Satellite Application Facility' (SAF, http://www.eumetsat.int/website/home/Satellites/GroundSegment/Safs/index.html) to complement its ground segment. The Land Surface Analysis (LSA) SAF (http://landsaf.meteo.pt/) is devoted to the development of operational products derived from the European meteorological satellites. In particular, an evapotranspiration (ET) product has been developed by the Royal Meteorological Institute of Belgium. Instantaneous and daily integrated results are produced in near real time and are freely available respectively since the end of 2009 and 2010. The products cover Europe, Africa and the Eastern part of South America with the spatial resolution of the SEVIRI sensor on-board Meteosat Second Generation (MSG) satellites. The ET product algorithm (Ghilain et al., 2011) is based on a simplified Soil-Vegetation-Atmosphere transfer (SVAT) scheme, forced with MSG derived radiative products (LSA SAF short and longwave surface fluxes, albedo). It has been extensively validated against in-situ validation data, mainly FLUXNET observations, demonstrating its good performances except in some arid or semi-arid areas. Research has then been pursued to develop an improved version for those areas. Solutions have been found in reviewing some of the model parameterizations and in assimilating additional satellite products (mainly vegetation indices and land surface temperature) into the model. The ET products will be complemented with related latent and sensible heat fluxes, to allow the monitoring of land surface energy partitioning. The new algorithm version should be tested in the LSA-SAF operational computer system in 2016 and results should become accessible to beta-users/regular users by the end of 2016/early 2017. In

  16. Synergy use of satellite images for Vrancea seismic area analysis

    Science.gov (United States)

    Zoran, Maria A.; Ninomiya, Yoshiki; Zoran, Liviu Florin V.

    2004-10-01

    The seismic hazard of Romania is relatively high, mainly due to the subcrustal earthquakes located at the sharp bend of the Southeast Carpathians, in Vrancea region, one of the most seismically active area in Europe. It is crossed by a series of principal and secondary faults. Vrancea area is assumed to be a conjunction of 4 tectonic blocks which lie on the edge of the Eurasian plate. Several GPS monitoring data revealed the motion of the blocks both in horizontal direction (relative motion of 5- 6 millimeters/year), as well as in vertical direction(of a few millimeters/ year).All data information available on the study area have been integrated in a unique database of geologic maps, thematic maps from cartography, land use maps provided by satellite images acquired in different spectral wavelengths by Landsat MSS, TM and ETM, SAR ERS and ASTER during a long term period (1975-2002). Satellite data are excellent for recognizing the continuity and regional relationships of faults . Synergy use of satellite data and image analysis techniques is essential for neotectonic applications, improving greatly the interpretability of the images and subsequent more accurate terrain features and lineament analysis of geologic structures in active seismic areas.

  17. METEOROLOGICAL SATELLITE IMAGES IN GEOGRAPHY CLASSES: a didactic possibility

    Directory of Open Access Journals (Sweden)

    Diego Correia Maia

    2016-01-01

    Full Text Available ABSTRACT: The satellite images are still largely unexplored as didactic resource in geography classes, particularly about meteorology. This article aims to contribute to the development of new methodologies of interpretation and understanding, beyond the construction of pedagogical practices involving meteorological satellite images, concepts and issues related to climate issues. The aim of this paper is to present possibilities for the use of meteorological satellite images in the Teaching of Geography, aiming the promoting and the understanding of contents of air masses and fronts and climatic factors. RESUMO: As imagens de satélite ainda são pouco exploradas como recurso didático nas aulas de Geografia, principalmente aquelas relativas à meteorologia. Este artigo visa contribuir com o desenvolvimento de novas metodologias de interpretação e compreensão, além da construção de práticas pedagógicas envolvendo imagens de satélite meteorológico, conceitos e temas ligados às questões climáticas. Seu objetivo é apresentar possibilidades de utilização das imagens de satélite meteorológico no Ensino de Geografia, visando à promoção e ao entendimento dos conteúdos de massas de ar e frentes e de elementos climáticos. Palavras chave

  18. Cloud pattern prediction from geostationary meteorological satellite images for solar energy forecasting

    Science.gov (United States)

    Cros, S.; Sébastien, N.; Liandrat, O.; Schmutz, N.

    2014-10-01

    Surface solar radiation forecasting permits to predict photovoltaic plant production for a massive and safe integration of solar energy into the electric network. For short-term forecasts (intra-day), methods using images from meteorological geostationary satellites are more suitable than numerical weather prediction models. Forecast schemes consist in assessing cloud motion vectors and in extrapolating cloud patterns from a given satellite image in order to predict cloud cover state above a PV plant. Atmospheric motion vectors retrieval techniques have been studied for several decades in order to improve weather forecasts. However, solar energy forecasting requires the extraction of cloud motion vectors on a finer spatial- and time-resolution than those provided for weather forecast applications. Even if motion vector retrieval is a wide research field in image processing related topics, only block-matching techniques are operationally used for solar energy forecasts via satellite images. In this paper, we propose two motion vectors extraction methods originating from video compression techniques (correlation phase and optical flow methods). We implemented them on a 6-day dataset of Meteosat-10 satellite diurnal images. We proceeded to cloud pattern extrapolation and compared predicted cloud maps against actual ones at different time horizons from 15 minutes to 4 hours ahead. Forecast scores were compared to the state-of-the-art (block matching) method. Correlation phase methods do not outperform block-matching but their computation time is about 25 times shorter. Optical flow based method outperforms all the methods with a satisfactory time computing.

  19. A fast and automatic mosaic method for high-resolution satellite images

    Science.gov (United States)

    Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

    2015-12-01

    We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

  20. Effect of satellite formations and imaging modes on global albedo estimation

    Science.gov (United States)

    Nag, Sreeja; Gatebe, Charles K.; Miller, David W.; de Weck, Olivier L.

    2016-05-01

    We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static referencecase. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/m2 or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than

  1. Effect of Satellite Formations and Imaging Modes on Global Albedo Estimation

    Science.gov (United States)

    Nag, Sreeja; Gatebe, Charles K.; Miller, David W.; de Weck, Olivier L.

    2016-01-01

    We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static reference case. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/sq m or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More

  2. Development and validation of satellite based estimates of surface visibility

    Science.gov (United States)

    Brunner, J.; Pierce, R. B.; Lenzen, A.

    2015-10-01

    A satellite based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5% for classifying Clear (V ≥ 30 km), Moderate (10 km ≤ V < 30 km), Low (2 km ≤ V < 10 km) and Poor (V < 2 km) visibilities and shows the most skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network, and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

  3. Dissemination of satellite-based river discharge and flood data

    Science.gov (United States)

    Kettner, A. J.; Brakenridge, G. R.; van Praag, E.; de Groeve, T.; Slayback, D. A.; Cohen, S.

    2014-12-01

    In collaboration with NASA Goddard Spaceflight Center and the European Commission Joint Research Centre, the Dartmouth Flood Observatory (DFO) daily measures and distributes: 1) river discharges, and 2) near real-time flood extents with a global coverage. Satellite-based passive microwave sensors and hydrological modeling are utilized to establish 'remote-sensing based discharge stations', and observed time series cover 1998 to the present. The advantages over in-situ gauged discharges are: a) easy access to remote or due to political reasons isolated locations, b) relatively low maintenance costs to maintain a continuous observational record, and c) the capability to obtain measurements during floods, hazardous conditions that often impair or destroy in-situ stations. Two MODIS instruments aboard the NASA Terra and Aqua satellites provide global flood extent coverage at a spatial resolution of 250m. Cloud cover hampers flood extent detection; therefore we ingest 6 images (the Terra and Aqua images of each day, for three days), in combination with a cloud shadow filter, to provide daily global flood extent updates. The Flood Observatory has always made it a high priority to visualize and share its data and products through its website. Recent collaborative efforts with e.g. GeoSUR have enhanced accessibility of DFO data. A web map service has been implemented to automatically disseminate geo-referenced flood extent products into client-side GIS software. For example, for Latin America and the Caribbean region, the GeoSUR portal now displays current flood extent maps, which can be integrated and visualized with other relevant geographical data. Furthermore, the flood state of satellite-observed river discharge sites are displayed through the portal as well. Additional efforts include implementing Open Geospatial Consortium (OGC) standards to incorporate Water Markup Language (WaterML) data exchange mechanisms to further facilitate the distribution of the satellite

  4. Automatic Registration Method for Fusion of ZY-1-02C Satellite Images

    Directory of Open Access Journals (Sweden)

    Qi Chen

    2013-12-01

    Full Text Available Automatic image registration (AIR has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size and unstable positioning accuracy resulting from the limited manufacturing technology of charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter lead to difficulty in obtaining agreeable corresponding points for registration using only area-based matching or feature-based matching. In this situation, a coarse-to-fine matching strategy integrating two types of algorithms is proven feasible and effective. In this paper, an AIR method for application to the fusion of ZY-1-02C satellite imagery is proposed. First, the images are geometrically corrected. Coarse matching, based on scale invariant feature transform, is performed for the subsampled corrected images, and a rough global estimation is made with the matching results. Harris feature points are then extracted, and the coordinates of the corresponding points are calculated according to the global estimation results. Precise matching is conducted, based on normalized cross correlation and least squares matching. As complex image distortion cannot be precisely estimated, a local estimation using the structure of triangulated irregular network is applied to eliminate the false matches. Finally, image resampling is conducted, based on local affine transformation, to achieve high-precision registration. Experiments with ZY-1-02C datasets demonstrate that the accuracy of the proposed method meets the requirements of fusion application, and its efficiency is also suitable for the commercial operation of the automatic satellite data process system.

  5. TecLines: A MATLAB-Based Toolbox for Tectonic Lineament Analysis from Satellite Images and DEMs, Part 2: Line Segments Linking and Merging

    Directory of Open Access Journals (Sweden)

    Mehdi Rahnama

    2014-11-01

    Full Text Available Extraction and interpretation of tectonic lineaments is one of the routines for mapping large areas using remote sensing data. However, this is a subjective and time-consuming process. It is difficult to choose an optimal lineament extraction method in order to reduce subjectivity and obtain vectors similar to what an analyst would manually extract. The objective of this study is the implementation, evaluation and comparison of Hough transform, segment merging and polynomial fitting methods towards automated tectonic lineament mapping. For this purpose we developed a new MATLAB-based toolbox (TecLines. The proposed toolbox capabilities were validated using a synthetic Digital Elevation Model (DEM and tested along in the Andarab fault zone (Afghanistan where specific fault structures are known. In this study, we used filters in both frequency and spatial domains and the tensor voting framework to produce binary edge maps. We used the Hough transform to extract linear image discontinuities. We used B-spline as a polynomial curve fitting method to eliminate artificial line segments that are out of interest and to link discontinuous segments with similar trends. We performed statistical analyses in order to compare the final image discontinuities maps with existing references map.

  6. New and Emerging Satellite Imaging Capabilities in Support of Safeguards

    International Nuclear Information System (INIS)

    This abstract is focused on new and emerging commercial satellite imagery (CSI) capabilities. For more than a decade, experienced imagery analysts have been exploiting and analyzing CSI in support of the Department of Safeguards. As the remote sensing industry continues to evolve, additional CSI imagery types are becoming available that could enhance our ability to evaluate and verify States' declarations and to investigate the possible presence of undeclared activities. A newly available and promising CSI capability that may have a Safeguards application is Full Motion Video (FMV) imagery collection from satellites. For quite some time, FMV imagery has been collected from airborne platforms, but now FMV sensors are being deployed into space. Like its airborne counterpart, satellite FMV imagery could provide analysts with a great deal of information, including insight into the operational status of facilities and patterns of activity. From a Safeguards perspective, FMV imagery could help the Agency in the evaluation and verification of States' declared facilities and activities. There are advantages of FMV imaging capabilities that cannot be duplicated with other CSI capabilities, including the ability to loiter over areas of interest and the potential to revisit sites multiple times per day. Additional sensor capabilities applicable to the Safeguards mission include, but are not limited to, the following sensors: · Thermal Infrared imaging sensors will be launched in late 2014 to monitor operational status, e.g., heat from a transformer. · High resolution ShortWave Infrared sensors able to characterize materials that could support verification of Additional Protocol declarations under Article 2.a(v). · Unmanned Aerial Vehicles with individual sensors or specific sensor combinations. The Safeguards Symposium provides a forum to showcase and demonstrate safeguards applications for these emerging satellite imaging capabilities. (author)

  7. 基于6S模型的GF-1卫星影像大气校正及效果%GF-1 satellite image atmospheric correction based on 6S model and its effect

    Institute of Scientific and Technical Information of China (English)

    刘佳; 王利民; 杨玲波; 滕飞; 邵杰; 杨福刚; 富长虹

    2015-01-01

    GF-1 satellite is the first satellite of the high resolution satellite series in China. Since its successful launch on April 26 2013, GF-1 satellite has been widely applied in agricultural remote sensing monitoring practice in China, and it has become a major data source of agricultural remote sensing dynamic monitoring. Based on the principle of radioactive transfer model of 6S (second simulation of a satellite signal in the solar spectrum), this paper designed and realized the algorithm and program suitable for GF-1 satellite data atmospheric correction. By using the 6S model, the algorithm obtains the parameters for the conversion from reflectivity (or irradiance) of Top Of Atmosphere (TOA) to surface reflectance, and then calculates the surface reflectance of each pixel of each image according to the conversion parameter. The algorithm takes GF-1 satellite first level data, metadata, and open parameter of sensor as the input data, without auxiliary data from other sources. The specific process includes 3 steps, i.e. radiometric calibration, running parameters settings and atmospheric correction. Radiometric calibration is to convert the DN (digital number) value of the original GF-1 satellite first level image into radiation brightness, and then calculate apparent reflectance by combining the reflectivity (or irradiance) of TOA. Either reflectivity (or irradiance) of TOA or apparent reflectance can be taken as the input of atmospheric correction program. Precondition for realizing the algorithm is to calculate the average solar irradiance parameters of each wave band of satellite sensor atmospheric top according to spectral response function of GF-1 satellite sensor and WRC (world radiation center) sun spectrum function. Operation parameters include 2 types: 1) input of satellite images, including satellite zenith angle, satellite azimuth angle, solar zenith angle, solar azimuth, sensor height, ground elevation, radiation calibration coefficient and spectral

  8. Using satellite image-based maps to improve sugarcane straw burning emission estimates in the state of São Paulo, Brazil

    Science.gov (United States)

    França, D.; Longo, K.; Rudorff, B.; Aguiar, D.; Freitas, S. R.; Stockler, R.; Pereira, G.

    2014-12-01

    Since the last decade, the global demand for biofuel production has been increasing every year due to the growing need for energy supply security and mitigation of greenhouse gases (GHG). Currently, sugarcane ethanol is one of the most widely used biofuels and Brazil is already the world's largest sugarcane producer, devoting almost 50% of it to ethanol production. The state of São Paulo is the major sugarcane producer in this country, with a cultivated area of about 5.4 Mha in 2011. Approximately 2 million hectares were harvested annually from 2006 to 2011 with the pre-harvest straw burning practice, which emits trace gases and particulate material to the atmosphere. The assessment and monitoring of sugarcane burning impacts are fundamental in order to mitigate the negative impacts of pre-harvest burning and consolidate the environmental benefits of sugarcane ethanol. Although some official inventories created by the Brazilian government have indicated the prevalence of emissions from sugarcane straw burning in total agricultural residue emissions, specific information about emissions of gases and aerosols during pre-harvest burning of sugarcane is still scarce in Brazil. This study aimed to contribute to the improvement of estimates of emissions from sugarcane burning through the use of specific parameters for sugarcane straw burning and a method which has avoided underestimations resulting from the unique characteristics of this type of biomass fire. In this investigation, emissions of several air pollutants released by sugarcane burning during the harvest season were estimated through the integrated use of remote sensing based maps of sugarcane burned area and a numerical tool for the state of São Paulo from 2006 to 2011. Average estimated emissions (Gg/year) were 1,130 ± 152 for CO, 26 ± 4 for NOX, 16 ± 2 for CH4, 45 ± 6 for PM2.5, 120 ± 16 for PM10 and 154 ± 21 for NMHC (non-methane hydrocarbons). An intercomparison among annual emissions from this

  9. 一种基于PCA-LDA的卫星遥感图像的分类方法%A CLASSIFICATION APPROACH FOR SATELLITE REMOTE SENSING IMAGE BASED ON PCA-LDA

    Institute of Scientific and Technical Information of China (English)

    赵蔷; 宋笑雪; 郭新明; 李红

    2013-01-01

    We propose a colour classification algorithm for satellite remote sensing images based on PCA-LDA, which integrates the features of components analysis (PCA) and linear discriminant analysis (LDA). The algorithm fuses the feature spaces of PCA and LDA algorithms to get the colour-fused feature space. The algorithm removes the correlation between R, G and B of the image, improves the light sensitivity and classifies the colours of the image using region classification-based spatial consistency principle. Experimental results demonstrate that the PCA-LDA-based algorithm is an effective method to classify the remote multi-frequency sensing image.%结合主成分分析PCA(Principal Components Analysis)和线性判别分析LDA(Linear Discriminant Analysis)的特点,提出一种基于PCA-LDA算法的卫星遥感图像色彩分类方法.该算法将PCA算法和LDA算法的特征空间相融合,得到融合颜色特征空间.该方法去除了图像的R、G、B之间的相关性,改善了光照敏感性,采用基于区域分类的空间一致性原则对图像进行颜色分类.实验结果表明,该方法是对多频谱遥感图像分类的一种有效的方法.

  10. Color Satellite Image Encryption Algorithm Based on Improved Generalized Cat Mapping%基于改进广义cat映射的彩色卫星图像加密算法

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    In order to improve encryption effect of color satellite image,in this paper,a color satellite image encryption algorithm based on improved generalized cat map is proposed; the idea of constructing the generalized cat mapping is used in this algorithm. The transformation of the corresponding first transform expression of discrete generalized cat mapping of the nonlinear transform into second, three color components of color images were three scrambled by using the improved generalized cat mapping; then the diffusion for scrambled image is carried out by using compound chaos mapping. Theoretical analysis and simulation results show that the algorithm can improve encryption effect of the image;it has a large space with a secret key,anti-statistical attack,good performance and strong sensitivity of the secret key and can achieve the appropriate level of safety.%为了提高彩色卫星图像的加密效果,提出了一种基于改进广义cat映射的彩色卫星图像加密算法。该算法利用广义cat映射的构造思想,将离散广义cat映射的第一个变换表达式所对应的变换结果非线性的融入第二个变换表达式,利用改进广义cat映射对彩色卫星图像的三个色彩分量分别进行三轮置乱,然后利用复合混沌映射对置乱后的图像进行扩散。经过理论分析和仿真实验检测,该算法可以更好的改善图像的加密效果,具有密钥空间大、抗统计攻击能力强、密钥敏感性强等良好的性能,能够达到相应的安全水平。

  11. Simultaneous hierarchical segmentation and vectorization of satellite images through combined data sampling and anisotropic triangulation

    Energy Technology Data Exchange (ETDEWEB)

    Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL

    2010-10-21

    The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.

  12. An efficient watermarking technique for satellite images using discrete cosine transform

    Science.gov (United States)

    AL-Mansoori, Saeed

    2012-10-01

    Due to the significant progress in science and technology, the digital world became an interesting topic for many studies. "Data Security" is one of the main concepts related to the digital world especially in the field of remote sensing. Therefore, to deal with this matter the "Watermarking" concept was introduced. The idea of digital image watermarking is to embed the information within a signal (i.e. image, video, etc.), which cannot be easily extracted by a third party. This will generate a copyright protection and authentication for the owner(s). Emirates Institution for Advanced Science and Technology (EIAST) as an owner provides satellite images captured by DubaiSat-1 satellite to customers. The aim of this study is to implement a robust algorithm to hide EIAST logo within any delivered image in order to increase the data security and protect the ownership of DubaiSat-1 images. In addition, it is necessary to provide a high quality images to the end-user; nevertheless, adding any information (logo) to these images will affect its quality. Therefore, the model will be designed to keep the observable difference between the watermarked and original image at minimum. Moreover, the watermark should be difficult to remove or alter without the degradation of the host image. This study will be based on Discrete Cosine Transform (DCT) to provide an excellent and highly robust protection in cases such as noise addition, cropping, rotation and JPEG compression attacks.

  13. Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

    Science.gov (United States)

    Champion, Nicolas

    2016-06-01

    Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

  14. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai;

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  15. Path planning on satellite images for unmanned surface vehicles

    Directory of Open Access Journals (Sweden)

    Yang Joe-Ming

    2015-01-01

    Full Text Available In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle A* algorithm (FAA*, an advanced A* algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV.

  16. A new lossless compression algorithm for satellite earth science multi-spectral imagers

    Science.gov (United States)

    Gladkova, Irina; Gottipati, Srikanth; Grossberg, Michael

    2007-09-01

    Multispectral imaging is becoming an increasingly important tool for monitoring the earth and its environment from space borne and airborne platforms. Multispectral imaging data consists of visible and IR measurements from a scene across space and spectrum. Growing data rates resulting from faster scanning and finer spatial and spectral resolution makes compression an increasingly critical tool to reduce data volume for transmission and archiving. Examples of multispectral sensors we consider include the NASA 36 band MODIS imager, Meteosat 2nd generation 12 band SEVIRI imager, GOES R series 16 band ABI imager, current generation GOES 5 band imager, and Japan's 5 band MTSAT imager. Conventional lossless compression algorithms are not able to reach satisfactory compression ratios nor are they near the upper limits for lossless compression on imager data as estimated from the Shannon entropy. We introduce a new lossless compression algorithm developed for the NOAA-NESDIS satellite based Earth science multispectral imagers. The algorithm is based on capturing spectral correlations using spectral prediction, and spatial correlations with a linear transform encoder. Our results are evaluated by comparison with current sattelite compression algorithms such the new CCSDS standard compression algorithm, and JPEG2000. The algorithm as presented has been designed to work with NOAA's scientific data and so is purely lossless but lossy modes can be supported. The compression algorithm also structures the data in a way that makes it easy to incorporate robust error correction using FEC coding methods as TPC and LDPC for satellite use. This research was funded by NOAA-NESDIS for its Earth observing satellite program and NOAA goals.

  17. RapidEye satellite based geo-information system

    Science.gov (United States)

    Krischke, M.; Niemeyer, W.; Scherer, S.

    2000-03-01

    It has been found that the ability to offer a guaranteed delivery of information products is the key for any successful commercial Earth observation service. This understanding led to the definition of the RapidEye system and the foundation of the RapidEye AG. RapidEye is a satellite based remote sensing system which permits to have from any point on Earth, at least daily a multispectral (and optionally stereo) imaging capability with a resolution of 5-7 m. It is aimed at establishing an efficient operation for the rapid and accurate reception and processing of thematic information of the Earth's surface and to establish a reliable and sustained service for customers. RapidEye is set up in several steps. The individual steps can be realised according to the system's acceptance on the market. Four satellites are planned already for the first step which permits a revisiting rate of 1/day. In its final configuration, RapidEye consists of a chain of Earth observation satellites which optionally communicate with one another via communication links.

  18. Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID)

    Data.gov (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

  19. Global Solar Radiation in Spain from Satellite Images

    International Nuclear Information System (INIS)

    In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been reevaluated to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar, impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyrano metric measures in a concrete locality, but it provides a very valid indicator in places in which it is not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs

  20. Dictionary Based Image Segmentation

    DEFF Research Database (Denmark)

    Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

    2015-01-01

    We propose a method for weakly supervised segmentation of natural images, which may contain both textured or non-textured regions. Our texture representation is based on a dictionary of image patches. To divide an image into separated regions with similar texture we use an implicit level sets...

  1. Parallel algorithms of relative radiometric correction for images of TH-1 satellite

    Science.gov (United States)

    Wang, Xiang; Zhang, Tingtao; Cheng, Jiasheng; Yang, Tao

    2014-05-01

    The first generation of transitive stereo-metric satellites in China, TH-1 Satellite, is able to gain stereo images of three-line-array with resolution of 5 meters, multispectral images of 10 meters, and panchromatic high resolution images of 2 meters. The procedure between level 0 and level 1A of high resolution images is so called relative radiometric correction (RRC for short). The processing algorithm of high resolution images, with large volumes of data, is complicated and time consuming. In order to bring up the processing speed, people in industry commonly apply parallel processing techniques based on CPU or GPU. This article firstly introduces the whole process and each step of the algorithm - that is in application - of RRC for high resolution images in level 0; secondly, the theory and characteristics of MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) parallel programming techniques is briefly described, as well as the superiority for parallel technique in image processing field; thirdly, aiming at each step of the algorithm in application and based on MPI+OpenMP hybrid paradigm, the parallelizability and the strategies of parallelism for three processing steps: Radiometric Correction, Splicing Pieces of TDICCD (Time Delay Integration Charge-Coupled Device) and Gray Level Adjustment among pieces of TDICCD are deeply discussed, and furthermore, deducts the theoretical acceleration rates of each step and the one of whole procedure, according to the processing styles and independence of calculation; for the step Splicing Pieces of TDICCD, two different strategies of parallelism are proposed, which are to be chosen with consideration of hardware capabilities; finally, series of experiments are carried out to verify the parallel algorithms by applying 2-meter panchromatic high resolution images of TH-1 Satellite, and the experimental results are analyzed. Strictly on the basis of former parallel algorithms, the programs in the experiments

  2. Instrument calibration architecture of Radar Imaging Satellite (RISAT-1)

    Science.gov (United States)

    Misra, T.; Bhan, R.; Putrevu, D.; Mehrotra, P.; Nandy, P. S.; Shukla, S. D.; Rao, C. V. N.; Dave, D. B.; Desai, N. M.

    2016-05-01

    Radar Imaging Satellite (RISAT-1) payload system is configured to perform self-calibration of transmit and receive paths before and after imaging sessions through a special instrument calibration technique. Instrument calibration architecture of RISAT-1 supported ground verification and validation of payload including active array antenna. During on-ground validation of 126 beams of active array antenna which needed precise calibration of boresight pointing, a unique method called "collimation coefficient error estimation" was utilized. This method of antenna calibration was supported by special hardware and software calibration architecture of RISAT-1. This paper concentrates on RISAT-1 hardware and software architecture which supports in-orbit and on-ground instrument calibration. Efforts are also put here to highlight use of special calibration scheme of RISAT-1 instrument to evaluate system response during ground verification and validation.

  3. Satellite based Global Flood Detection System - strengths and limitations

    Science.gov (United States)

    Revilla-Romero, Beatriz; Salamon, Peter; Thielen, Jutta; De Groeve, Tom; Zajac, Zuzanna

    2014-05-01

    One of the main problems for global hydrological models is that for many regions only very limited or no observational data for a model assessment is available. This problem could be overcome with filling the gaps using information derived from satellite observations. Thus, an evaluation of the remote sensing signal of the Global Flood Detection System (GFDS) against observed discharge data was performed in order to test the use of this data in sparsely gauged river basins. The study was carried out at 398 locations near the main rivers and in Africa, Asia, Europe, North America and South America. After evaluating different methodologies for extracting the satellite signal, a temporal (4 days) and spatial (4 GFDS pixels) average was chosen to proceed with the analysis. For the 340 stations with a concurrent time series longer than seven years for both, the signal and the in situ observed discharge (obtained mainly from the Global Runoff Data Centre), a calibration based on monthly linear models was carried out. The validation was executed and several skill scores were calculated such as the R2, Nash-Sutcliffe (NSE), and Root Mean Square Error (RMSE). It is important to highlight that, for this study, 230 stations globally had Nash-Sutcliffe efficient score higher than zero, indicating that for specific conditions the satellite signal as used in GFDS can fill the gaps where observations are not available. For example, several locations in African catchments have good performance as in the Niger, Volta and Zambezi for which Nash-Sutcliffe is greater than 0.75. It is known that a number of factors affect total upwelling microwave brightness from a mixed water and land surface measured by a single image pixel. Aiming to better understand how some features of the sites could affect the satellite signal and the correlation with in situ observations, apart from the dependency on the river geometry, a multivariate analysis was carried out between the skill scores (NSE and

  4. Foodstuff Survey Around a Major Nuclear Facility with Test of Satellite Image Application

    International Nuclear Information System (INIS)

    'A foodstuff survey was performed around the Savannah River Site, Aiken SC. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of SRS center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined in two ways: by the usual process of assuming uniform crop distribution in each county on the basis of agricultural statistics reported by state agencies, and by analysis of two LANDSAT TM images obtained in May and September. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the Site and by 16-km distance intervals from 16 km to 80 km. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption. For four food crops, the amounts per section based on county agricultural statistics prorated by area were compared with the amounts per section based on satellite image analysis. The median ratios of the former to the latter were 0.6 - 0.7, suggesting that the two approaches are comparable but that satellite image analysis gave consistently higher amounts. Use of satellite image analysis is recommended on the basis of these findings to obtain site-specific, as compared to area-averaged, information on crop locations in conjunction with radionuclide pathway modelling. Some improvements in technique are suggested for satellite image application to characterize additional crops.'

  5. Satellite image time series simulation for environmental monitoring

    Science.gov (United States)

    Guo, Tao

    2014-11-01

    The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of

  6. Observer-based Satellite Attitude Control and Simulation Researches

    Institute of Scientific and Technical Information of China (English)

    王子才; 马克茂

    2002-01-01

    Observer design method is applied to the realization of satellite attitude control law baaed on simplified control model. Exact mathematical model of the satellite attitude control system is also constructed, together with the observer-based control law, to conduct simulation research. The simulation results justify the effectiveness andfeasibility of the observer-based control method.

  7. Development of dual imaging optical sensor (DIOS) for small satellites

    Science.gov (United States)

    Choi, Young-Wan; Kang, Myung-Seok; Jeong, Sung-Keun; Yun, Ji-Ho; Yang, Seung-Uk; Kim, Jongun; Kim, Ee-Eul

    2007-09-01

    The mission of DIOS program is to provide the function of large-swathwidth or in-track stereo imaging with compact electro-optical cameras. Optimized from its predecessor SAC (Small-sized Aperture Camera), DIOS consists of two cameras, each with an aperture of 120 mm diameter, 10 m GSD, and 50 km swath width in the spectral range of 520 ~ 890 nm. DIOS is developed to produce high quality images: MTF of more than 12 %; SNR of more than 100. DIOS can be configured to have cameras side-by-side, providing a swathwidth up to 100 km for a mission of large swathwidth. DIOS will be configured with installation of slanted two cameras for the mission of in-track stereo imaging to produce digital elevation model. In this paper, Dual Imaging Optical Sensor (DIOS) will be introduced with design approach and performance measure. Even though developed for micro satellites, the presentation of development status and test results will demonstrate the potential capability that DISO can provide for world-wide remote sensing groups: short development period, cost-effectiveness, wide application ranges, and high performance.

  8. Detecting weather radar clutter using satellite-based nowcasting products

    DEFF Research Database (Denmark)

    Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren;

    2006-01-01

    This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results...... for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...

  9. Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

    Science.gov (United States)

    Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

    2015-12-01

    Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

  10. Automatic Mrf-Based Registration of High Resolution Satellite Video Data

    Science.gov (United States)

    Platias, C.; Vakalopoulou, M.; Karantzalos, K.

    2016-06-01

    In this paper we propose a deformable registration framework for high resolution satellite video data able to automatically and accurately co-register satellite video frames and/or register them to a reference map/image. The proposed approach performs non-rigid registration, formulates a Markov Random Fields (MRF) model, while efficient linear programming is employed for reaching the lowest potential of the cost function. The developed approach has been applied and validated on satellite video sequences from Skybox Imaging and compared with a rigid, descriptor-based registration method. Regarding the computational performance, both the MRF-based and the descriptor-based methods were quite efficient, with the first one converging in some minutes and the second in some seconds. Regarding the registration accuracy the proposed MRF-based method significantly outperformed the descriptor-based one in all the performing experiments.

  11. Satellite-to-satellite Lidar Imaging Using Reflective Tomography%星对星激光雷达反射层析成像技术探讨

    Institute of Scientific and Technical Information of China (English)

    瞿福琪; 胡以华; 焦均均; 董彬

    2013-01-01

    以星对星激光雷达成像为应用背景,提出了一种基于啁啾脉冲信号的反射层析成像处理方法,该方法通过激光雷达多角度回波非相干累积实现高分辨率的图像重构;分析了星对星反射层析成像的实现条件,包括成像分辨率、工作模式及成像时间.研究结果表明,采用本文所提出的成像方法,通过同轨道面的伴星探测方式可以满足激光雷达反射层析成像多角度探测的要求,在观测角度范围大于60°时能够得到0.1m目标分辨率,角度范围越大,分辨率越高,且成像时间与卫星轨道半径和两星距离有关.实验验证了该方法的有效性和星对星反射层析成像的可行性.%Taking satellite-to-satellite lidar imaging as application background, an imaging processing method based on chirped pulse for reflective tomography lidar is presented. In this method, high precision image reconstruction is obtained by extracting projection data of different observation angle and using CBP algorithm. The condition of satellite-to-satellite lidar reflective tomography imaging is analyzed, including imaging resolution, working modes and imaging time. The results show that, the mode of accompanying satellite detecting in the same orbit plan meet the requirement of multiple angle detecting for lidar reflective tomography imaging. 0. 1 meter spacial resolution can be achieved while the range of detecting angle is larger than 60 degree, and the larger the range of angle, the higher the resolution is. The imaging time depends on the satellite orbit radius and the range between two satellites. Imaging experiment validates the feasibility and effectiveness of the presented method.

  12. Satellite-based monitoring of cotton evapotranspiration

    Science.gov (United States)

    Dalezios, Nicolas; Dercas, Nicholas; Tarquis, Ana Maria

    2016-04-01

    Water for agricultural use represents the largest share among all water uses. Vulnerability in agriculture is influenced, among others, by extended periods of water shortage in regions exposed to droughts. Advanced technological approaches and methodologies, including remote sensing, are increasingly incorporated for the assessment of irrigation water requirements. In this paper, remote sensing techniques are integrated for the estimation and monitoring of crop evapotranspiration ETc. The study area is Thessaly central Greece, which is a drought-prone agricultural region. Cotton fields in a small agricultural sub-catchment in Thessaly are used as an experimental site. Daily meteorological data and weekly field data are recorded throughout seven (2004-2010) growing seasons for the computation of reference evapotranspiration ETo, crop coefficient Kc and cotton crop ETc based on conventional data. Satellite data (Landsat TM) for the corresponding period are processed to estimate cotton crop coefficient Kc and cotton crop ETc and delineate its spatiotemporal variability. The methodology is applied for monitoring Kc and ETc during the growing season in the selected sub-catchment. Several error statistics are used showing very good agreement with ground-truth observations.

  13. Nightfire method to track volcanic eruptions from multispectral satellite images

    Science.gov (United States)

    Trifonov, Grigory; Zhizhin, Mikhail; Melnikov, Dmitry

    2016-04-01

    This work presents the first results of an application of the Nightfire hotspot algorithm towards volcano activity detection. Nightfire algorithm have been developed to play along with a Suomi-NPP polar satellite launched in 2011, which has a new generation multispectral VIIRS thermal sensor on board, to detect gas flares related to the upstream and downstream production of oil and natural gas. Simultaneously using of nighttime data in SWIR, MWIR, and LWIR sensor bands the algorithm is able to estimate the hotspot temperature, size and radiant heat. Four years of non-filtered observations have been accumulated in a spatio-temporal detection database, which currently totals 125 GB in size. The first part of this work presents results of retrospective cross-match of the detection database with the publicly available observed eruptions databases. The second part discusses how an approximate 3D shape of a lava lake could be modeled based on the apparent source size and satellite zenith angle. The third part presents the results of fusion Landsat-8 and Himawari-8 satellites data with the VIIRS Nightfire for several active volcanoes.

  14. Terrestrial Myriametric Radio Burst Observed by IMAGE and Geotail Satellites

    Science.gov (United States)

    Fung, Shing F.; Hashimoto, KoZo; Kojima, Hirotsugu; Boardson, Scott A.; Garcia, Leonard N.; Matsumoto, Hiroshi; Green, James L.; Reinisch, Bodo W.

    2013-01-01

    We report the simultaneous detection of a terrestrial myriametric radio burst (TMRB) by IMAGE and Geotail on 19 August 2001. The TMRB was confined in time (0830-1006 UT) and frequency (12-50kHz). Comparisons with all known nonthermal myriametric radiation components reveal that the TMRB might be a distinct radiation with a source that is unrelated to the previously known radiation. Considerations of beaming from spin-modulation analysis and observing satellite and source locations suggest that the TMRB may have a fan beamlike radiation pattern emitted by a discrete, dayside source located along the poleward edge of magnetospheric cusp field lines. TMRB responsiveness to IMF Bz and By orientations suggests that a possible source of the TMRB could be due to dayside magnetic reconnection instigated by northward interplanetary field condition.

  15. Galileo's first images of Jupiter and the Galilean satellites

    Science.gov (United States)

    Belton, M.J.S.; Head, J. W., III; Ingersoll, A.P.; Greeley, R.; McEwen, A.S.; Klaasen, K.P.; Senske, D.; Pappalardo, R.; Collins, G.; Vasavada, A.R.; Sullivan, R.; Simonelli, D.; Geissler, P.; Carr, M.H.; Davies, M.E.; Veverka, J.; Gierasch, P.J.; Banfield, D.; Bell, M.; Chapman, C.R.; Anger, C.; Greenberg, R.; Neukum, G.; Pilcher, C.B.; Beebe, R.F.; Burns, J.A.; Fanale, F.; Ip, W.; Johnson, T.V.; Morrison, D.; Moore, J.; Orton, G.S.; Thomas, P.; West, R.A.

    1996-01-01

    The first images of Jupiter, Io, Europa, and Ganymede from the Galileo spacecraft reveal new information about Jupiter's Great Red Spot (GRS) and the surfaces of the Galilean satellites. Features similar to clusters of thunderstorms were found in the GRS. Nearby wave structures suggest that the GRS may be a shallow atmospheric feature. Changes in surface color and plume distribution indicate differences in resurfacing processes near hot spots on lo. Patchy emissions were seen while Io was in eclipse by Jupiter. The outer margins of prominent linear markings (triple bands) on Europa are diffuse, suggesting that material has been vented from fractures. Numerous small circular craters indicate localized areas of relatively old surface. Pervasive brittle deformation of an ice layer appears to have formed grooves on Ganymede. Dark terrain unexpectedly shows distinctive albedo variations to the limit of resolution.

  16. A Cooperation-Based Fault Management Method for Satellite Networks

    Directory of Open Access Journals (Sweden)

    Wenbo Zhang

    2012-07-01

    Full Text Available In order to efficiently diagnose the satellite network, a three level management architecture was proposed and a cooperated-based fault management method was put forward. In this method the traditional fault management method was used through network management technique when a satellite agent could respond to the network management instruction received from the management station. However, if the satellite agent could not respond to the network management demands, the intra-domain cooperation or inter-domain cooperation would be activated. The suspected fault satellite could be tested through cooperation among the satellite agents. The simulation results shows that in the circumstance of the low faulty frequency, the new method could be effectively used in satellite network with short cooperative time and low throughput.

  17. Correction of ZY-3 image distortion caused by satellite jitter via virtual steady reimaging using attitude data

    Science.gov (United States)

    Wang, Mi; Zhu, Ying; Jin, Shuying; Pan, Jun; Zhu, Quansheng

    2016-09-01

    ZiYuan-3 (ZY-3), the first Chinese civilian stereo mapping satellite, suffers from 0.67 Hz satellite jitter that deteriorates its geometric performance in mapping, resource monitoring and other applications. This paper proposes a distortion correction method based on virtual steady reimaging (VSRI) using attitude data to eliminate the negative influence caused by satellite jitter in satellite data preprocessing. VSRI helps linear array pushbroom cameras rescan the ground with a uniform integral time and smooth attitude. In this method, a VSRI model is proposed, and the geometric relationship between the original and corrected image is determined in terms of geolocation consistency based on a rigorous geometric model. Thus, the corrected image is obtained by resampling from the original one. Three areas of ZY-3 three-line images suffering from satellite jitter were used to validate the accuracy and efficiency of the proposed method. First, different attitude interpolation methods were compared. It is found that the Lagrange polynomial model and the cubic piecewise polynomial model have higher interpolation accuracy for original imagery. Then, the replacement accuracy of the rational function model (RFM) for ZY-3 was analyzed with 0.67 Hz satellite jitter. The results indicate that attitude oscillation reduces the fitting precision of the RFM for the rigorous imaging model. Finally, the relative orientation accuracy of the three-line images and the geo-positioning accuracy with ground control points (GCPs) before and after distortion correction were compared. The results show that the distortion caused by satellite jitter is corrected efficiently, and the accuracy of the three experimental datasets is improved in both the image space and the ground space.

  18. A Bayesian approach for solar resource potential assessment using satellite images

    International Nuclear Information System (INIS)

    The need for a more sustainable and more protective development opens new possibilities for renewable energy. Among the different renewable energy sources, the direct conversion of sunlight into electricity by solar photovoltaic (PV) technology seems to be the most promising and represents a technically viable solution to energy demands. But implantation and deployment of PV energy need solar resource data for utility planning, accommodating grid capacity, and formulating future adaptive policies. Currently, the best approach to determine the solar resource at a given site is based on the use of satellite images. However, the computation of solar resource (non-linear process) from satellite images is unfortunately not straightforward. From a signal processing point of view, it falls within non-stationary, non-linear/non-Gaussian dynamical inverse problems. In this paper, we propose a Bayesian approach combining satellite images and in situ data. We propose original observation and transition functions taking advantages of the characteristics of both the involved type of data. A simulation study of solar irradiance is carried along with this method and a French Guiana solar resource potential map for year 2010 is given

  19. Investigations on satellite image and reference data for exploration-related tasks

    International Nuclear Information System (INIS)

    This report describes the results of advanced data processing and image interpretation. The development of an exploration-related image processing methodology led to a quick and complete mapping of the regional structure pattern as well as lithological units in humid climates on the base of highly processed satellite imagery. Today, for the evaluation of the potential of mapped lineaments exploration-derived reference data are still prerequisites. Those digitized data included in the image processing procedure support the interpretation of structures. The report further compares remote sensing methodology applied to exploration with common exploration methods under technical/economical aspects. By that, Landsat TM (and modern airborne scanner data) is an important and cost-effective tool for mineral exploration. The developed image processing methodology is already operational today and can be transferred to other climates as well as to other fields of application. (orig.) With 17 figs., 6 tabs., 18 refs

  20. An artificial neural network ensemble model for estimating global solar radiation from Meteosat satellite images

    International Nuclear Information System (INIS)

    An optimized artificial neural network ensemble model is built to estimate daily global solar radiation over large areas. The model uses clear-sky estimates and satellite images as input variables. Unlike most studies using satellite imagery based on visible channels, our model also exploits all information within infrared channels of the Meteosat 9 satellite. A genetic algorithm is used to optimize selection of model inputs, for which twelve are selected – eleven 3-km Meteosat 9 channels and one clear-sky term. The model is validated in Andalusia (Spain) from January 2008 through December 2008. Measured data from 83 stations across the region are used, 65 for training and 18 independent ones for testing the model. At the latter stations, the ensemble model yields an overall root mean square error of 6.74% and correlation coefficient of 99%; the generated estimates are relatively accurate and errors spatially uniform. The model yields reliable results even on cloudy days, improving on current models based on satellite imagery. - Highlights: • Daily solar radiation data are generated using an artificial neural network ensemble. • Eleven Meteosat channels observations and a clear sky term are used as model inputs. • Model exploits all information within infrared Meteosat channels. • Measured data for a year from 83 ground stations are used. • The proposed approach has better performance than existing models on daily basis

  1. Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

    Energy Technology Data Exchange (ETDEWEB)

    Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)

    2008-07-01

    The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots.

  2. A Framework for Satellite Image Enhancement Using Quantum Genetic and Weighted IHS+Wavelet Fusion Method

    Directory of Open Access Journals (Sweden)

    Amal A. HAMED

    2016-04-01

    Full Text Available this paper examined the applicability of quantum genetic algorithms to solve optimization problems posed by satellite image enhancement techniques, particularly super-resolution, and fusion. We introduce a framework starting from reconstructing the higher-resolution panchromatic image by using the subpixel-shifts between a set of lower-resolution images (registration, then interpolation, restoration, till using the higher-resolution image in pan-sharpening a multispectral image by weighted IHS+Wavelet fusion technique. For successful super-resolution, accurate image registration should be achieved by optimal estimation of subpixel-shifts. Optimal-parameters blind restoration and interpolation should be performed for the optimal quality higher-resolution image. There is a trade-off between spatial and spectral enhancement in image fusion; it is difficult for the existing methods to do the best in both aspects. The objective here is to achieve all combined requirements with optimal fusion weights, and use the parameters constraints to direct the optimization process. QGA is used to estimate the optimal parameters needed for each mathematic model in this framework “Super-resolution and fusion.” The simulation results show that the QGA-based method can be used successfully to estimate automatically the approaching parameters which need the maximal accuracy, and achieve higher quality and efficient convergence rate more than the corresponding conventional GA-based and the classic computational methods.

  3. Global trends in satellite-based emergency mapping

    Science.gov (United States)

    Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

    2016-07-01

    Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

  4. Global trends in satellite-based emergency mapping.

    Science.gov (United States)

    Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

    2016-07-15

    Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective. PMID:27418503

  5. Digital, Satellite-Based Aeronautical Communication

    Science.gov (United States)

    Davarian, F.

    1989-01-01

    Satellite system relays communication between aircraft and stations on ground. System offers better coverage with direct communication between air and ground, costs less and makes possible new communication services. Carries both voice and data. Because many data exchanged between aircraft and ground contain safety-related information, probability of bit errors essential.

  6. A method for generating high resolution satellite image time series

    Science.gov (United States)

    Guo, Tao

    2014-10-01

    There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation

  7. Evaluation of SPIHT Compression Scheme for Satellite Imageries Based on Statistical Parameters

    Directory of Open Access Journals (Sweden)

    Nagamani .K

    2012-05-01

    Full Text Available Non reversible and lossy image compression techniques is known to be computationally more complex as they grow more efficient, confirming the constraints of source coding theorems in information theory that a code for a (stationary source approaches optimality the limit of infinite computation (source length. It has been observed that when a variety of images of different types are compressed using a fixed wavelet filter, the peak signal to noise ratios (PSNR vary widely from image to image. This variation in PSNR can be attributed to the nature and inherent statistical characteristics of image. To explore the effect of various image features on the coding performance, a set of gray level image statistics have been analyzed by using SPIHT (Set Partitioning In Hierarchical Trees algorithm. The Mean Square Error (MSE and Peak Signal to Noise Ratios (PSNR determined for an image depends on the statistical properties of the image and the compression scheme applied. The efficiency of the compression scheme can be evaluated by examining the statistical parameters of the image. In this paper various statistical parameters associated with the SPIHT compression scheme are derived for three different types of images namely standard Lena, satellite urban and rural imageries based on higher order statistics. The statistical parameters include higher order image statistics like Rate Distortion and Skewness and Kurtosis which describe the shape and symmetry of the image. The statistical parameters derived for a fixed rate and fixed level of decomposition for three types of images have been are used for the explanation of the Compression Ratio and Peak Signal to Noise Ratio (PSNR achieved for the satellite imageries. The results show that urban images are better suited for SPIHT compression scheme compared to that of satellite rural image. The results of the analysis are presented in the paper.

  8. Dictionary Based Image Segmentation

    OpenAIRE

    Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

    2015-01-01

    We propose a method for weakly supervised segmentationof natural images, which may contain both textured or non-texturedregions. Our texture representation is based on a dictionary of imagepatches. To divide an image into separated regions with similar texturewe use an implicit level sets representation of the curve, which makesour method topologically adaptive. In addition, we suggest a multi-labelversion of the method. Finally, we improve upon a similar texture representation,by formulating...

  9. Active-imaging-based underwater navigation

    Science.gov (United States)

    Monnin, David; Schmitt, Gwenaël.; Fischer, Colin; Laurenzis, Martin; Christnacher, Frank

    2015-10-01

    Global navigation satellite systems (GNSS) are widely used for the localization and the navigation of unmanned and remotely operated vehicles (ROV). In contrast to ground or aerial vehicles, GNSS cannot be employed for autonomous underwater vehicles (AUV) without the use of a communication link to the water surface, since satellite signals cannot be received underwater. However, underwater autonomous navigation is still possible using self-localization methods which determines the relative location of an AUV with respect to a reference location using inertial measurement units (IMU), depth sensors and even sometimes radar or sonar imaging. As an alternative or a complementary solution to common underwater reckoning techniques, we present the first results of a feasibility study of an active-imaging-based localization method which uses a range-gated active-imaging system and can yield radiometric and odometric information even in turbid water.

  10. Agricultural land-use mapping using very high resolution satellite images in Canary Islands

    Science.gov (United States)

    Labrador Garcia, Mauricio; Arbelo, Manuel; Evora Brondo, Juan Antonio; Hernandez-Leal, Pedro A.; Alonso-Benito, Alfonso

    Crop maps are a basic tool for rural planning and a way to asses the impact of politics and infrastructures in the rural environment. Thus, they must be accurate and updated. Because of the small size of the land fields in Canary Islands, until now the crop maps have been made by means of an intense and expensive field work. The tiny crop terraces do not allow the use of traditional medium-size resolution satellite images. The launch of several satellites with sub-meter spatial resolutions in the last years provides an opportunity to update land use maps in these fragmented areas. SATELMAC is a project financed by the PCT-MAC 2007-2013 (FEDER funds). One of the main objectives of this project is to develop a methodology that allows the use of very high resolution satellite images to automate as much as possible the updating of agricultural land use maps. The study was carried out in 3 different areas of the two main islands of the Canarian Archipelago, Tenerife and Gran Canaria. The total area is about 550 km2 , which includes both urban and rural areas. Multitemporal images from Geo-Eye 1 were acquired during a whole agricultural season to extract information about annual and perennial crops. The work includes a detailed geographic correction of the images and dealing with many adverse factors like cloud shadows, variability of atmospheric conditions and the heterogeneity of the land uses within the study area. Different classification methods, including traditional pixel-based methods and object-oriented approach, were compared in order to obtain the best accuracy. An intensive field work was carried out to obtain the ground truth, which is the base for the classification procedures and the validation of the results. The final results will be integrated into a cadastral vector layer.

  11. Children observe the Digital Earth from above: How they read aerial and satellite images

    International Nuclear Information System (INIS)

    Digital aerial and satellite images depicting the Earth surface are not secret anymore and they are easily available for general public. Publishing of aerial and satellite images provoke the questions how the non-experts or the amateur groups can interpret these images, how they are able to cope with vertical or oblique images, with their colour, missing lettering, etc. The paper presents the results of the research of the above mentioned questions where the respondents were the Czech pupils and student at the age of about eleven, fifteen and nineteen years. These results are aimed at the effective exploitation of aerial and satellite images in teaching, they represent also information for imagery producers and distributors. A non-traditional view on the Earth surface from above using aerial or satellite images is one of the opportunities to discover the beauty of the Earth

  12. An anti-image interference quadrature IF architecture for satellite receivers

    Institute of Scientific and Technical Information of China (English)

    He Weidong; Lu Xiaochun; He Chengyan; James Torley

    2014-01-01

    Since Global Navigation Satellite System (GNSS) signals span a wide range of frequency, wireless signals coming from other communication systems may be aliased and appear as image interference. In quadrature intermediate frequency (IF) receivers, image aliasing due to in-phase and quadrature (I/Q) channel mismatches is always a big problem. I/Q mismatches occur because of gain and phase imbalances between quadrature mixers and capacitor mismatches in ana-log-to-digital converters (ADC). As a result, the dynamic range and performance of a receiver are severely degraded. In this paper, several popular receiver architectures are summarized and the image aliasing problem is investigated in detail. Based on this analysis, a low-IF architecture is pro-posed for a single-chip solution and a novel and feasible anti-image algorithm is investigated. With this anti-image digital processing, the image reject ratio (IRR) can reach approximately above 50 dB, which relaxes image rejection specific in front-end circuit designs and allows cheap and highly flexible analog front-end solutions. Simulation and experimental data show that the anti-image algorithm can work effectively, robustly, and steadily.

  13. Utilizing Chinese high-resolution satellite images for inspection of unauthorized constructions in Beijing

    Institute of Scientific and Technical Information of China (English)

    LI DeRen; WANG Mi; HU Fen

    2009-01-01

    After Beijing wins the bit to host the 29th Olympic Games, in order to manifest the technical support advantages and capabilities of the autonomously-developed RS and GIS based change detection techniques in 2008 Beijing Olympic Games, and from the standpoints of executing new city planning, relieving the traffic congestion as well as maintaining the historic features, an automatic satellite monitoring system has been studied and established to accomplish the mission of unauthorized construction inspection within the Sixth Ring Road of Beijing city quarterly, by adopting the CBERS-2 satellite images and combining technologies of GIS, GPS, etc. This article discusses the applicable procedures and key issues when utilizing such Chinese satellite images and relevant techniques to discover the illegal constructions, and introduces the monitoring system from both the design and implementation aspects; additionally, some typical application cases in the practice of the system are also illustrated. The monitoring system can timely supply abundant information to facilitate the policy-making of relevant planning departments, thus providing consolidate technical support to eliminate the illegal constructing behaviors in the blossom. During the five years' excellent performance, it has helped China save large amounts of expenditures for processing of unauthorized constructed buildings.

  14. Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry

    Science.gov (United States)

    Gleason, Colin J.; Smith, Laurence C.

    2014-01-01

    Rivers provide critical water supply for many human societies and ecosystems, yet global knowledge of their flow rates is poor. We show that useful estimates of absolute river discharge (in cubic meters per second) may be derived solely from satellite images, with no ground-based or a priori information whatsoever. The approach works owing to discovery of a characteristic scaling law uniquely fundamental to natural rivers, here termed a river’s at-many-stations hydraulic geometry. A first demonstration using Landsat Thematic Mapper images over three rivers in the United States, Canada, and China yields absolute discharges agreeing to within 20–30% of traditional in situ gauging station measurements and good tracking of flow changes over time. Within such accuracies, the door appears open for quantifying river resources globally with repeat imaging, both retroactively and henceforth into the future, with strong implications for water resource management, food security, ecosystem studies, flood forecasting, and geopolitics. PMID:24639551

  15. Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry.

    Science.gov (United States)

    Gleason, Colin J; Smith, Laurence C

    2014-04-01

    Rivers provide critical water supply for many human societies and ecosystems, yet global knowledge of their flow rates is poor. We show that useful estimates of absolute river discharge (in cubic meters per second) may be derived solely from satellite images, with no ground-based or a priori information whatsoever. The approach works owing to discovery of a characteristic scaling law uniquely fundamental to natural rivers, here termed a river's at-many-stations hydraulic geometry. A first demonstration using Landsat Thematic Mapper images over three rivers in the United States, Canada, and China yields absolute discharges agreeing to within 20-30% of traditional in situ gauging station measurements and good tracking of flow changes over time. Within such accuracies, the door appears open for quantifying river resources globally with repeat imaging, both retroactively and henceforth into the future, with strong implications for water resource management, food security, ecosystem studies, flood forecasting, and geopolitics. PMID:24639551

  16. Satellite Image Processing for Land Use and Land Cover Mapping

    Directory of Open Access Journals (Sweden)

    Ashoka Vanjare

    2014-09-01

    Full Text Available In this paper, urban growth of Bangalore region is analyzed and discussed by using multi-temporal and multi-spectral Landsat satellite images. Urban growth analysis helps in understanding the change detection of Bangalore region. The change detection is studied over a period of 39 years and the region of interest covers an area of 2182 km2. The main cause for urban growth is the increase in population. In India, rapid urbanization is witnessed due to an increase in the population, continuous development has affected the existence of natural resources. Therefore observing and monitoring the natural resources (land use plays an important role. To analyze changed detection, researcher’s use remote sensing data. Continuous use of remote sensing data helps researchers to analyze the change detection. The main objective of this study is to monitor land cover changes of Bangalore district which covers rural and urban regions using multi-temporal and multi-sensor Landsat - multi-spectral scanner (MSS, thematic mapper (TM, Enhanced Thematic mapper plus (ETM+ MSS, TM and ETM+ images captured in the years 1973, 1992, 1999, 2002, 2005, 2008 and 2011. Temporal changes were determined by using maximum likelihood classification method. The classification results contain four land cover classes namely, built-up, vegetation, water and barren land. The results indicate that the region is densely developed which has resulted in decrease of water and vegetation regions. The continuous transformation of barren land to built-up region has affected water and vegetation regions. Generally, from 1973 to 2011 the percentage of urban region has increased from 4.6% to 25.43%, mainly due to urbanization.

  17. Effect of different spatial resolution of satellite image to observe the forest condition using satellite image and National Forest Inventory data

    Science.gov (United States)

    Kajisa, T.; Mizoue, N.; Yoshida, S.

    2010-12-01

    One of the most substantial needs in forest management planning is information about the condition of the forest. Strategic decisions concerning timber policies, decisions about timing and spatial extent of forest operations, and operational decisions such as work plans are all examples where accurate information of the forest conditions are required. Landsat has played the important role for land cover observation in the past, but, got a serious problem. Currently, many kinds of satellite image are available to monitor land cover. So, the utility of different types of satellite image have to be evaluated for land cover monitoring. On the other hands, in Japan, National Forest Inventory (NFI) has been conducted since 1999 with the aim of understanding the state and dynamics of various aspects in forests such as wood production and biodiversity throughout the country. However, few studies have been conducted to combine the satellite image and NFI data. Therefore, the objective of this study was to evaluate the effect of different spatial resolution of satellite image to observe the forest condition (forest/non-forest, forest types, forest stand volume) using satellite image and NFI data.

  18. 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.

  19. Autonomous sensor-based dual-arm satellite grappling

    Science.gov (United States)

    Wilcox, Brian; Tso, Kam; Litwin, Todd; Hayati, Samad; Bon, Bruce

    1989-01-01

    Dual-arm satellite grappling involves the integration of technologies developed in the Sensing and Perception (S&P) Subsystem for object acquisition and tracking, and the Manipulator Control and Mechanization (MCM) Subsystem for dual-arm control. S&P acquires and tracks the position, orientation, velocity, and angular velocity of a slowly spinning satellite, and sends tracking data to the MCM subsystem. MCM grapples the satellite and brings it to rest, controlling the arms so that no excessive forces or torques are exerted on the satellite or arms. A 350-pound satellite mockup which can spin freely on a gimbal for several minutes, closely simulating the dynamics of a real satellite is demonstrated. The satellite mockup is fitted with a panel under which may be mounted various elements such as line replacement modules and electrical connectors that will be used to demonstrate servicing tasks once the satellite is docked. The subsystems are housed in three MicroVAX II microcomputers. The hardware of the S&P Subsystem includes CCD cameras, video digitizers, frame buffers, IMFEX (a custom pipelined video processor), a time-code generator with millisecond precision, and a MicroVAX II computer. Its software is written in Pascal and is based on a locally written vision software library. The hardware of the MCM Subsystem includes PUMA 560 robot arms, Lord force/torque sensors, two MicroVAX II computers, and unimation pneumatic parallel grippers. Its software is written in C, and is based on a robot language called RCCL. The two subsystems are described and test results on the grappling of the satellite mockup with rotational rates of up to 2 rpm are provided.

  20. An Analytical Framework for Assessing the Efficacy of Small Satellites in Performing Novel Imaging Missions

    Science.gov (United States)

    Weaver, Oesa A.

    In the last two decades, small satellites have opened up the use of space to groups other than governments and large corporations, allowing for increased participation and experimentation. This democratization of space was primarily enabled by two factors: improved technology and reduced launch costs. Improved technology allowed the miniaturization of components and reduced overall cost meaning many of the capabilities of larger satellites could be replicated at a fraction of the cost. In addition, new launcher systems that could host many small satellites as ride-shares on manifested vehicles lowered launch costs and simplified the process of getting a satellite into orbit. The potential of these smaller satellites to replace or augment existing systems has led to a flood of potential satellite and mission concepts, often with little rigorous study of whether the proposed satellite or mission is achievable or necessary. This work proposes an analytical framework to aid system designers in evaluating the ability of an existing concept or small satellite to perform a particular imaging mission, either replacing or augmenting existing capabilities. This framework was developed and then refined by application to the problem of using small satellites to perform a wide area search mission -- a mission not possible with existing imaging satellites, but one that would add to current capabilities. Requirements for a wide area search mission were developed, along with a list of factors that would affect image quality and system performance. Two existing small satellite concepts were evaluated for use by examining image quality from the systems, selecting an algorithm to perform the search function automatically, and then assessing mission feasibility by applying the algorithm to simulated imagery. Finally, a notional constellation design was developed to assess the number of satellites required to perform the mission. It was found that a constellation of 480 Cube

  1. Assessment of Off-shore Wind Energy Resource in China using QuikSCAT Satellite data and SAR Satellite Images

    DEFF Research Database (Denmark)

    Xiuzhi, Zhang; Yanbo, Shen; Jingwei, Xu;

    2010-01-01

    From August 2008 to August 2009, the project ‘Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China’ was carried out by China Meteorological Administration (CMA), which was funded by the EU-China Energy and Environment Programme (EEP). As one...... part of the project, off-shore wind energy resource in China was assessed with QuikSCAT Satellite data and SAR Satellite Images. In this paper, the results from these two ways were introduced....

  2. Automatic archaeological feature extraction from satellite VHR images

    Science.gov (United States)

    Jahjah, Munzer; Ulivieri, Carlo

    2010-05-01

    Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were

  3. Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data

    Directory of Open Access Journals (Sweden)

    Jonikavičius D

    2013-04-01

    Full Text Available This paper introduces a method for rapid forest damage assessment using satellite images and stand-wise forest inventory data. Two Landsat 5 Thematic Mapper (TM images from June and September 2010 and data from a forest stand register developed within the frameworks of conventional stand-wise forest inventories in Lithuania were used to assess the forest damage caused by wind storms that occurred on August 8, 2010. Satellite images were geometrically and radiometrically corrected. The percentage of damage in terms of wind-fallen or broken tree volume was then predicted for each forest compartment within the zone potentially affected by the wind storm, using the non-parametric k-nearest neighbor technique. Satellite imagery-based difference images and general forest stand characteristics from the stand register were used as the auxiliary data sets for prediction. All auxiliary data were available from existing databases, and therefore did not involve any added data acquisition costs. Simultaneously, aerial photography of the area damaged by the wind storm was carried-out and color infrared (CIR orthophotos with a resolution of 0.5 x 0.5 m were produced. A precise manual interpretation of the effects of the wind storm was used to validate satellite image-based estimates. The total wind damaged volume in pine dominating forest (~1.180.000 m3 was underestimated by 2.2%, in predominantly spruce stands (~233.000 m3 by 2.6% and in predominantly deciduous stands (~195.000 m3 by 4.2%, compared to validation data. The overall accuracy of identification of wind-damaged areas was around 95-98%, based solely on difference data from satellite images gathered on two dates.

  4. SOFT project: a new forecasting system based on satellite data

    OpenAIRE

    Pascual, Ananda; Orfila, Alejandro; Álvarez, Alberto; Hernández-García, Emilio; Gomis, Damià; Barth, Alexander; Tintoré, Joaquín

    2002-01-01

    The aim of the SOFT project is to develop a new ocean forecasting system by using a combination of satellite data, evolutionary programming and numerical ocean models. To achieve this objective two steps are proposed: (1) to obtain an accurate ocean forecasting system using genetic algorithms based on satellite data; and (2) to integrate the above new system into existing deterministic numerical models. Evolutionary programming will be employed to build “intelligent” systems that,...

  5. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  6. Digital Video Broadcast Return Channel via Satellite (DVB-RCS Hub for Satellite Based E-Learning

    Directory of Open Access Journals (Sweden)

    N.G.Vasantha Kumar

    2011-02-01

    Full Text Available This paper discusses in-house designed and developed scale-down DVB-RCS hub along with the performance of the realized hub. This development is intended to support the Satellite Based e-Learning initiative in India. The scale-down DVB-RCS HUB is implemented around a single PC with other subsystems making it very cost effective and unique of its kind. This realization will drastically reduce the total cost of Satellite based Education Networks as very low cost commercially available Satellite Interactive Terminals (SITs complying to open standard could be used at remote locations. The system is successfully tested to work with a commercial SIT using a GEO satellite EDUSAT which is especially dedicated for satellite based e-Learning. The internal detail of the DVB-RCS Forward and Return Link Organization and how it manages the Satellite Interactive Terminals access to the satellite channel using MF-TDMA approach has been described.

  7. DIGITAL VIDEO BROADCAST RETURN CHANNEL VIA SATELLITE (DVB-RCS HUB FOR SATELLITE BASED E-LEARNING

    Directory of Open Access Journals (Sweden)

    N.G.Vasantha Kumar

    2011-02-01

    Full Text Available This paper discusses in-house designed and developed scale-down DVB-RCS hub along with the performance of the realized hub. This development is intended to support the Satellite Based e-Learning initiative in India. The scale-down DVB-RCS HUB is implemented around a single PC with other subsystems making it very cost effective and unique of its kind. This realization will drastically reduce the total cost of Satellite based Education Networks as very low cost commercially available Satellite Interactive Terminals (SITs complying to open standard could be used at remote locations. The system is successfully tested to work with a commercial SIT using a GEO satellite EDUSAT which is especially dedicated for satellite based e-Learning. The internal detail of the DVB-RCS Forward and Return Link Organization and how it manages the Satellite Interactive Terminals access to the satellite channel using MF-TDMA approach has been described.

  8. Influence of relativistic effects on satellite-based clock synchronization

    Science.gov (United States)

    Wang, Jieci; Tian, Zehua; Jing, Jiliang; Fan, Heng

    2016-03-01

    Clock synchronization between the ground and satellites is a fundamental issue in future quantum telecommunication, navigation, and global positioning systems. Here, we propose a scheme of near-Earth orbit satellite-based quantum clock synchronization with atmospheric dispersion cancellation by taking into account the spacetime background of the Earth. Two frequency entangled pulses are employed to synchronize two clocks, one at a ground station and the other at a satellite. The time discrepancy of the two clocks is introduced into the pulses by moving mirrors and is extracted by measuring the coincidence rate of the pulses in the interferometer. We find that the pulses are distorted due to effects of gravity when they propagate between the Earth and the satellite, resulting in remarkably affected coincidence rates. We also find that the precision of the clock synchronization is sensitive to the source parameters and the altitude of the satellite. The scheme provides a solution for satellite-based quantum clock synchronization with high precision, which can be realized, in principle, with current technology.

  9. Determination of Destructed and Infracted Forest Areas with Multi-temporal High Resolution Satellite Images

    Science.gov (United States)

    Seker, D. Z.; Unal, A.; Kaya, S.; Alganci, U.

    2015-12-01

    Migration from rural areas to city centers and their surroundings is an important problem of not only our country but also the countries that under development stage. This uncontrolled and huge amount of migration brings out urbanization and socio - economic problems. The demand on settling the industrial areas and commercial activities nearby the city centers results with a negative change in natural land cover on cities. Negative impacts of human induced activities on natural resources and land cover has been continuously increasing for decades. The main human activities that resulted with destruction and infraction of forest areas can be defined as mining activities, agricultural activities, industrial / commercial activities and urbanization. Temporal monitoring of the changes in spatial distribution of forest areas is significantly important for effective management and planning progress. Changes can occur as spatially large destructions or small infractions. Therefore there is a need for reliable, fast and accurate data sources. At this point, satellite images proved to be a good data source for determination of the land use /cover changes with their capability of monitoring large areas with reasonable temporal resolutions. Spectral information derived from images provides discrimination of land use/cover types from each other. Developments in remote sensing technology in the last decade improved the spatial resolution of satellites and high resolution images were started to be used to detect even small changes in the land surface. As being the megacity of Turkey, Istanbul has been facing a huge migration for the last 20 years and effects of urbanization and other human based activities over forest areas are significant. Main focus of this study is to determine the destructions and infractions in forest areas of Istanbul, Turkey with 2.5m resolution SPOT 5 multi-temporal satellite imagery. Analysis was mainly constructed on threshold based classification of

  10. A method of using commercial virtual satellite image to check the pattern painting spot effect

    Science.gov (United States)

    Wang, Zheng-gang; Kang, Qing; Shen, Zhi-qiang; Cui, Chang-bin

    2014-02-01

    A method of using commercial virtual satellite image to check the pattern painting spot effect contrast with the satellite images before painting and after painting have been discussed. Using a housetop as the testing platform analyses and discusses the factors' influence such as resolution of satellite image, spot size and color of pattern painting spot and pattern painting camouflage method choosing to the plan implement. The pattern painting design and spot size used in the testing has been ensured, and housetop pattern painting has been painted. Finally, the small spot pattern painting camouflage effect of engineering using upon painting pattern size, color and texture have been checked, contrasting with the satellite image before painting and after painting.

  11. New Generation Meteorological Satellite Imager Aviation Decision Support Applications for Detection of Convection, Turbulence, and Volcanic Ash

    Science.gov (United States)

    Feltz, Wayne

    2016-04-01

    A suite of aviation related decision support products have been in development to meet GOES-R science requirements since 2008 and are being evaluated to assess meteorological hazards to aircraft in flight derived from the current generation of European Spinning Enhanced Visible and Infrared Imager (SEVIRI) imager data. This presentation will focus on GOES-R Advanced Baseline Imager (ABI) measurement requirements relating to satellite-based aviation convective, turbulence, and volcanic ash/SO2 products that can be applied globally on next generation geostationary imagers including the Japanese Himawari, South Korean COMS (AMI), and European Metop-SG imagers. These new methodologies have relevance on current generation GOES and SEVIRI imagers, and overview will include discussion on how product utility has been improved through satellite GOES-R/JPSS Proving Ground NOAA testbed activities. Satellite-based decision support for aviation context toward improvement of future air transportation route planning and warning for the general public with emphasis on successfully bridging research to operations will also be discussed with anticipated October 2016 launch of GOES-R.

  12. A Multivariate Model for Coastal Water Quality Mapping Using Satellite Remote Sensing Images

    OpenAIRE

    Yeng-Fung Wang; Ke-Sheng Cheng; Ming-Daw Su; Yi-Ting Lien; Shu-Mei Hsu; Wei-Chun Hung; Ju-Chen Hou; Jun-Jih Liou; Yuan-Fong Su

    2008-01-01

    This study demonstrates the feasibility of coastal water quality mapping using satellite remote sensing images. Water quality sampling campaigns were conducted over a coastal area in northern Taiwan for measurements of three water quality variables including Secchi disk depth, turbidity, and total suspended solids. SPOT satellite images nearly concurrent with the water quality sampling campaigns were also acquired. A spectral reflectance estimation scheme proposed in this study was applied to...

  13. Building Change Detection in Very High Resolution Satellite Stereo Image Time Series

    Science.gov (United States)

    Tian, J.; Qin, R.; Cerra, D.; Reinartz, P.

    2016-06-01

    There is an increasing demand for robust methods on urban sprawl monitoring. The steadily increasing number of high resolution and multi-view sensors allows producing datasets with high temporal and spatial resolution; however, less effort has been dedicated to employ very high resolution (VHR) satellite image time series (SITS) to monitor the changes in buildings with higher accuracy. In addition, these VHR data are often acquired from different sensors. The objective of this research is to propose a robust time-series data analysis method for VHR stereo imagery. Firstly, the spatial-temporal information of the stereo imagery and the Digital Surface Models (DSMs) generated from them are combined, and building probability maps (BPM) are calculated for all acquisition dates. In the second step, an object-based change analysis is performed based on the derivative features of the BPM sets. The change consistence between object-level and pixel-level are checked to remove any outlier pixels. Results are assessed on six pairs of VHR satellite images acquired within a time span of 7 years. The evaluation results have proved the efficiency of the proposed method.

  14. NOAA Geostationary Operational Environmental Satellite (GOES) Imager Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Geostationary Operational Environmental Satellite (GOES) series provides continuous measurements of the atmosphere and surface over the Western Hemisphere....

  15. NEPR World View 2 Satellite Mosaic - NOAA TIFF Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a mosaic of World View 2 panchromatic satellite imagery of Northeast Puerto Rico that contains the shallow water area (0-35m deep) surrounding...

  16. The Matsu Wheel: A Cloud-based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

    OpenAIRE

    Patterson, Maria T; Anderson, Nikolas; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert; Handy, Matthew; Ly, Vuong; Mandl, Dan; Pederson, Shane; Pivarski, Jim; Powell, Ray; Spring, Jonathan; Wells, Walt

    2016-01-01

    Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for the cloud-based processing of Earth satellite imagery. A particular focus is the development of applications for detecting fires and floods to help support natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStac...

  17. 基于遥感的达来诺尔湖泊水域面积变化研究%The Water Body Area Changes of Dalainur Lake Based on Satellite Images of Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    张宝林; 贾瑞晨; 张倩; 程高

    2011-01-01

    达来诺尔是浑善达克地区重要的湖泊之一,利用遥感技术,通过近红外单波段灰度阈值法对达来诺尔的水域面积进行了分析。研究表明:单波段灰度阈值法可以简单快速地实现湖泊水体信息的提取和水域面积的变化研究,1975年,1987年,2001年和2008年四期遥感影像表明达来诺尔水域自1975年以来一直在萎缩,尤其是进入21世纪以后,湖泊的四周水域均发生明显的变化,湖泊萎缩和干涸是人类必须面临的重要环境问题之一。随着气候变暖和人口压力的增加,浑善达克沙地湖泊湿地的保护和生态环境的可持续发展必将面临更为严峻的考验。%The changes of the area of Dalainur,one of the key lakes in Otintag Sandy Land,were analyzed in this paper based on remote sensing technology.The results show that the information about the lake and its changes in area of water body can be achieved quickly and conveniently by the method of single near infrared grayscale threshold.Satellite images of remote sensing,acquired by Landsat in 1975,1989,2001 and 2008,presented that Dalainur had been shrinking since 1975.Especially with the advent of the 21st century,the lake began to change significantly on all sides.Lakes shrinking and drying up are the important environmental issue that human has to cope with seriously.Under the pressure from global warming and population growth,the lake and wetland protection in Otintag Sandy Land and its local eco-environment sustainable development will face the greater challenges.

  18. Tropical cyclone intensity estimation using temporal and image analysis of satellite data

    Science.gov (United States)

    Fetanat, G.; Homaifar, A.; Knapp, K.

    2012-12-01

    Tropical cyclones (TCs) are becoming an increasing threat to life and property. Developing an automated technique to estimate TC intensity and to overcome the existing errors in estimation is still a challenge. The Dvorak technique (DT) is the state-of-the-art method that has been used over three decades for estimating the intensity of a tropical cyclone. The DT subjectively estimates TC intensity based on visible and infrared satellite images. In spite of wide usage of the DT for TC analysis, it has some limitations. The most important one is that the DT does not use the valuable historical data mainly because of the challenges on computing and human resources. This research is inspired by the availability of historical TC satellite data. We hypothesize that discovering unknown regularities and abnormalities that may exist in the large group of past observations could help human experts interpret TC intensity changes from various points of view. Our goal is to provide a data mining tool that increases the ability of human experts to analyze huge amount of historical data for TC intensity estimation. The proposed intensity estimation algorithm has two parts: temporal constraints and image analysis. Temporal information provides a priori estimates of storm intensity (in terms of wind speed) prior to using any satellite image analysis. Hurricane Satellite data (HURSAT-B1) includes best-track intensity are used as a training data. A case study using North Atlantic Hurricane Satellite data from 1988-2009 is considered. The temporal analysis uses the age of the cyclone, 6, 12 and 24 hours prior intensities as predictors of the expected intensity. The 10 closest analogs (determined by a K-nearest-neighbor algorithm) are averaged to estimate the intensity. The distribution of intensity estimation errors of the proposed technique shows that 50% of the estimates have a mean absolute error less than 4.4 knots, 75% are 6.3 knots and 90% are within 8 knots. Several validation

  19. Identity Based Color Image Cryptography

    OpenAIRE

    Gopi Krishnan S; Loganathan D

    2011-01-01

    An Identity based cryptography based on visual cryptography scheme was proposed for protecting color image. A color image to be protected and authentic entities such as account number, password, signature image are given as input. The binary key image is obtained by distributing the digital signature of obtained authentic entities. A secret color image which needs to be communicated is decomposed into three grayscale tones of Y-Cb-Cr color component. Then these grayscale images are half-toned...

  20. Satellite-Based Study of Glaciers Retreat in Northern Pakistan

    Science.gov (United States)

    Munir, Siraj

    Glaciers serve as a natural regulator of regional water supplies. About 16933 Km 2 area of glaciers is covered by Pakistan. These glaciers are enormous reservoirs of fresh water and their meltwater is an important resource which feed rivers in Pakistan. Glacier depletion, especially recent melting can affect agriculture, drinking water supplies, hydro-electric power, and ecological habitats. This can also have a more immediate impact on Pakistan's economy that depends mainly on water from glacier melt. Melting of seasonal snowfall and permanent glaciers has resulted not only in reduction of water resources but also caused flash floods in many areas of Pakistan. With the advent of satellite technology, using optical and SAR data the study of glaciers, has become possible. Using temporal data, based on calculation of snow index, band ratios and texture reflectance it has been revealed that the rate of glacier melting has increased as a consequent of global warming. Comparison of Landsat images of Batura glacier for October 1992 and October 2000 has revealed that there is a decrease of about 17 sq km in Batura glaciers. Although accurate changes in glacier extent cannot be assessed without baseline information, these efforts have been made to analyze future changes in glaciated area.

  1. Assimilation of satellite images into a sediment transport model of Lake Michigan.

    Energy Technology Data Exchange (ETDEWEB)

    Stroud, J.; Lesht, B.; Beletsky, D.; Stein, M.; Univ. of Pennsylvania; NOAA; Univ. of Michigan; Univ. of Chicago

    2009-01-01

    In this paper we develop and examine several schemes for combining daily images obtained from the Sea-viewing Wide Field Spectrometer (SeaWiFS) with a two-dimensional sediment transport model of Lake Michigan. We consider two data assimilation methods, direct insertion and a kriging-based approach, and perform a forecasting study focused on a 2-month period in spring 1998 when a large storm caused substantial amounts of sediment resuspension and horizontal sediment transport in the lake. By beginning with the simplest possible forecast method and sequentially adding complexity we are able to assess the improvements offered by combining the satellite data with the numerical model. In our application, we find that data assimilation schemes that include both the data and the lake dynamics improve forecast root mean square error by 40% over purely model-based approaches and by 20% over purely data-based approaches.

  2. The Economical Microbolometer-Based Environmental Radiometer Satellite (EMBERSat) Designed for Forest Fire Detection and Monitoring

    Science.gov (United States)

    Lancaster, Redgie S.; Skillman, David R.; Welch, Wayne C.; Spinhirne, James D.; Manizade, Katherine F.; Beecken, Brian P.

    2004-01-01

    Thermal infrared imagery from several satellite instruments, such as the NOAA AVHRR and the NASA MODIS, is presently used to detect and map forest fires. But while these radiometers can identify fires they are designed and optimized for cloud detection, providing relatively low spatial resolution and quickly saturating even for small fires. Efforts to detect and monitor forest fires from space would benefit from the development of single-sensor satellites designed specifically for this purpose. With the advent of uncooled thermal detectors, and thus the absence of aggressive cooling, the possibility of developing small satellites for the purpose of fire detection and monitoring becomes practical and cost-effective. Thus is the case with the Economical Microbolometer Based Environmental Radiometer Satellite (EMBERSat) program. The objective of this program is to develop a single, prototype satellite that will provide multiband thermal imagery with a spatial resolution of 250m and a dynamic range of 300-1000K. The thermal imaging payload has flight heritage in the Infrared Spectral Imaging Radiometer that flew aboard mission STS-85 and the spacecraft is a variant of the SimpleSat bus launched from the shuttle Columbia as part of STS-105. The EMBERSat program is a technology demonstration initiative with the eventual goal of providing high-resolution thermal imagery to both the scientific community and the public.

  3. Delineation of burnt mountain forest areas by high-resolution satellite images

    Directory of Open Access Journals (Sweden)

    Deligios G

    2007-01-01

    Full Text Available In this paper we present a remote sensing technique, based on very high spatial resolution Quickbird satellite data, aimed to map burnt forested areas located in alpine environment hit by winter fires occurred in Lombardia Region in the 2005 year. Quickbird satellite images have a spatial resolution of 2.5 m and are characterized by 4 spectral bands covering the regions of blue, green, red and near infrared. Burnt areas were automatically extracted by using an object oriented classification combined with a connectivity algorithm developed with the aim to join burnt isolates pixel with the main body of the area hit by fire. The proposed algorithm is based on the exploitation of a Gaussian function that produces a degree of membership to be burnt for every pixel not classified as burnt by means of the preliminary automatic classification. The membership function is established on the base of the spatial distance and it decrease according the full width at half maximum of the Gaussian function. The produced maps have been compared with the burnt area boundaries obtained by means of field survey based on GPS measurements; this allowed us to estimate the goodness of the proposed method. The comparison between the results produced by the connectivity algorithm and the reference measured in ground showed high degrees of accuracy with errors ranging from 3 to 20%.

  4. Japanese Global Precipitation Measurement (GPM) mission status and application of satellite-based global rainfall map

    Science.gov (United States)

    Kachi, Misako; Shimizu, Shuji; Kubota, Takuji; Yoshida, Naofumi; Oki, Riko; Kojima, Masahiro; Iguchi, Toshio; Nakamura, Kenji

    2010-05-01

    As accuracy of satellite precipitation estimates improves and observation frequency increases, application of those data to societal benefit areas, such as weather forecasts and flood predictions, is expected, in addition to research of precipitation climatology to analyze precipitation systems. There is, however, limitation on single satellite observation in coverage and frequency. Currently, the Global Precipitation Measurement (GPM) mission is scheduled under international collaboration to fulfill various user requirements that cannot be achieved by the single satellite, like the Tropical Rainfall Measurement Mission (TRMM). The GPM mission is an international mission to achieve high-accurate and high-frequent rainfall observation over a global area. GPM is composed of a TRMM-like non-sun-synchronous orbit satellite (GPM core satellite) and constellation of satellites carrying microwave radiometer instruments. The GPM core satellite carries the Dual-frequency Precipitation Radar (DPR), which is being developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT), and microwave radiometer provided by the National Aeronautics and Space Administration (NASA). Development of DPR instrument is in good progress for scheduled launch in 2013, and DPR Critical Design Review has completed in July - September 2009. Constellation satellites, which carry a microwave imager and/or sounder, are planned to be launched around 2013 by each partner agency for its own purpose, and will contribute to extending coverage and increasing frequency. JAXA's future mission, the Global Change Observation Mission (GCOM) - Water (GCOM-W) satellite will be one of constellation satellites. The first generation of GCOM-W satellite is scheduled to be launched in 2011, and it carries the Advanced Microwave Scanning Radiometer 2 (AMSR2), which is being developed based on the experience of the AMSR-E on EOS Aqua satellite

  5. Genetic Optimization for Associative Semantic Ranking Models of Satellite Images by Land Cover

    Directory of Open Access Journals (Sweden)

    Nil Kilicay-Ergin

    2013-06-01

    Full Text Available Associative methods for content-based image ranking by semantics are attractive due to the similarity of generated models to human models of understanding. Although they tend to return results that are better understood by image analysts, the induction of these models is difficult to build due to factors that affect training complexity, such as coexistence of visual patterns in same images, over-fitting or under-fitting and semantic representation differences among image analysts. This article proposes a methodology to reduce the complexity of ranking satellite images for associative methods. Our approach employs genetic operations to provide faster and more accurate models for ranking by semantic using low level features. The added accuracy is provided by a reduction in the likelihood to reach local minima or to overfit. The experiments show that, using genetic optimization, associative methods perform better or at similar levels as state-of-the-art ensemble methods for ranking. The mean average precision (MAP of ranking by semantic was improved by 14% over similar associative methods that use other optimization techniques while maintaining smaller size for each semantic model.

  6. Experimental comparison between coppice clearcuts observed by high resolution satellite images and administrative statistics in central-southern Italy

    OpenAIRE

    Marchetti M; Chirici G; Tonti D; Mattioli W; Lamonaca A; Giuliarelli D; Corona P

    2007-01-01

    The aim of this work is to test the potential of SPOT5 satellite images for monitoring coppice clearcuts. The clearcuts, delineated by on screen interpretation of the satellite images, are compared with the administrative statistics reported for a sample of 230 administrative units. Administrative statistics result significantly lower than those by satellite images, with an average ratio between clearcut area observed by SPOT5 images within each sample unit and the corresponding administrativ...

  7. SOFT project: a new forecasting system based on satellite data

    Science.gov (United States)

    Pascual, Ananda; Orfila, A.; Alvarez, Alberto; Hernandez, E.; Gomis, D.; Barth, Alexander; Tintore, Joaquim

    2002-01-01

    The aim of the SOFT project is to develop a new ocean forecasting system by using a combination of satellite dat, evolutionary programming and numerical ocean models. To achieve this objective two steps are proved: (1) to obtain an accurate ocean forecasting system using genetic algorithms based on satellite data; and (2) to integrate the above new system into existing deterministic numerical models. Evolutionary programming will be employed to build 'intelligent' systems that, learning form the past ocean variability and considering the present ocean state, will be able to infer near future ocean conditions. Validation of the forecast skill will be carried out by comparing the forecasts fields with satellite and in situ observations. Validation with satellite observations will provide the expected errors in the forecasting system. Validation with in situ data will indicate the capabilities of the satellite based forecast information to improve the performance of the numerical ocean models. This later validation will be accomplished considering in situ measurements in a specific oceanographic area at two different periods of time. The first set of observations will be employed to feed the hybrid systems while the second set will be used to validate the hybrid and traditional numerical model results.

  8. Building identification from very high-resolution satellite images

    Science.gov (United States)

    Lhomme, Stephane

    (geometric and radiometric quality), the basic image of our analysis. A review of existing methods clearly show a common limit: the detection of building boundaries. Consequently, we evaluate the efficiency of several segmentation methods that finally induces a change in our methodological approach. The fourth chapter contains the central part of our work, which consists in the development of a building extraction method. After strict formalisation of our, objectives, we present the theoretical principles of our approach based on textural buildings definition. In the identification process we use only one parameter that accounts at the same time for the variance of the building and the variance of its immediate surroundings. In the following, additional information (shadow and vegetation) is integrated to reduce commission errors. The last chapter exposes the results. They clearly show the capacity of our method for building identification. However, they show some limitations of application, especially on large size buildings and/or in heterogeneous areas. We also propose possible applications such as analysis of suburban buildings or detection of natural disaster damages. The main outcome of this work is the originality of our theoretical approach that encourages new reflections for future research.

  9. Deep and shallow structures in the Arctic region imaged by satellite magnetic and gravity data

    Science.gov (United States)

    Gaina, Carmen; Panet, Isabelle; Shephard, Grace

    2016-07-01

    The last decade has seen an increase in geoscientific data collection, which, together with available and older classified data made publicly available, is contributing to increasing our knowledge about Earth's structure and evolution. Despite this development, there are many gaps in data coverage in remote, hard-to-access regions. Satellite data have the advantage of acquiring measurements steadily and covering the entire globe. From a tectonics point of view, the specific heights of various satellites allow for the identification of moderate to large tectonic features, and can shed light on Earth's lower crust and lithosphere structure. In this contribution I discuss the use of magnetic and gravity models based on satellite data in deciphering the tectonic structure of remote areas. The present day Circum-Arctic region comprises a variety of tectonic settings: from active seafloor spreading in the North Atlantic and Eurasian Basin, and subduction in the North Pacific, to long-lived stable continental platforms in North America and Asia. A series of rifted margins, abandoned rifted areas and presumably extinct oceanic basins fringe these regions. Moreover, rifting- and seafloor spreading-related processes formed many continental splinters and terranes that were transported and docked at higher latitudes. Volcanic provinces of different ages have also been identified, from the Permian-Triassic Siberian traps at ca. 251 Ma to the (presumably) Cretaceous HALIP and smaller Cenozoic provinces in northern Greenland and the Barents Sea. We inspect global lithospheric magnetic data in order to identify the signature of the main volcanic provinces in the High Arctic. One of the most striking features in the Arctic domain is the strong magnetic anomaly close to the North Pole that correlates with a large, igneous oceanic plateau called the Alpha Mendeleev Ridge. The intensity and extent of the magnetic anomalies recorded by aircraft or satellites point towards a very thick

  10. Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

    Science.gov (United States)

    Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

    2008-07-01

    SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

  11. Star-based defocus computing technique for PLEIADES-HR satellites

    Science.gov (United States)

    Amberg, Virginie; Bernard, Laurent; Latry, Christophe

    2015-10-01

    PLEIADES-HR is an earth observing system developed by the French National Space Agency, CNES. It consists of two satellites launched on December 2011 (PHR-1A) and December 2012 (PHR-1B). Each satellite is designed to provide optical 70 cm resolution panchromatic and 2.80m colored images to civilian and defense users. During commissioning period of these satellites, thanks to their extreme agility, new calibration methods have been tested based on the observation of celestial bodies, and stars in particular. It has then been made possible to perform MTF and defocus measurement (in order to refocus), geometrical bias computation, focal plane assessment, absolute calibration, ghost images localization, micro-vibrations measurement, etc… This article deals with the problem of satellite refocusing. By using images of stars, the problem can be considered as a phase diversity inverse problem. Significant evolution has been brought to the previous method developed during the commissioning period in order to improve accuracy and reduce operating constraints of the method.

  12. Engineering satellite-based navigation and timing global navigation satellite systems, signals, and receivers

    CERN Document Server

    Betz, J

    2016-01-01

    This book describes the design and performance analysis of satnav systems, signals, and receivers. It also provides succinct descriptions and comparisons of all the world’s satnav systems. Its comprehensive and logical structure addresses all satnav signals and systems in operation and being developed. Engineering Satellite-Based Navigation and Timing: Global Navigation Satellite Systems, Signals, and Receivers provides the technical foundation for designing and analyzing satnav signals, systems, and receivers. Its contents and structure address all satnav systems and signals: legacy, modernized, and new. It combines qualitative information with detailed techniques and analyses, providing a comprehensive set of insights and engineering tools for this complex multidisciplinary field. Part I describes system and signal engineering including orbital mechanics and constellation design, signal design principles and underlying considerations, link budgets, qua tifying receiver performance in interference, and e...

  13. Extracting oil palm crown from WorldView-2 satellite image

    International Nuclear Information System (INIS)

    Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1')

  14. Extracting oil palm crown from WorldView-2 satellite image

    Science.gov (United States)

    Korom, A.; Phua, M.-H.; Hirata, Y.; Matsuura, T.

    2014-02-01

    Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1').

  15. Active machine learning for rapid landslide inventory mapping with VHR satellite images (Invited)

    Science.gov (United States)

    Stumpf, A.; Lachiche, N.; Malet, J.; Kerle, N.; Puissant, A.

    2013-12-01

    VHR satellite images have become a primary source for landslide inventory mapping after major triggering events such as earthquakes and heavy rainfalls. Visual image interpretation is still the prevailing standard method for operational purposes but is time-consuming and not well suited to fully exploit the increasingly better supply of remote sensing data. Recent studies have addressed the development of more automated image analysis workflows for landslide inventory mapping. In particular object-oriented approaches that account for spatial and textural image information have been demonstrated to be more adequate than pixel-based classification but manually elaborated rule-based classifiers are difficult to adapt under changing scene characteristics. Machine learning algorithm allow learning classification rules for complex image patterns from labelled examples and can be adapted straightforwardly with available training data. In order to reduce the amount of costly training data active learning (AL) has evolved as a key concept to guide the sampling for many applications. The underlying idea of AL is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and data structure to iteratively select the most valuable samples that should be labelled by the user. With relatively few queries and labelled samples, an AL strategy yields higher accuracies than an equivalent classifier trained with many randomly selected samples. This study addressed the development of an AL method for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. Our approach [1] is based on the Random Forest algorithm and considers the classifier uncertainty as well as the variance of potential sampling regions to guide the user towards the most valuable sampling areas. The algorithm explicitly searches for compact regions and thereby avoids a spatially disperse sampling pattern

  16. Wildfire monitoring using satellite images, ontologies and linked geospatial data

    NARCIS (Netherlands)

    Kyzirakos, K.; Karpathiotakis, M.; Garbis, G.; Nikolaou, C.; Bereta, K.; Papoutsis, I.; Herekakis, T.; Michail, D.; Koubarakis, M.; Kontoes, C.

    2014-01-01

    Advances in remote sensing technologies have allowed us to send an ever-increasing number of satellites in orbit around Earth. As a result, Earth Observation data archives have been constantly increasing in size in the last few years, and have become a valuable source of data for many scientific and

  17. Identification method of satellite local components based on combined feature metrics

    Science.gov (United States)

    Zhi, Xi-yang; Hou, Qing-yu; Zhang, Wei; Sun, Xuan

    2014-11-01

    In order to meet the requirements of identification of satellite local targets, a new method based on combined feature metrics is proposed. Firstly, the geometric features of satellite local targets including body, solar panel and antenna are analyzed respectively, and then the cluster of each component are constructed based on the combined feature metrics of mathematical morphology. Then the corresponding fractal clustering criterions are given. A cluster model is established, which determines the component classification according to weighted combination of the fractal geometric features. On this basis, the identified targets in the satellite image can be recognized by computing the matching probabilities between the identified targets and the clustered ones, which are weighted combinations of the component fractal feature metrics defined in the model. Moreover, the weights are iteratively selected through particle swarm optimization to promote recognition accuracy. Finally, the performance of the identification algorithm is analyzed and verified. Experimental results indicate that the algorithm is able to identify the satellite body, solar panel and antenna accurately with identification probability up to 95%, and has high computing efficiency. The proposed method can be applied to identify on-orbit satellite local targets and possesses potential application prospects on spatial target detection and identification.

  18. Aerosol climatology over Nile Delta based on MODIS, MISR and OMI satellite data

    OpenAIRE

    H. S. Marey; J. C. Gille; H. M. El-Askary; Shalaby, E. A.; M. E. El-Raey

    2011-01-01

    Since 1999 Cairo and the Nile delta region have suffered from air pollution episodes called the "black cloud" during the fall season. These have been attributed to either burning of agriculture waste or long-range transport of desert dust. Here we present a detailed analysis of the optical and microphysical aerosol properties, based on satellite data. Monthly mean values of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) at 550 nm were examined for the 10 yr ...

  19. Satellite Based Downward Long Wave Radiation by Various Models in Northeast Asia

    OpenAIRE

    Chanyang Sur; Hyunwoo Kim; and Minha Choi

    2014-01-01

    Satellite-based downward long wave radiation measurement under clear sky conditions in Northeast Asia was conducted using five well-known physical models (Brunt 1932, Idso and Jackson 1969, Brutsaert 1975, Satterlund 1979, Prata 1996) with a newly proposed global Rld model (Abramowitz et al. 2012). Data from two flux towers in South Korea were used to validate downward long wave radiation. Moderate resolution imaging spectroradiometer (MODIS) atmospheric profile products were used to develop ...

  20. Application of high-resolution stereo satellite images to detailed landslide hazard assessment

    Science.gov (United States)

    Nichol, Janet E.; Shaker, Ahmed; Wong, Man-Sing

    2006-06-01

    This study investigates and demonstrates the state of the art in remote sensing techniques for detailed landslide hazard assessment applicable to large areas. Since the most common methods of landslide hazard assessment using simple inventories and weighted overlays are heavily dependent on three-dimensional terrain visualization and analysis, stereo satellite images from the IKONOS Very High Resolution (VHR) sensor are used for this study. The DEMs created from IKONOS stereo images appear to be much more accurate and sensitive to micro-scale terrain features than a DEM created from digital contour data with a 2 m contour interval. Pan-sharpened stereo IKONOS images permit interpretation of recent landslides as small as 2-3 m in width as well as relict landslides older than 50 years. A cost-benefit analysis comparing stereo air photo interpretation with stereo satellite image interpretation suggests that stereo satellite imagery is usually more cost-effective for detailed landslide hazard assessment over large areas.

  1. Combing rough set and RBF neural network for large-scale ship recognition in optical satellite images

    International Nuclear Information System (INIS)

    Large scale ship recognition in optical remote sensing images is of great importance for many military applications. It aims to recognize the category information of the detected ships for effective maritime surveillance. The contributions of the paper can be summarized as follows: Firstly, based on the rough set theory, the common discernibility degree is used to compute the significance weight of each candidate feature and select valid recognition features automatically; Secondly, RBF neural network is constructed based on the selected recognition features. Experiments on recorded optical satellite images show the proposed method is effective and can get better classification rates at a higher speed than the state of the art methods

  2. Estimating fractional vegetation cover (FVC) using satellite vegetation indices and digital photo image in Mongolia

    Science.gov (United States)

    Kim, J.

    2015-12-01

    Fractional vegetation cover (FVC) is a useful index of monitoring land cover dynamics and land surface energy partitioning into sensible and latent heats from satellite because it can be estimated by using satellite-based spectral vegetation indices (VI), such as NDVI and EVI. The relationship between FVC and vegetation indices is however variable depending on regional vegetation types and background soil types across different regions. In particular, arid and semi-arid region shows substantial uncertainty in the VI-FVC relations because of sparse vegetation cover and hence, important roles of local soil type in land-surface spectral reflectance. In this study, VI-FVC relations were investigated for arid and semi-arid regions of Mongolia. The FVC data was prepared from digital-camera image interpretation sheets taken at 160 sites in our field excursions from 2012 to 2014. In comparisons with visual inspections, the camera-based FVC showed good linear relations (r = 0.97, p Pearson correlation coefficient and RMSE). In results, the regression models generally showed good agreements in model validations over r = 0.8 (p < 0.001). This study discussed problems in long-term FVC retrieval for the arid and semi-arid regions of Mongolia.

  3. Very high resolution satellite data: New challenges in image analysis

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.; Muraleedharan, P.M.

    or other natural landscapes. Having very high resolution digital data over a landscape will however create new challenges in the field of atmospheric correction, ground registration, image processing and finally the image interpretation itself. Even...

  4. The principle of the positioning system based on communication satellites

    Science.gov (United States)

    Ai, Guoxiang; Shi, Huli; Wu, Haitao; Li, Zhigang; Guo, Ji

    2009-03-01

    It is a long dream to realize the communication and navigation functionality in a satellite system in the world. This paper introduces how to establish the system, a positioning system based on communication satellites called Chinese Area Positioning System (CAPS). Instead of the typical navigation satellites, the communication satellites are configured firstly to transfer navigation signals from ground stations, and can be used to obtain service of the positioning, velocity and time, and to achieve the function of navigation and positioning. Some key technique issues should be first solved; they include the accuracy position determination and orbit prediction of the communication satellites, the measuring and calculation of transfer time of the signals, the carrier frequency drift in communication satellite signal transfer, how to improve the geometrical configuration of the constellation in the system, and the integration of navigation & communication. Several innovative methods are developed to make the new system have full functions of navigation and communication. Based on the development of crucial techniques and methods, the CAPS demonstration system has been designed and developed. Four communication satellites in the geosynchronous orbit (GEO) located at 87.5°E, 110.5°E, 134°E, 142°E and barometric altimetry are used in the CAPS system. The GEO satellites located at 134°E and 142°E are decommissioned GEO (DGEO) satellites. C-band is used as the navigation band. Dual frequency at C1=4143.15 MHz and C2=3826.02 MHz as well as dual codes with standard code (CA code and precision code (P code)) are adopted. The ground segment consists of five ground stations; the master station is in Lintong, Xi’an. The ground stations take a lot of responsibilities, including monitor and management of the operation of all system components, determination of the satellite position and prediction of the satellite orbit, accomplishment of the virtual atomic clock

  5. Prospects of using the k-NN method of classification of satellite images for the forest inventory in Ukraine

    OpenAIRE

    V. Myroniuk

    2015-01-01

    This paper deals with modern experience of statistical inventory of forests using ground-based inventory and remote sensing data (RSD). A detailed analysis of the k-NN method of classification of satellite images is given and features of its applying for thematic mapping of forest fund under the statistical forest inventory defined. The algorithm for calculating the stock of plantings for the statistical software with R open source is shown on the example of local research material.

  6. Forecasting irrigation demand by assimilating satellite images and numerical weather predictions

    Science.gov (United States)

    Pelosi, Anna; Medina, Hanoi; Villani, Paolo; Falanga Bolognesi, Salvatore; D'Urso, Guido; Battista Chirico, Giovanni

    2016-04-01

    Forecasting irrigation water demand, with small predictive uncertainty in the short-medium term, is fundamental for an efficient planning of water resource allocation among multiple users and for decreasing water and energy consumptions. In this study we present an innovative system for forecasting irrigation water demand, applicable at different spatial scales: from the farm level to the irrigation district level. The forecast system is centred on a crop growth model assimilating data from satellite images and numerical weather forecasts, according to a stochastic ensemble-based approach. Different sources of uncertainty affecting model predictions are represented by an ensemble of model trajectories, each generated by a possible realization of the model components (model parameters, input weather data and model state variables). The crop growth model is based on a set of simplified analytical relations, with the aim to assess biomass, leaf area index (LAI) growth and evapotranspiration rate with a daily time step. Within the crop growth model, LAI dynamics is let be governed by temperature and leaf dry matter supply, according to the development stage of the crop. The model assimilates LAI data retrieved from VIS-NIR high-resolution multispectral satellite images. Numerical weather model outputs are those from the European limited area ensemble prediction system (COSMO-LEPS), which provides forecasts up to five days with a spatial resolution of seven kilometres. Weather forecasts are sequentially bias corrected based on data from ground weather stations. The forecasting system is evaluated in experimental areas of southern Italy during three irrigation seasons. The performance analysis shows very accurate irrigation water demand forecasts, which make the proposed system a valuable support for water planning and saving at farm level as well as for water management at larger spatial scales.

  7. LEO AUTONOMOUS NAVIGATION BASED ON IMAGE MOTION

    Institute of Scientific and Technical Information of China (English)

    DUANFang; LIUJian-ye; YUFeng

    2005-01-01

    A method of LEO autonomous navigation is presented based on the nonlinear satellite velocity relative to the earth. The velocity is detected by a high-speed camera, with the attitude information detected by a star sensor. Compared with traditional autonomous navigation by landmark identification, the satellite velocity relarive to the earth is obtained by correlativity analysis of images. It does not need to recognize ground objects or views. Since it is not necessary to pre-store the database of ground marks, lots of memory space can be saved.The state and observation equations are constructed, and the filtering is processed by the Kalman filter. Simulation results show that the system has high autonomous navigation precision in LEO autonomous navigation.

  8. Identification and mapping of natural vegetation on a coastal site using a Worldview-2 satellite image

    OpenAIRE

    Rapinel, Sebastien; Clément, Bernard; Magnanon, Sylvie; Sellin, Vanessa; Hubert-Moy, Laurence

    2014-01-01

    Identification and mapping of natural vegetation are major issues for biodiversity management and conservation. Remotely sensed data with very high spatial resolution are currently used to study vegetation, but most satellite sensors are limited to four spectral bands, which is insufficient to identify some natural vegetation formations. The study objectives are to discriminate natural vegetation and identify natural vegetation formations using a Worldview-2 satellite image. The classificatio...

  9. Price-Based Information Routing in Complex Satellite Networks for

    Science.gov (United States)

    Hussein, I.; Su, J.; Wang, Y.; Wyglinski, A.

    Future space-based situational awareness and space surveillance systems are envisioned to include a large array of satellites that seek to cooperatively achieve full awareness over given space and terrestrial domains. Given the complexity of the communication network architecture of such a system, in this paper we build on the system architecture that was proposed by the presenting author in the 2008 AMOS conference and propose an efficient, adaptable and scalable price-based routing and bandwidth allocation algorithm for the generation, routing and delivery of surveillance information in distributed wireless satellite networks. Due to the potentially large deployments of these satellites, the access points employed in a centralized network control scheme would easily be overwhelmed due to lack of spectral bandwidth, synchronization issues, and multiple access coordination. Alternatively, decentralized schemes could facilitate the flow and transference of information between data gatherers and data collectors via mechanisms such as (multi-hop) routing, allocation of spectral bandwidths per relaying node, and coordination between adjacent nodes. Although there are numerous techniques and concepts focusing on the network operations, control, and management of sensor networks, existing solution approaches require the use of information for routing, allocation, and decision-making that may not be readily available to the satellites in a timely fashion. This is especially true in the literature on price-based routing, where the approach is almost always game theoretic or relies on optimization techniques. Instead of seeking such techniques, in this paper we present algorithms that will (1) be energy-aware, (2) be highly adaptable and responsive to demands and seek delivery of information to desired nodes despite the fact that the source and destination are not globally known, (3) be secure, (4) be efficient in allocating bandwidth, (5) be decentralized and allow for

  10. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    OpenAIRE

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai; Gill, Rashpal S.; Overgaard, Søren

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an opera...

  11. 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.

  12. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery

    Science.gov (United States)

    Sakamoto, Takuto

    2016-01-01

    Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level. PMID:26963526

  13. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery.

    Science.gov (United States)

    Sakamoto, Takuto

    2016-01-01

    Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level. PMID:26963526

  14. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery.

    Directory of Open Access Journals (Sweden)

    Takuto Sakamoto

    Full Text Available Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level.

  15. Evaluating the hydrological consistency of satellite based water cycle components

    KAUST Repository

    Lopez, Oliver

    2016-06-15

    Advances in multi-satellite based observations of the earth system have provided the capacity to retrieve information across a wide-range of land surface hydrological components and provided an opportunity to characterize terrestrial processes from a completely new perspective. Given the spatial advantage that space-based observations offer, several regional-to-global scale products have been developed, offering insights into the multi-scale behaviour and variability of hydrological states and fluxes. However, one of the key challenges in the use of satellite-based products is characterizing the degree to which they provide realistic and representative estimates of the underlying retrieval: that is, how accurate are the hydrological components derived from satellite observations? The challenge is intrinsically linked to issues of scale, since the availability of high-quality in-situ data is limited, and even where it does exist, is generally not commensurate to the resolution of the satellite observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating hydrological observations, it makes sense to first test it over environments with restricted hydrological inputs, before applying it to more hydrological complex basins. Here we explore the concept of hydrological consistency, i.e. the physical considerations that the water budget impose on the hydrologic fluxes and states to be temporally and spatially linked, to evaluate the reproduction of a set of large-scale evaporation (E) products by using a combination of satellite rainfall (P) and Gravity Recovery and Climate Experiment (GRACE) observations of storage change, focusing on arid and semi-arid environments, where the hydrological flows can be more realistically described. Our results indicate no persistent hydrological

  16. Mosquito Larval Habitats, Land Use, and Potential Malaria Risk in Northern Belize from Satellite Image Analyses

    Science.gov (United States)

    Pope, Kevin; Masuoka, Penny; Rejmankova, Eliska; Grieco, John; Johnson, Sarah; Roberts, Donald

    2004-01-01

    The distribution of Anopheles mosquito habitats and land use in northern Belize is examined with satellite data. -A land cover classification based on multispectral SPOT and multitemporal Radarsat images identified eleven land cover classes, including agricultural, forest, and marsh types. Two of the land cover types, Typha domingensis marsh and flooded forest, are Anopheles vestitipennis larval habitats. Eleocharis spp. marsh is the larval habitat for Anopheles albimanus. Geographic Information Systems (GIS) analyses of land cover demonstrate that the amount of T-ha domingensis in a marsh is positively correlated with the amount of agricultural land in the adjacent upland, and negatively correlated with the amount of adjacent forest. This finding is consistent with the hypothesis that nutrient (phosphorus) runoff from agricultural lands is causing an expansion of Typha domingensis in northern Belize. This expansion of Anopheles vestitipennis larval habitat may in turn cause an increase in malaria risk in the region.

  17. Volcview: A Web-Based Platform for Satellite Monitoring of Volcanic Activity and Eruption Response

    Science.gov (United States)

    Schneider, D. J.; Randall, M.; Parker, T.

    2014-12-01

    The U.S. Geological Survey (USGS), in cooperation with University and State partners, operates five volcano observatories that employ specialized software packages and computer systems to process and display real-time data coming from in-situ geophysical sensors and from near-real-time satellite sources. However, access to these systems both inside and from outside the observatory offices are limited in some cases by factors such as software cost, network security, and bandwidth. Thus, a variety of Internet-based tools have been developed by the USGS Volcano Science Center to: 1) Improve accessibility to data sources for staff scientists across volcano monitoring disciplines; 2) Allow access for observatory partners and for after-hours, on-call duty scientists; 3) Provide situational awareness for emergency managers and the general public. Herein we describe VolcView (volcview.wr.usgs.gov), a freely available, web-based platform for display and analysis of near-real-time satellite data. Initial geographic coverage is of the volcanoes in Alaska, the Russian Far East, and the Commonwealth of the Northern Mariana Islands. Coverage of other volcanoes in the United States will be added in the future. Near-real-time satellite data from NOAA, NASA and JMA satellite systems are processed to create image products for detection of elevated surface temperatures and volcanic ash and SO2 clouds. VolcView uses HTML5 and the canvas element to provide image overlays (volcano location and alert status, annotation, and location information) and image products that can be queried to provide data values, location and measurement capabilities. Use over the past year during the eruptions of Pavlof, Veniaminof, and Cleveland volcanoes in Alaska by the Alaska Volcano Observatory, the National Weather Service, and the U.S. Air Force has reinforced the utility of shared situational awareness and has guided further development. These include overlay of volcanic cloud trajectory and

  18. Identity Based Color Image Cryptography

    Directory of Open Access Journals (Sweden)

    Gopi Krishnan S

    2011-05-01

    Full Text Available An Identity based cryptography based on visual cryptography scheme was proposed for protecting color image. A color image to be protected and authentic entities such as account number, password, signature image are given as input. The binary key image is obtained by distributing the digital signature of obtained authentic entities. A secret color image which needs to be communicated is decomposed into three grayscale tones of Y-Cb-Cr color component. Then these grayscale images are half-toned to binary image, and finally the obtained binary images are encrypted using binary key image to obtain binary cipher images. To encrypt Exclusive-OR operation is done on binary key image and three half-tones of secret color image separately. These binary images are combined to obtain cipher. In decryption the shares are decrypted by applying Exclusive-OR operation on cipher and key, then the recovered binary images are inverse half-toned and combined to get secret color image. This scheme is more efficient for communicating natural images across diffident channel.

  19. Use of dust storm observations on satellite images to identify areas vulnerable to severe wind erosion

    Science.gov (United States)

    Breed, C.S.; McCauley, J.F.

    1986-01-01

    Blowing dust is symptomatic of severe wind erosion and deterioration of soils in areas undergoing dessication and/or devegetation. Dust plumes on satellite images can commonly be traced to sources in marginally arable semiarid areas where protective lag gravels or vegetation have been removed and soils are dry, as demonstrated for the Portales Valley, New Mexico. Images from Landsat and manned orbiters such as Skylab and the Space Shuttle are useful for illustrating the regional relations of airborne dust plumes to source areas. Geostationary satellites such as GOES are useful in tracking the time-histories of episodic dust storms. These events sometimes go unrecognized by weather observers and are the precursors of long-term land degradation trends. In areas where soil maps and meteorological data are inadequate, satellite images provide a means for identifying problem areas where measures are needed to control or mitigate wind erosion. ?? 1986 D. Reidel Publishing Company.

  20. Periodic material-based vibration isolation for satellites

    Directory of Open Access Journals (Sweden)

    Xinnan Liu

    2016-01-01

    Full Text Available The vibration environment of a satellite is very severe during launch. Isolating the satellitevibrations during launch will significantly enhance reliability and lifespan, and reduce the weight of satellite structure and manufacturing cost. Guided by the recent advances in solid-state physics research, a new type of satellite vibration isolator is proposed by usingperiodic material that is hence called periodic isolator. The periodic isolator possesses a unique dynamic property, i.e., frequency band gaps. External vibrations with frequencies falling in the frequency band gaps of the periodic isolator are to be isolated. Using the elastodynamics and the Bloch-Floquet theorem, the frequency band gaps of periodic isolators are determined. A parametric study is conducted to provide guidelines for the design of periodic isolators. Based on these analytical results, a finite element model of a micro-satellite with a set of designed periodic isolators is built to show the feasibility of vibration isolation. The periodic isolator is found to be a multi-directional isolator that provides vibration isolation in the three directions.

  1. GPS SATELLITE SIMULATOR SIGNAL ESTIMATION BASED ON ANN

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Multi-channel Global Positioning System (GPS) satellite signal simulator is used to provide realistic test signals for GPS receivers and navigation systems. In this paper, signals arriving the antenna of GPS receiver are analyzed from the viewpoint of simulator design. The estimation methods are focused of which several signal parameters are difficult to determine directly according to existing experiential models due to various error factors. Based on the theory of Artificial Neural Network (ANN), an approach is proposed to simulate signal propagation delay,carrier phase, power, and other parameters using ANN. The architecture of the hardware-in-the-loop test system is given. The ANN training and validation process is described. Experimental results demonstrate that the ANN designed can statistically simulate sample data in high fidelity.Therefore the computation of signal state based on this ANN can meet the design requirement,and can be directly applied to the development of multi-channel GPS satellite signal simulator.

  2. Distributing Digital Imaging and Communications in Medicine data and optimizing access over satellite networks

    OpenAIRE

    Ernst, Randy D.; Kawashima, Akira; Shepherd, William(Santa Cruz Institute for Particle Physics and Department of Physics, Santa Cruz, CA, 95064, U.S.A); Tamm, Eric P.; Sandler, Carl M.

    1999-01-01

    To improve radiology access to full uncompressed Digital Imaging and Communications in Medicine (DICOM) data sets, we evaluated satellite access to a DICOM server. Radiologists′ home computers were connected by satellite to a medweb DICOM server (Medweb, San Francisco, CA). A 10.2-kb data set containing a 19-image head computed tomography (CT) scan was transferred using DirecPC (Hughes Electronics Corp, Arlington, VA) at three different times of the day; 6 AM, 3 PM, and 8 PM. The average tran...

  3. A GPS-Based Attitude Determination System for Small Satellites

    OpenAIRE

    Gershman, Daniel; Young, Kristopher; Kelsey, Anders; Eldad, Ofer; Rostoker, Jason; Mohiuddin, Shan; Cerruti, Alessandro; Peck, Mason

    2006-01-01

    This paper presents a novel, GPS-based attitude determination system (ADS). Carrier-phase differential GPS (CDGPS) accurate to within centimeters enables magnetometer-level pointing accuracy. Employing three GPS antennas allows for the determination of three independent baseline vectors, which can be combined to yield a precise attitude solution. Both simulation data for a satellite in LEO and terrestrial field test data suggest subcentimeter level accuracy, yielding an instantaneous pointing...

  4. Market-based task allocation in distributed satellite systems

    OpenAIRE

    van der Horst, Johannes

    2012-01-01

    This thesis addresses the problem of task allocation in a distributed satellite system. These spacecraft specialise in different functions, and must collaborate to complete the mission objectives. The energy available for task execution and communication is, however, extremely limited, which poses a challenging design problem. I propose the use of a market-based, multi-agent approach to achieve the necessary macro-level behaviour. The development and verification of this allocation mechanism ...

  5. Detecting weather radar clutter using satellite-based nowcasting products

    OpenAIRE

    Jensen, Thomas B. S.; Gill, Rashpal S.; Overgaard, Søren; Hansen, Lars Kai; Nielsen, Allan Aasbjerg

    2006-01-01

    This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expect...

  6. The satellite based augmentation system – EGNOS for non-precision approach global navigation satellite system

    Directory of Open Access Journals (Sweden)

    Andrzej FELLNER

    2012-01-01

    Full Text Available First in the Poland tests of the EGNOS SIS (Signal in Space were conducted on 5th October 2007 on the flight inspection with SPAN (The Synchronized Position Attitude Navigation technology at the Mielec airfield. This was an introduction to a test campaign of the EGNOS-based satellite navigation system for air traffic. The advanced studies will be performed within the framework of the EGNOS-APV project in 2011. The implementation of the EGNOS system to APV-I precision approach operations, is conducted according to ICAO requirements in Annex 10. Definition of usefulness and certification of EGNOS as SBAS (Satellite Based Augmentation System in aviation requires thorough analyses of accuracy, integrity, continuity and availability of SIS. Also, the project will try to exploit the excellent accuracy performance of EGNOS to analyze the implementation of GLS (GNSS Landing System approaches (Cat I-like approached using SBAS, with a decision height of 200 ft. Location of the EGNOS monitoring station Rzeszów, located near Polish-Ukrainian border, being also at the east border of planned EGNOS coverage for ECAC states is very useful for SIS tests in this area. According to current EGNOS programmed schedule, the project activities will be carried out with EGNOS system v2.2, which is the version released for civil aviation certification. Therefore, the project will allow demonstrating the feasibility of the EGNOS certifiable version for civil applications.

  7. Gemini Planet Imager Observational Calibrations VIII: Characterization and Role of Satellite Spots

    CERN Document Server

    Wang, Jason J; Graham, James R; Savransky, Dmitry; Ingraham, Patrick J; Ward-Duong, Kimberly; Patience, Jennifer; De Rosa, Robert J; Bulger, Joanna; Sivaramakrishnan, Anand; Perrin, Marshall D; Thomas, Sandrine J; Sadakuni, Naru; Greenbaum, Alexandra Z; Pueyo, Laurent; Marois, Christian; Oppenheimer, Ben R; Kalas, Paul; Cardwell, Andrew; Goodsell, Stephen; Hibon, Pascale; Rantakyrö, Fredrik T

    2014-01-01

    The Gemini Planet Imager (GPI) combines extreme adaptive optics, an integral field spectrograph, and a high performance coronagraph to directly image extrasolar planets in the near-infrared. Because the coronagraph blocks most of the light from the star, it prevents the properties of the host star from being measured directly. Instead, satellite spots, which are created by diffraction from a square grid in the pupil plane, can be used to locate the star and extract its spectrum. We describe the techniques implemented into the GPI Data Reduction Pipeline to measure the properties of the satellite spots and discuss the precision of the reconstructed astrometry and spectrophotometry of the occulted star. We find the astrometric precision of the satellite spots in an $H$-band datacube to be $0.05$ pixels and is best when individual satellite spots have a signal to noise ratio (SNR) of $> 20$. In regards to satellite spot spectrophotometry, we find that the total flux from the satellite spots is stable to $\\sim 7\\...

  8. A methodology for near real-time change detection between Unmanned Aerial Vehicle and wide area satellite images

    Science.gov (United States)

    Fytsilis, Anastasios L.; Prokos, Anthony; Koutroumbas, Konstantinos D.; Michail, Dimitrios; Kontoes, Charalambos C.

    2016-09-01

    In this paper a novel integrated hybrid methodology for unsupervised change detection between Unmanned Aerial Vehicle (UAV) and satellite images, which can be utilized in various fields like security applications (e.g. border surveillance) and damage assessment, is proposed. This is a challenging problem mainly due to the difference in geographic coverage and the spatial resolution of the two images, as well as to the acquisition modes which lead to misregistration errors. The methodology consists of the following steps: (a) pre-processing, where the part of the satellite image that corresponds to the UAV image is determined and the UAV image is ortho-rectified using information provided by a Digital Terrain Model, (b) the detection of potential changes, which is based exclusively on intensity and image gradient information, (c) the generation of the region map, where homogeneous regions are produced by the previous potential changes via a seeded region growing algorithm and placed on the region map, and (d) the evaluation of the above regions, in order to characterize them as true changes or not. The methodology has been applied on demanding real datasets with very encouraging results. Finally, its robustness to the misregistration errors is assessed via extensive experimentation.

  9. Optimization of post-classification processing of high-resolution satellite image: A case study

    Institute of Scientific and Technical Information of China (English)

    DONG Rencai; DONG Jiajia; WU Gang; DENG Hongbing

    2006-01-01

    The application of remote sensing monitoring techniques plays a crucial role in evaluating and governing the vast amount of ecological construction projects in China. However, extracting information of ecological engineering target through high-resolution satellite image is arduous due to the unique topography and complicated spatial pattern on the Loess Plateau of China. As a result, enhancing classification accuracy is a huge challenge to high-resolution image processing techniques. Image processing techniques have a definitive effect on image properties and the selection of different parameters may change the final classification accuracy during post-classification processing. The common method of eliminating noise and smoothing image is majority filtering. However, the filter function may modify the original classified image and the final accuracy. The aim of this study is to develop an efficient and accurate post-processing technique for acquiring information of soil and water conservation engineering, on the Loess Plateau of China, using SPOT image with 2.5 rn resolution. We argue that it is vital to optimize satellite image filtering parameters for special areas and purposes, which focus on monitoring ecological construction projects. We want to know how image filtering influences final classified results and which filtering kernel is optimum. The study design used a series of window sizes to filter the original classified image, and then assess the accuracy of each output map and image quality. We measured the relationship between filtering window size and classification accuracy, and optimized the post-processing techniques of SPOT5satellite images. We conclude that (1) smoothing with the majority filter is sensitive to the information accuracy of soil and water conservation engineering, and (2) for SPOT5 2.5 m image, the 5×5 pixel majority filter is most suitable kernel for extracting information of ecological construction sites in the Loess Plateau of

  10. Soil moisture and evapotranspiration of wetlands vegetation habitats retrieved from satellite images

    Directory of Open Access Journals (Sweden)

    K. Dabrowska-Zielinska

    2010-08-01

    Full Text Available The research has been carried out in Biebrza Ramsar Convention test site situated in the N-E part of Poland. Data from optical and microwave satellite images have been analysed and compared to the detailed soil-vegetation ground truth measurements conducted during the satellite overpasses. Satellite data applied for the study include: ENVISAT.ASAR, ENVISAT.MERIS, ALOS.PALSAR, ALOS.AVNIR-2, ALOS.PRISM, TERRA.ASTER, and NOAA.AVHRR. Optical images have been used for classification of wetlands vegetation habitats and vegetation surface roughness expressed by LAI. Also, heat fluxes have been calculated using NOAA.AVHRR data and meteorological data. Microwave images have been used for the assessment of soil moisture. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined, and the best combination of microwave variables (wave length, incidence angle, polarization has been used for mapping and monitoring of soil moisture. The results of this study give possibility to improve models of water cycle over wetlands ecosystems by adding information about soil moisture and surface heat fluxes derived from satellite images. Such information is very essential for better protection of the European sensitive wetland ecosystems. ENVISAT and ALOS images have been obtained from ESA for AO ID 122 and AOALO.3742 projects.

  11. Foodstuff survey around a major nuclear facility with test of satellite images application

    International Nuclear Information System (INIS)

    A foodstuff survey was performed around the Savannah River Site, Aiken, South Carolina. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of the Savannah River Site center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined by the usual process of applying county agricultural statistics reported by state agencies. This process was compared to crop analysis of two LANDSAT Thematic Mapper images. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the site and by 16-km distance intervals from 16 km to 80 km. The median areas per section devoted to each of four food crops based on county agricultural statistics were about two-thirds of those based on satellite image analysis. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption

  12. SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

    Science.gov (United States)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

    2016-04-01

    Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

  13. The Matsu Wheel: A Cloud-based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

    CERN Document Server

    Patterson, Maria T; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert; Handy, Matthew; Ly, Vuong; Mandl, Dan; Pederson, Shane; Pivarski, Jim; Powell, Ray; Spring, Jonathan; Wells, Walt

    2016-01-01

    Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for the cloud-based processing of Earth satellite imagery. A particular focus is the development of applications for detecting fires and floods to help support natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce, Storm and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework is designed to be able to support scanning queries using cloud computing applications, such as Hadoop and Accumulo. A scanning query processes all, or most of the data, in a database or data repository. We also descri...

  14. 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

  15. Covariance analysis of differential drag-based satellite cluster flight

    Science.gov (United States)

    Ben-Yaacov, Ohad; Ivantsov, Anatoly; Gurfil, Pini

    2016-06-01

    One possibility for satellite cluster flight is to control relative distances using differential drag. The idea is to increase or decrease the drag acceleration on each satellite by changing its attitude, and use the resulting small differential acceleration as a controller. The most significant advantage of the differential drag concept is that it enables cluster flight without consuming fuel. However, any drag-based control algorithm must cope with significant aerodynamical and mechanical uncertainties. The goal of the current paper is to develop a method for examination of the differential drag-based cluster flight performance in the presence of noise and uncertainties. In particular, the differential drag control law is examined under measurement noise, drag uncertainties, and initial condition-related uncertainties. The method used for uncertainty quantification is the Linear Covariance Analysis, which enables us to propagate the augmented state and filter covariance without propagating the state itself. Validation using a Monte-Carlo simulation is provided. The results show that all uncertainties have relatively small effect on the inter-satellite distance, even in the long term, which validates the robustness of the used differential drag controller.

  16. Efficient Satellite Scheduling Based on Improved Vector Evaluated Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Tengyue Mao

    2012-03-01

    Full Text Available Satellite scheduling is a typical multi-peak, many-valley, nonlinear multi-objective optimization problem. How to effectively implement the satellite scheduling is a crucial research in space areas.This paper mainly discusses the performance of VEGA (Vector Evaluated Genetic Algorithm based on the study of basic principles of VEGA algorithm, algorithm realization and test function, and then improves VEGA algorithm through introducing vector coding, new crossover and mutation operators, new methods to assign fitness and hold good individuals. As a result, the diversity and convergence of improved VEGA algorithm of improved VEGA algorithm have been significantly enhanced and will be applied to Earth-Mars orbit optimization. At the same time, this paper analyzes the results of the improved VEGA, whose results of performance analysis and evaluation show that although VEGA has a profound impact upon multi-objective evolutionary research,  multi-objective evolutionary algorithm on the basis of Pareto seems to be a more effective method to get the non-dominated solutions from the perspective of diversity and convergence of experimental result. Finally, based on Visual C + + integrated development environment, we have implemented improved vector evaluation algorithm in the satellite scheduling.

  17. Chaos Based Secure IP Communications over Satellite DVB

    Science.gov (United States)

    Caragata, Daniel; El Assad, Safwan; Tutanescu, Ion; Sofron, Emil

    2010-06-01

    The Digital Video Broadcasting—Satellite (DVB-S) standard was originally conceived for TV and radio broadcasting. Later, it became possible to send IP packets using encapsulation methods such as Multi Protocol Encapsulation, MPE, or Unidirectional Lightweight Encapsulation, ULE. This paper proposes a chaos based security system for IP communications over DVB-S with ULE encapsulation. The proposed security system satisfies all the security requirements while respecting the characteristics of satellite links, such as the importance of efficient bandwidth utilization and high latency time. It uses chaotic functions to generate the keys and to encrypt the data. The key management is realized using a multi-layer architecture. A theoretical analysis of the system and a simulation of FTP and HTTP traffic are presented and discussed to show the cost of the security enhancement and to provide the necessary tools for security parameters setup.

  18. Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

    Science.gov (United States)

    Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

    2016-06-01

    The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

  19. Development of a Lyman-α Imaging Solar Telescope for the Satellite

    Science.gov (United States)

    Jang, M.; Oh, H.-S.; Rim, C.-S.; Park, J.-S.; Kim, J.-S.; Son, D.

    2005-09-01

    Long term observations of full-disk Lyman-α irradiance have been made by the instruments on various satellites. In addition, several sounding rockets dating back to the 1950s and up through the present have measured the Lyman-α irradiance. Previous full disk Lyman-α images of the sun have been very interesting and useful scientifically, but have been only five-minute ``snapshots" obtained on sounding rocket flights. All of these observations to date have been snapshots, with no time resolution to observe changes in the chromospheric structure as a result of the evolving magnetic field, and its effect on the Lyman-α intensity. The Lyman-α Imaging Solar Telescope(LIST) can provide a unique opportunity for the study of the sun in the Lyman-α region with the high time and spatial resolution for the first time. Up to the 2nd year development, the preliminary design of the optics, mechanical structure and electronics system has been completed. Also the mechanical structure analysis, thermal analysis were performed and the material for the structure was chosen as a result of these analyses. And the test plan and the verification matrix were decided. The operation systems, technical and scientific operation, were studied and finally decided. Those are the technical operation, mechanical working modes for the observation and safety, the scientific operation and the process of the acquired data. The basic techniques acquired through the development of satellite based solar telescope are essential for the construction of space environment forecast system in the future. The techniques which we developed through this study, like mechanical, optical and data processing techniques, could be applied extensively not only to the process of the future production of flight models of this kind, but also to the related industries. Also, we can utilize the scientific achievements which are obtained throughout the project. And these can be utilized to build a high resolution

  20. Estimating Reliability of Disturbances in Satellite Time Series Data Based on Statistical Analysis

    Science.gov (United States)

    Zhou, Z.-G.; Tang, P.; Zhou, M.

    2016-06-01

    Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, deforestation, and plant diseases — occur worldwide at unknown times and locations. Timely detection and characterization of these disturbances is of importance for land cover monitoring. Recently, many time-series-analysis methods have been developed for near real-time or online disturbance detection, using satellite image time series. However, the detection results were only labelled with "Change/ No change" by most of the present methods, while few methods focus on estimating reliability (or confidence level) of the detected disturbances in image time series. To this end, this paper propose a statistical analysis method for estimating reliability of disturbances in new available remote sensing image time series, through analysis of full temporal information laid in time series data. The method consists of three main steps. (1) Segmenting and modelling of historical time series data based on Breaks for Additive Seasonal and Trend (BFAST). (2) Forecasting and detecting disturbances in new time series data. (3) Estimating reliability of each detected disturbance using statistical analysis based on Confidence Interval (CI) and Confidence Levels (CL). The method was validated by estimating reliability of disturbance regions caused by a recent severe flooding occurred around the border of Russia and China. Results demonstrated that the method can estimate reliability of disturbances detected in satellite image with estimation error less than 5% and overall accuracy up to 90%.

  1. Collection of road traffic information from satellite images and digital map

    Science.gov (United States)

    Shinmura, Fumito; Saji, Hitoshi

    2010-10-01

    There have been many reports on the analysis of the Earth's surface by remote sensing. The purpose of this study is to analyze traffic information, and we have been studying methods of collecting traffic information by remote sensing. To collect traffic information, sensors installed on the roadside are frequently used. However, methods using sensors only collect information around the positions of the sensors. In this study, we attempt to solve this problem by using satellite images, which have recently become increasingly available. We propose a method of collecting traffic information over a large area using satellite images as well as three-dimensional digital maps. We assess traffic conditions by computing the number of edges of vehicles per road section as follows. First, the edges of vehicles are detected in satellite images. During this processing, three-dimensional digital maps are used to increase the accuracy of vehicle edge detection. The number of vehicles per road section, which is computed from the number of edges of vehicles, is computed and referred to as the vehicle density. Traffic conditions can be assessed from the vehicle density and are considered useful for collecting information on traffic congestion. In this study, we experimentally confirm that congested roads can be extracted from satellite images by our method.

  2. Georectification and snow classification of webcam images: potential for complementing satellite-derrived snow maps over Switzerland

    Science.gov (United States)

    Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

    2016-04-01

    The spatial and temporal variability of snow cover has a significant impact on climate and environment and is of great socio-economic importance for the European Alps. Satellite remote sensing data is widely used to study snow cover variability and can provide spatially comprehensive information on snow cover extent. However, cloud cover strongly impedes the surface view and hence limits the number of useful snow observations. Outdoor webcam images not only offer unique potential for complementing satellite-derived snow retrieval under cloudy conditions but could also serve as a reference for improved validation of satellite-based approaches. Thousands of webcams are currently connected to the Internet and deliver freely available images with high temporal and spatial resolutions. To exploit the untapped potential of these webcams, a semi-automatic procedure was developed to generate snow cover maps based on webcam images. We used daily webcam images of the Swiss alpine region to apply, improve, and extend existing approaches dealing with the positioning of photographs within a terrain model, appropriate georectification, and the automatic snow classification of such photographs. In this presentation, we provide an overview of the implemented procedure and demonstrate how our registration approach automatically resolves the orientation of a webcam by using a high-resolution digital elevation model and the webcam's position. This allows snow-classified pixels of webcam images to be related to their real-world coordinates. We present several examples of resulting snow cover maps, which have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or not visible from webcams' positions. The procedure is expected to work under almost any weather condition and demonstrates the feasibility of using webcams for the retrieval of high-resolution snow cover information.

  3. Efficient Image Retireval Using Region Based Image Retrieval

    OpenAIRE

    Niket Amoda; Ramesh K Kulkarni

    2013-01-01

    Early image retrieval techniques were based on text ual annotation of images. Manual annotation of images is a burdensome and expensive work for a huge image database. It is often introspective, context-sensitive and crude. Content based image retrieval, is implem ented using the optical constituents of an image such as shape, colour, spatial layout, and texture to ex hibit and index the image. The Region Based Image Retrieval (RBIR) system us...

  4. Imager-to-Radiometer In-flight Cross Calibration: RSP Radiometric Comparison with Airborne and Satellite Sensors

    Science.gov (United States)

    McCorkel, Joel; Cairns, Brian; Wasilewski, Andrzej

    2016-01-01

    This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

  5. 3D modeling of satellite spectral images, radiation budget and energy budget of urban landscapes

    Science.gov (United States)

    Gastellu-Etchegorry, J. P.

    2008-12-01

    DART EB is a model that is being developed for simulating the 3D (3 dimensional) energy budget of urban and natural scenes, possibly with topography and atmosphere. It simulates all non radiative energy mechanisms (heat conduction, turbulent momentum and heat fluxes, water reservoir evolution, etc.). It uses DART model (Discrete Anisotropic Radiative Transfer) for simulating radiative mechanisms: 3D radiative budget of 3D scenes and their remote sensing images expressed in terms of reflectance or brightness temperature values, for any atmosphere, wavelength, sun/view direction, altitude and spatial resolution. It uses an innovative multispectral approach (ray tracing, exact kernel, discrete ordinate techniques) over the whole optical domain. This paper presents two major and recent improvements of DART for adapting it to urban canopies. (1) Simulation of the geometry and optical characteristics of urban elements (houses, etc.). (2) Modeling of thermal infrared emission by vegetation and urban elements. The new DART version was used in the context of the CAPITOUL project. For that, districts of the Toulouse urban data base (Autocad format) were translated into DART scenes. This allowed us to simulate visible, near infrared and thermal infrared satellite images of Toulouse districts. Moreover, the 3D radiation budget was used by DARTEB for simulating the time evolution of a number of geophysical quantities of various surface elements (roads, walls, roofs). Results were successfully compared with ground measurements of the CAPITOUL project.

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

    Science.gov (United States)

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

    2016-06-01

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

  7. Evaluation of satellite based indices for primary production estimates in a sparse savanna in the Sudan

    Directory of Open Access Journals (Sweden)

    M. Sjöström

    2008-07-01

    Full Text Available One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE approach. Satellite indices such as the Enhanced Vegetation Index (EVI and the Shortwave Infrared Water Stress Index (SIWSI have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modelling within a water limited environment. Results show a strong correlation between EVI against gross primary production (GPP, demonstrating the significance of EVI for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modelling in similar semi-arid ecosystems is limited.

  8. The System Overview and Geometric Image Quality of the TH-1 Satellite

    Science.gov (United States)

    Wang, Jianrong; Hu, Xin

    2016-06-01

    The Tian-Hui 1 (TH-1) is the first stereo mapping transmission satellite in China, and the primary mission goal of the satellite is for topographic mapping at 1:50,000 scale without Ground Control Points (GCPs). 1st, 2nd and 3rd satellite of TH-1 was launched on August 24, 2010, May 6, 2012 and October 26, 2015. In TH-1 satellite, many payloads are put on a small satellite platform, which has a low cost. The optical camera of TH-1 includes Line-Matrix CCD (LMCCD) camera, high resolution camera and multispectral camera with 60 km ground swath width. To get high geometric accuracy without GCPs, the on-orbit calibration camera parameters and the Equivalent Frame Photo (EFP) Multi-functional bundle adjustment are proposed and realized in ground image processing of TH-1. In order to evaluate the location accuracy of TH-1, some testing fields are established. All GCPs of testing fields are measured by GPS. The GCPs are not participated the EFP Multi-functional bundle adjustment, and are only as Check Points (CPs) to evaluate the location accuracy. The evaluation of 1st satellite is shown: the horizontal accuracy is 10.3 m (RMSE) and the vertical accuracy is 5.7 m (RMSE) without GCPs, which can satisfy for topographic mapping at 1:50,000 scale. The overviews of TH-1 satellite are described in this paper: First, the system overview is introduced, including mission and optical camera of TH-1. Then, the on-orbit calibration camera parameters using LMCCD image and the EFP Multi-functional bundle adjustment are presented. Finally, the location performance is analysed without GCPs and with different number of GCPs. In addition, the products of TH-1 are introduced.

  9. Satellite-based delivery of educational content to geographically isolated communities: a service based approach

    OpenAIRE

    Serif, Tacha; Ghinea, Gheorghita; Stergioulas, Lampros; Chen, Sherry Y.; Tiropanis, Thanassis; Tsekeridou, Sofia

    2009-01-01

    Enabling learning for members of geographically isolated communities presents benefits in terms of promoting regional development and cost savings for governments and companies. However, notwithstanding recent advances in e-Learning, from both technological and pedagogical perspectives, there are very few, if any, recognised methodologies for user-led design of satellite-based e-learning infrastructures. In this paper, we present a methodology for designing a satellite and wireless based netw...

  10. Study of frontal weather system using satellite images

    International Nuclear Information System (INIS)

    Pakistan which is situated in the south Asian sub continent, has a peculiar climatological position. It is one of the few countries in the world, which undergo a complete transformation from summer to winter season. However this project only pertains to the winter weather conditions in Pakistan. During winter, the land masses cool off rapidly as compared to the seas and so high pressure cells are developed over land causing, weak anti-cyclonic circulation over the country. In between these cells of anti-cyclonic flow of wind, there are zones of convergence, which offer a good breeding place for low-pressure waves. The low-pressure waves are similar to the extra tropical depressions and approach and approach Pakistan from west. From the same reason these are locally called the western Disturbances. Consequently the focus of study is on the extra tropical cyclones which originate along the boundary between polar continental and tropical or polar maritime and tropical maritime air masses. The extra tropical cyclones (also called western disturbances and westerly waves.) which are embedded in westerly flow of air move across north of Pakistan are usually originate from the Mediterranean sea. These systems consist of two types of fronts i.e. warm and cold fronts. In fact these systems can be traced right from the Atlantic Ocean and Mediterranean Sea. The location of frontal weather is generally associated with the surrounding synoptic situation, geographical position of the westerly wave, location of subtropical jet stream, steering wind level etc. although the satellite imageries are quite helpful for forecasting the frontal weather over our region however the weather charts (both surface and upper air ) and jet maps are also very helpful for this purpose

  11. A Simple Fusion Method for Image Time Series Based on the Estimation of Image Temporal Validity

    Directory of Open Access Journals (Sweden)

    Mar Bisquert

    2015-01-01

    Full Text Available High-spatial-resolution satellites usually have the constraint of a low temporal frequency, which leads to long periods without information in cloudy areas. Furthermore, low-spatial-resolution satellites have higher revisit cycles. Combining information from high- and low- spatial-resolution satellites is thought a key factor for studies that require dense time series of high-resolution images, e.g., crop monitoring. There are several fusion methods in the bibliography, but they are time-consuming and complicated to implement. Moreover, the local evaluation of the fused images is rarely analyzed. In this paper, we present a simple and fast fusion method based on a weighted average of two input images (H and L, which are weighted by their temporal validity to the image to be fused. The method was applied to two years (2009–2010 of Landsat and MODIS (MODerate Imaging Spectroradiometer images that were acquired over a cropped area in Brazil. The fusion method was evaluated at global and local scales. The results show that the fused images reproduced reliable crop temporal profiles and correctly delineated the boundaries between two neighboring fields. The greatest advantages of the proposed method are the execution time and ease of use, which allow us to obtain a fused image in less than five minutes.

  12. Development and validation of satellite-based estimates of surface visibility

    Science.gov (United States)

    Brunner, J.; Pierce, R. B.; Lenzen, A.

    2016-02-01

    A satellite-based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5 % for classifying clear (V ≥ 30 km), moderate (10 km ≤ V < 30 km), low (2 km ≤ V < 10 km), and poor (V < 2 km) visibilities and shows the most skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear-sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

  13. An Investigation on Water Quality of Darlik Dam Drinking Water using Satellite Images

    Directory of Open Access Journals (Sweden)

    Erhan Alparslan

    2010-01-01

    Full Text Available Darlik Dam supplies 15% of the water demand of Istanbul Metropolitan City of Turkey. Water quality (WQ in the Darlik Dam was investigated from Landsat 5 TM satellite images of the years 2004, 2005, and 2006 in order to determine land use/land cover changes in the watershed of the dam that may deteriorate its WQ. The images were geometrically and atmospherically corrected for WQ analysis. Next, an investigation was made by multiple regression analysis between the unitless planetary reflectance values of the first four bands of the June 2005 Landsat TM image of the dam and WQ parameters, such as chlorophyll-a, total dissolved matter, turbidity, total phosphorous, and total nitrogen, measured at satellite image acquisition time at seven stations in the dam. Finally, WQ in the dam was studied from satellite images of the years 2004, 2005, and 2006 by pattern recognition techniques in order to determine possible water pollution in the dam. This study was compared to a previous study done by the authors in the Küçükçekmece water reservoir, also in Istanbul City.

  14. The spatial distribution of dust sources in Iraq by using satellite images

    Directory of Open Access Journals (Sweden)

    Kamal H.Lateef, Azhaar K.Mishaal, Ahmed M.Abud

    2015-01-01

    Full Text Available Dust storms phenomenon occurs in the most regions of Iraq during the year, this paper is study this phenomenon by using the technique of satellite images, it has been used satellite images (Meteosat-9 with the sensor (SEVERI and selected different dates of dust storms in 2012, geographic information system programs (ERDAS-GIS has been used to discrimination the regions that cause this phenomena within the study area to prepare the images to read the real geographic coordinates and determines the regions that caused the occurrence of the dust storms represented by geographical location (Lon/Lat and making Iraqi map describes these regions for year 2012 and compared with maps for previous years.

  15. Improving Sediment Transport Prediction by Assimilating Satellite Images in a Tidal Bay Model of Hong Kong

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    2014-03-01

    Full Text Available Numerical models being one of the major tools for sediment dynamic studies in complex coastal waters are now benefitting from remote sensing images that are easily available for model inputs. The present study explored various methods of integrating remote sensing ocean color data into a numerical model to improve sediment transport prediction in a tide-dominated bay in Hong Kong, Deep Bay. Two sea surface sediment datasets delineated from satellite images from the Moderate Resolution Imaging Spectra-radiometer (MODIS were assimilated into a coastal ocean model of the bay for one tidal cycle. It was found that remote sensing sediment information enhanced the sediment transport model ability by validating the model results with in situ measurements. Model results showed that root mean square errors of forecast sediment both at the surface layer and the vertical layers from the model with satellite sediment assimilation are reduced by at least 36% over the model without assimilation.

  16. An objective method for computing advective surface velocities from sequential infrared satellite images

    Science.gov (United States)

    Emery, W. J.; Thomas, A. C.; Collins, M. J.; Crawford, W. R.; Mackas, D. L.

    1986-11-01

    Using cross correlations between sequential infrared satellite images, an objective technique is developed to compute advective sea surface velocities. Cross correlations are computed in 32 × 32 pixel search (second image) and 22 × 22 template (first image) windows from gradients of sea surface temperature computed from the satellite images. Velocity vectors, computed from sequential images of the British Columbia coastal ocean, generally appear coherent and consistent with the seasonal surface current in the region. During periods of strong wind forcing, as indicated by maps of sea level pressure, the image advective velocities are stronger and more coherent spatially and appear to cross surface temperature gradients; when winds are weaker, the advective velocities correspond better with the infrared temperature patterns, suggesting the increased contribution of the geostrophic current to the surface flow. Velocities determined from coincident, near-surface drogued (5-10 m) buoys, positioned every half hour by internal LORAN-C units in mid-June, show excellent agreement with the image advective velocities. In addition, conductivity, temperature, and depth (CTD) measurements (taken during the buoy tracking) confirm the homogeneity of the upper 10 m, and CTD-derived geostrophic currents are consistent with both buoy and sequential image displacement velocities.

  17. Analysis and Assessment of Land Use Change in Alexandria, Egypt Using Satellite Images, GIS, and Modelling Techniques

    International Nuclear Information System (INIS)

    Alexandria is the second largest urban governorate in Egypt and has seen significant urban growth in its modern and contemporary history. This study investigates the urban growth phenomenon in Alexandria, Egypt, using the integration of remote sensing and GIS. The urban physical expansion and change were detected using Landsat satellite images. The satellite images of years 1984 and 1993 were first geo referenced, achieving a very small RMSE that provided high accuracy data for satellite image analysis. Then, the images were classified using a tailored classification scheme with accuracy of 93.82% and 95.27% for 1984 and 1993 images respectively. This high accuracy enabled detecting land use/land cover changes with high confidence using a post-classification comparison method. One of the most important findings here is the loss of cultivated land in favour of urban expansion. If the current loss rates continued, 75% of green lands would be lost by year 2191. These hazardous rates call for an urban growth management policy that can preserve such valuable resources to achieve sustainable urban development. Modelling techniques can help in defining the scenarios of urban growth. In this study, the SLEUTH urban growth model was applied to predict future urban expansion in Alexandria until the year 2055. The application of this model in Alexandria of Egypt with its different environmental characteristics is the first application outside USA and Europe. The results revealed that future urban growth would continue along the edges of the current urban extent. This means that the cultivated lands in the east and the southeast of the city will be decreased. To deal with such crisis, there is a serious need for a comprehensive urban growth management programme that can be based on the best practices in similar situations

  18. Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China

    Directory of Open Access Journals (Sweden)

    Shanyu Huang

    2015-08-01

    Full Text Available Rice farming in Northeast China is crucially important for China’s food security and sustainable development. A key challenge is how to optimize nitrogen (N management to ensure high yield production while improving N use efficiency and protecting the environment. Handheld chlorophyll meter (CM and active crop canopy sensors have been used to improve rice N management in this region. However, these technologies are still time consuming for large-scale applications. Satellite remote sensing provides a promising technology for large-scale crop growth monitoring and precision management. The objective of this study was to evaluate the potential of using FORMOSAT-2 satellite images to diagnose rice N status for guiding topdressing N application at the stem elongation stage in Northeast China. Five farmers’ fields (three in 2011 and two in 2012 were selected from the Qixing Farm in Heilongjiang Province of Northeast China. FORMOSAT-2 satellite images were collected in late June. Simultaneously, 92 field samples were collected and six agronomic variables, including aboveground biomass, leaf area index (LAI, plant N concentration (PNC, plant N uptake (PNU, CM readings and N nutrition index (NNI defined as the ratio of actual PNC and critical PNC, were determined. Based on the FORMOSAT-2 imagery, a total of 50 vegetation indices (VIs were computed and correlated with the field-based agronomic variables. Results indicated that 45% of NNI variability could be explained using Ratio Vegetation Index 3 (RVI3 directly across years. A more practical and promising approach was proposed by using satellite remote sensing to estimate aboveground biomass and PNU at the panicle initiation stage and then using these two variables to estimate NNI indirectly (R2 = 0.52 across years. Further, the difference between the estimated PNU and the critical PNU can be used to guide the topdressing N application rate adjustments.

  19. Development of a satellite-based nowcasting system for surface solar radiation

    Science.gov (United States)

    Limbach, Sebastian; Hungershoefer, Katja; Müller, Richard; Trentmann, Jörg; Asmus, Jörg; Schömer, Elmar; Groß, André

    2014-05-01

    The goal of the RadNowCast project was the development of a tool-chain for a satellite-based nowcasting of the all sky global and direct surface solar radiation. One important application of such short-term forecasts is the computation of the expected energy yield of photovoltaic systems. This information is of great importance for an efficient balancing of power generation and consumption in large, decentralized power grids. Our nowcasting approach is based on an optical-flow analysis of a series of Meteosat SEVIRI satellite images. For this, we extended and combined several existing software tools and set up a series of benchmarks for determining the optimal forecasting parameters. The first step in our processing-chain is the determination of the cloud albedo from the HRV (High Resolution Visible)-satellite images using a Heliosat-type method. The actual nowcasting is then performed by a commercial software system in two steps: First, vector fields characterizing the movement of the clouds are derived from the cloud albedo data from the previous 15 min to 2 hours. Next, these vector fields are combined with the most recent cloud albedo data in order to extrapolate the cloud albedo in the near future. In the last step of the processing, the Gnu-Magic software is used to calculate the global and direct solar radiation based on the forecasted cloud albedo data. For an evaluation of the strengths and weaknesses of our nowcastig system, we analyzed four different benchmarks, each of which covered different weather conditions. We compared the forecasted data with radiation data derived from the real satellite images of the corresponding time steps. The impact of different parameters on the cloud albedo nowcasting and the surface radiation computation has been analysed. Additionally, we could show that our cloud-albedo-based forecasts outperform forecasts based on the original HRV images. Possible future extension are the incorporation of additional data sources, for

  20. Technology Status of HNF-based Monopropellants for Satellite Propulsion

    Science.gov (United States)

    Marée, A. G. M.; Moerel, J.-L.; Welland-Veltmans, W.; Wierckx, F.; Zevenbergen, J.

    2004-10-01

    This paper reports on significant technological progress made over the last few years in determining the feasibility of HNF-based monopropellants. An HNF- based monopropellant is an interesting alternative for hydrazine as monopropellant for satellite propulsion. New non-toxic monopropellants based on dissolved energetic oxidizer salts (e.g. HNF, HAN and ADN) have better performance, lower toxicity and higher storage density than hydrazine. New HNF-monopropellant blends will be presented which have a 5% and 10% higher performance than hydrazine at minimum storage temperatures of 0 and 10 degrees Celsius respectively. This is a major improvement compared with earlier HNF monopropellant blends with a performance equal to hydrazine which must be stored at a minimum temperature of 20 degrees Celsius. Furthermore, these blends are characterized by very low vapour pressures, which is beneficial for two reasons: very low risk of inhalation of harmful vapours and in case of spillage during handling or transport there will be a very low risk of crystallization of solid HNF-crystals. These new blends will be submitted to an extensive characterization program this year. This will include determination of physical properties (e.g. density and viscosity), explosion sensitivity and compatibility with common materials of satellite propulsion systems. Also catalytic ignition and production methods will be demonstrated this year.

  1. Field survey report and satellite image interpretation of the 2013 Super Typhoon Haiyan in the Philippines

    Science.gov (United States)

    Mas, E.; Bricker, J.; Kure, S.; Adriano, B.; Yi, C.; Suppasri, A.; Koshimura, S.

    2015-04-01

    Three weeks after the deadly Bohol earthquake of Mw 7.2, which claimed at least 222 victims, another disaster struck the Philippines. This time, Super Typhoon Haiyan, also known as Typhoon Yolanda in the Philippines, devastated the Eastern Visayas islands on 8 November 2013. Its classification as a super typhoon was based on its maximum sustained 1 min surface wind speed of 315 km h-1, which is equivalent to a strong Category 5 hurricane on the Saffir-Simpson scale. This was one of the deadliest typhoon events in the Philippines' history, after the 1897 and 1912 tropical cyclones. At least 6268 individuals have been reported dead and 1061 people are missing. In addition, a wide area of destruction was observed in the Eastern Visayas, on Samar and Leyte islands. The International Research Institute of Disaster Science (IRIDeS) at Tohoku University in Sendai, Japan, has deployed several teams for damage recognition, relief support and collaboration with regard to this disaster event. One of the teams, the hazard and damage evaluation team, visited the affected areas in the Eastern Visayas in mid-January 2014. In this paper, we summarize the rapid damage assessment from satellite imagery conducted days after the event and report on the inundation measurements and the damage surveyed in the field. Damage interpretation results by satellite images were qualitatively confirmed for the Tacloban city area on Leyte Island, the most populated city in the Eastern Visayas. During the survey, significant damage was observed from wind and storm surges on poorly designed housing on the east coast of Leyte Island. Damage, mainly from surface waves and winds, was observed on the east coast of Samar Island.

  2. Processing Satellite Images on Tertiary Storage: A Study of the Impact of Tile Size on Performance

    Science.gov (United States)

    Yu, JieBing; DeWitt, David J.

    1996-01-01

    Before raw data from a satellite can be used by an Earth scientist, it must first undergo a number of processing steps including basic processing, cleansing, and geo-registration. Processing actually expands the volume of data collected by a factor of 2 or 3 and the original data is never deleted. Thus processing and storage requirements can exceed 2 terrabytes/day. Once processed data is ready for analysis, a series of algorithms (typically developed by the Earth scientists) is applied to a large number of images in a data set. The focus of this paper is how best to handle such images stored on tape using the following assumptions: (1) all images of interest to a scientist are stored on a single tape, (2) images are accessed and processed in the order that they are stored on tape, and (3) the analysis requires access to only a portion of each image and not the entire image.

  3. Imaging based refractometers

    Energy Technology Data Exchange (ETDEWEB)

    Baba, Justin S.

    2015-11-24

    Refractometers for simultaneously measuring refractive index of a sample over a range or wavelengths of light include dispersive and focusing optical systems. An optical beam including the rang of wavelengths is spectrally spread along a first axis and focused along a second axis so as to be incident to an interface between the sample and a prism at a range of angles of incidence including a critical angle for at least one wavelength. In some cases, the prism can have a triangle, parallelogram, trapezoid, or other shape. In some cases, the optical beam can be reflected off of multiple interfaces between the prism and the sample. An imaging detector is situated to receive the spectrally spread and focused light from the interface and form an image corresponding to angle of incidence as a function of wavelength. One or more critical angles are indentified and corresponding refractive indices are determined.

  4. AUTOMATIC ROAD EXTRACTION FROM SATELLITE IMAGES USING EXTENDED KALMAN FILTERING AND EFFICIENT PARTICLE FILTERING

    Directory of Open Access Journals (Sweden)

    Jenita Subash

    2011-12-01

    Full Text Available Users of geospatial data in government, military, industry, research, and other sectors have need foraccurate display of roads and other terrain information in areas where there are ongoing operations orlocations of interest. Hence, road extraction that is significantly more automated than the employment ofcostly and scarce human resources has become a challenging technical issue for the geospatialcommunity. An automatic road extraction based on Extended Kalman Filtering (EKF and variablestructured multiple model particle filter (VS-MMPF from satellite images is addressed. EKF traces themedian axis of a single road segment while VS-MMPF traces all road branches initializing at theintersection. In case of Local Linearization Particle filter (LLPF, a large number of particles are usedand therefore high computational expense is usually required in order to attain certain accuracy androbustness. The basic idea is to reduce the whole sampling space of the multiple model system to the modesubspace by marginalization over the target subspace and choose better importance function for modestate sampling. The core of the system is based on profile matching. During the estimation, new referenceprofiles were generated and stored in the road template memory for future correlation analysis, thuscovering the space of road profiles. .

  5. Reconstruction of incomplete satellite SST data sets based on EOF method

    Institute of Scientific and Technical Information of China (English)

    DING Youzhuan; WEI Zhihui; MAO Zhihua; WANG Xiaofei; PAN Delu

    2009-01-01

    As for the satellite remote sensing data obtained by the visible and infrared bands inversion, the clouds coverage in the sky over the ocean often results in missing data of inversion products on a large scale, and thin clouds difficult to be detected would cause the data of the inversion products to be abnormal. Alvera et al.(2005) proposed a method for the reconstruction of missing data based on an Empirical Orthogonal Functions (EOF) decomposition, but his method couldn't process these images presenting extreme cloud coverage(more than 95%), and required a long time for reconstruction. Besides, the abnormal data in the images had a great effect on the reconstruction result.Therefore, this paper tries to improve the study result. It has reconstructed missing data sets by twice applying EOF decomposition method. Firstly, the abnormity time has been detected by analyzing the temporal modes of EOF decomposition, and the abnormal data have been eliminated.Secondly, the data sets, excluding the abnormal data, are analyzed by using EOF decomposition,and then the temporal modes undergo a filtering process so as to enhance the ability of reconstructing the images which are of no or just a little data, by using EOF. At last, this method has been applied to a large data set, i.e. 43 Sea Surface Temperature (SST) satellite images of the Changjiang River (Yangtze River) estuary and its adjacent areas, and the total reconstruction root mean square error (RMSE) is 0.82℃. And it has been proved that this improved EOF reconstruction method is robust for reconstructing satellite missing data and unreliable data.

  6. Estimation of PV energy production based on satellite data

    Science.gov (United States)

    Mazurek, G.

    2015-09-01

    Photovoltaic (PV) technology is an attractive source of power for systems without connection to power grid. Because of seasonal variations of solar radiation, design of such a power system requires careful analysis in order to provide required reliability. In this paper we present results of three-year measurements of experimental PV system located in Poland and based on polycrystalline silicon module. Irradiation values calculated from results of ground measurements have been compared with data from solar radiation databases employ calculations from of satellite observations. Good convergence level of both data sources has been shown, especially during summer. When satellite data from the same time period is available, yearly and monthly production of PV energy can be calculated with 2% and 5% accuracy, respectively. However, monthly production during winter seems to be overestimated, especially in January. Results of this work may be helpful in forecasting performance of similar PV systems in Central Europe and allow to make more precise forecasts of PV system performance than based only on tables with long time averaged values.

  7. Photography-based image generator

    Science.gov (United States)

    Dalton, Nicholas M.; Deering, Charles S.

    1989-09-01

    A two-channel Photography Based Image Generator system was developed to drive the Helmet Mounted Laser Projector at the Naval Training System Center at Orlando, Florida. This projector is a two-channel system that displays a wide field-of-view color image with a high-resolution inset to efficiently match the pilot's visual capability. The image generator is a derivative of the LTV-developed visual system installed in the A-7E Weapon System Trainer at NAS Cecil Field. The Photography Based Image Generator is based on patented LTV technology for high resolution, multi-channel, real world visual simulation. Special provisions were developed for driving the NTSC-developed and patented Helmet Mounted Laser Projector. These include a special 1023-line raster format, an electronic image blending technique, spherical lens mapping for dome projection, a special computer interface for head/eye tracking and flight parameters, special software, and a number of data bases. Good gaze angle tracking is critical to the use of the NTSC projector in a flight simulation environment. The Photography Based Image Generator provides superior dynamic response by performing a relatively simple perspective transformation on stored, high-detail photography instead of generating this detail by "brute force" computer image generation methods. With this approach, high detail can be displayed and updated at the television field rate (60 Hz).

  8. GPU-based normalized cuts for road extraction using satellite imagery

    Indian Academy of Sciences (India)

    J Senthilnath; S Sindhu; S N Omkar

    2014-12-01

    This paper presents a GPU implementation of normalized cuts for road extraction problem using panchromatic satellite imagery. The roads have been extracted in three stages namely pre-processing, image segmentation and post-processing. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, vegetation, and fallow regions). The road regions are then extracted using the normalized cuts algorithm. Normalized cuts algorithm is a graph-based partitioning approach whose focus lies in extracting the global impression (perceptual grouping) of an image rather than local features. For the segmented image, post-processing is carried out using morphological operations – erosion and dilation. Finally, the road extracted image is overlaid on the original image. Here, a GPGPU (General Purpose Graphical Processing Unit) approach has been adopted to implement the same algorithm on the GPU for fast processing. A performance comparison of this proposed GPU implementation of normalized cuts algorithm with the earlier algorithm (CPU implementation) is presented. From the results, we conclude that the computational improvement in terms of time as the size of image increases for the proposed GPU implementation of normalized cuts. Also, a qualitative and quantitative assessment of the segmentation results has been projected.

  9. Development of a Robotics-based Satellites Docking Simulator

    OpenAIRE

    Zebenay, M.

    2014-01-01

    The European Proximity Operation Simulator (EPOS) is a hardware-in-the-loop (HIL) system aiming, among other objectives, at emulating on-orbit docking of spacecraft for verification and validation of the docking phase. This HIL docking simulator set-up essentially consists of docking interfaces, simulating the servicing satellite called chaser satellite, the serviced satellite called target satellite, a sensor of the forces and torques during contact, and two industrial robots that hold the d...

  10. Medical Image Registration Based Retrieval

    Directory of Open Access Journals (Sweden)

    Swarnambiga AYYACHAMY

    2013-02-01

    Full Text Available This paper presents a quantitative evaluation of state-of-the art intensity based image registration with retrieval methods applied to medical images. The purpose of this study is to access the stability of these methods for medical image analysis. The accuracy of this medical image retrieval with affine based registration and without registration is evaluated using observer study. For retrieval without registration and with registration, we examine the performance of various transform methods for the retrieval of medical images by extracting the features. This helps for the early diagnosis. The technique used for retrieval of medical images were a set of 2-D discrete Fourier transform (DFT, discrete cosine transform (DCT, discrete wavelet transform (DWT, Complex wavelet transform (CWT, and rotated complex wavelet filters (RCWF were implemented and examined for MRI imaging modalities. Especially RCWF gives texture information strongly oriented in six different directions (45° apart from the complex wavelet transform. Experimental results indicate that the DWT method perform well in retrieval of medical images. The method also retains the comparable levels of computational complexity. Then the experimental evaluation is carried by calculating the precision and recall values. It is found that DWT performs well for retrieval without registration and CWT with affine performs well in registration based retrieval with efficiency of 92% from retrieval efficiency 83% of DWT without registration. This helps in classification as before registration and after registration especially for clinical treatment and diagnosis.

  11. Orbital analysis of the inner Uranian satellites from Hubble images

    Science.gov (United States)

    French, Robert S.; Showalter, Mark R.; de Pater, Imke; Lissauer, Jack J.

    2015-11-01

    The thirteen inner moons of Uranus form a densely-packed and possibly chaotic system. Numerical simulations show that several groups of moons exhibit complex resonant interactions, and Mab shows as-yet unexplained variations in its orbit. However, the masses of these moons are currently unknown, limiting the insights that can be gained from numerical simulations. Using over 650 long-exposure images taken during 2003-2013 by the Hubble Space Telescope through broadband filters, we have obtained astrometry for eleven of Uranus’s inner moons, comprising the Portia group (Bianca to Perdita) plus Puck and Mab; attempts to measure the positions of Cordelia and Ophelia are on-going. Using these measurements, which are frequently accurate to 0.05 pixels or less, we have derived Keplerian orbital elements including the influence of Uranus’s oblateness. The elements show year-to-year variations that are statistically significant and indicate the role of mutual perturbations among the moons. We are also using this information to place new constraints on the masses of these moons. We will present our most recent findings.

  12. Detector Based Radio Tomographic Imaging

    OpenAIRE

    Yiğitler, Hüseyin; Jäntti, Riku; Kaltiokallio, Ossi; Patwari, Neal

    2016-01-01

    Received signal strength based radio tomographic imaging is a popular device-free indoor localization method which reconstructs the spatial loss field of the environment using measurements from a dense wireless network. Existing methods solve an associated inverse problem using algebraic or compressed sensing reconstruction algorithms. We propose an alternative imaging method that reconstructs spatial field of occupancy using a back-projection based reconstruction algorithm. The introduced sy...

  13. Image Data Bases on Campus.

    Science.gov (United States)

    Kaplan, Reid; Mathieson, Gordon

    1989-01-01

    A description of how image database technology was used to develop two prototypes for academic and administrative applications at Yale University, one using a video data base integration and the other using document-scanning data base technology, is presented. Technical underpinnings for the creation of data bases are described. (Author/MLW)

  14. Application of Multifractal Analysis to Segmentation of Water Bodies in Optical and Synthetic Aperture Radar Satellite Images

    OpenAIRE

    Martin, Victor Manuel San; Figliola, Alejandra

    2016-01-01

    A method for segmenting water bodies in optical and synthetic aperture radar (SAR) satellite images is proposed. It makes use of the textural features of the different regions in the image for segmentation. The method consists in a multiscale analysis of the images, which allows us to study the images regularity both, locally and globally. As results of the analysis, coarse multifractal spectra of studied images and a group of images that associates each position (pixel) with its correspondin...

  15. Visual attention based detection of signs of anthropogenic activities in satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2010-10-13

    With increasing deployment of satellite imaging systems, only a small fraction of collected data can be subject to expert scrutiny. We present and evaluate a two-tier approach to broad area search for signs of anthropogenic activities in high-resolution commercial satellite imagery. The method filters image information using semantically oriented interest points by combining Harris corner detection and spatial pyramid matching. The idea is that anthropogenic structures, such as rooftop outlines, fence corners, road junctions, are locally arranged in specific angular relations to each other. They are often oriented at approximately right angles to each other (which is known as rectilinearity relation). Detecting the rectilinearity provides an opportunity to highlight regions most likely to contain anthropogenic activity. This is followed by supervised classification of regions surrounding the detected corner points as man-made vs. natural scenes. We consider, in particular, a search for anthropogenic activities in uncluttered areas. In this paper, we proposed and evaluated a two-tier approach to broad area search for signs of anthropogenic activities. Results from experiments on high-resolution ({approx}0.6m) commercial satellite image data showed the potential applicability of this approach and its ability of achieving both high precision and recall rates. The main advantage of combining corner-based cueing with general object recognition is that the incorporation of domain specific knowledge even in its more general form, such as presence of comers, provides a useful cue to narrow the focus of search for signs of anthropogenic activities. Combination of comer based cueing with spatial pyramid matching addressed the issue of comer categorization. An important practical issue for further research is optimizing the balance between false positive and false negative rates. While the results presented in the paper are encouraging, the problem of an automated broad area

  16. Land use change analysis of Beykoz-Istanbul by means of satellite images and GIS.

    Science.gov (United States)

    Musaoglu, N; Coskun, M; Kocabas, V

    2005-01-01

    Management and planning of the natural environment requires spatially accurate and timely information on land use patterns. With repetitive satellite coverage, the rapid evolution of computer technology and the integration of satellite and spatial data, the development of land use applications have become ubiquitous. The integration of Remote Sensing (RS) and Geographic Information Systems (GIS) has been widely applied and recognized as a powerful and effective tool in detecting land use change in urban areas. This paper presents the land use change analysis of the Beykoz region, which is the second largest administrative district of Istanbul. Land use changes and their impacts are monitored using Landsat (MSS - TM) and Spot 5 satellite data in the period of 1975-2001. The independent classification of each satellite image was used as a change analysis method and the resulting images were analyzed with GIS techniques. The results showed that forest area of Beykoz decreased from 80.55% to 70.5% between 1975 and 1984 and during the 1984-2001 periods, the forested area decreased from 70.5% to 68.86% and the urban growth rate was 4.65%. PMID:16114639

  17. Evaluation of cloud base height measurements from ceilometer CL31 and MODIS satellite over Ahmedabad, India

    Directory of Open Access Journals (Sweden)

    S. Sharma

    2015-11-01

    Full Text Available Clouds play a tangible role in the Earth's atmosphere and in particular, the cloud base height (CBH which is linked to cloud type is one of the important characteristic to describe the influence of clouds on the environment. In present study, CBH observations from ceilometer CL31 have been extensively studied during May 2013 to January 2015 over Ahmedabad (23.03° N, 72.54° E, India. A detail comparison has been performed with the use of ground-based CBH measurements from ceilometer CL31 and CBH retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer onboard Aqua and Terra satellite. Some interesting features of cloud dynamics viz. strong downdraft and updraft have been observed over Ahmedabad which revealed different cloud characteristics during monsoon and post-monsoon periods. CBH shows seasonal variation during Indian summer monsoon and post-monsoon period. Results indicate that ceilometer is one of the excellent instruments to precisely detect low and mid-level clouds and MODIS satellite provides accurate retrieval of high-level clouds over this region. The CBH algorithm used for MODIS satellite is also able to capture the low-level clouds.

  18. Evaluation of cloud base height measurements from Ceilometer CL31 and MODIS satellite over Ahmedabad, India

    Science.gov (United States)

    Sharma, Som; Vaishnav, Rajesh; Shukla, Munn V.; Kumar, Prashant; Kumar, Prateek; Thapliyal, Pradeep K.; Lal, Shyam; Acharya, Yashwant B.

    2016-02-01

    Clouds play a tangible role in the Earth's atmosphere and in particular, the cloud base height (CBH), which is linked to cloud type, is one of the most important characteristics to describe the influence of clouds on the environment. In the present study, CBH observations from Ceilometer CL31 were extensively studied during May 2013 to January 2015 over Ahmedabad (23.03° N, 72.54° E), India. A detailed comparison has been performed with the use of ground-based CBH measurements from Ceilometer CL31 and CBH retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard Aqua and Terra satellite. CBH retrieved from MODIS is ˜ 1.955 and ˜ 1.093 km on 25 July 2014 and 1 January 2015 respectively, which matches well with ceilometer-measured CBH ( ˜ 1.92 and ˜ 1.097 km). Some interesting features of cloud dynamics viz. strong downdraft and updraft have been observed over Ahmedabad which revealed different cloud characteristics during monsoon and post-monsoon periods. CBH shows seasonal variation during the Indian summer monsoon and post-monsoon period. Results indicate that the ceilometer is an excellent instrument to precisely detect low- and mid-level clouds, and the MODIS satellite provides accurate retrieval of high-level clouds over this region. The CBH algorithm used for the MODIS satellite is also able to capture the low-level clouds.

  19. Spatial scales of pollution from variable resolution satellite imaging

    International Nuclear Information System (INIS)

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM2.5 levels and wind speed. - Highlights: ► The correlation between PM2.5 and AOD decreases as AOD resolution is degraded. ► High resolution MAIAC AOD 1 km retrieval can be used to investigate within-city PM2.5 variability. ► Low pollution days exhibit higher spatial variability of AOD and PM2.5 then moderate pollution days. ► AOD spatial variability within urban area is higher during the lower wind speed conditions. - The correlation between PM2.5 and AOD decreases as AOD resolution is degraded. The new high-resolution MAIAC AOD retrieval has the potential to capture PM2.5 variability at the intra-urban scale.

  20. Planning for a data base system to support satellite conceptual design

    Science.gov (United States)

    Claydon, C. R.

    1976-01-01

    The conceptual design of an automated satellite design data base system is presented. The satellite catalog in the system includes data for all earth orbital satellites funded to the hardware stage for launch between 1970 and 1980, and provides a concise compilation of satellite capabilities and design parameters. The cost of satellite subsystems and components will be added to the base. Data elements are listed and discussed. Sensor and science and applications opportunities catalogs will be included in the data system. Capabilities of the BASIS storage, retrieval, and analysis system are used in the system design.

  1. Internet-Based Laboratory Activities Designed for Studying the Sun with Satellites

    Science.gov (United States)

    Slater, T. F.

    1998-12-01

    Yohkoh Public Outreach Project (YPOP) is a collaborative industry, university, and K-16 project bringing fascinating and dynamic images of the Sun to the public in real-time. Partners have developed an extensive public access and educational WWW site containing more than 100 pages of vibrant images with current information that focuses on movies of the X-ray output of our Sun taken by the Yohkoh Satellite. More than 5 Gb of images and movies are available on the WWW site from the Yohkoh satellite, a joint project of the Institute for Space and Astronautical Sciences (ISAS) and NASA. Using a movie theater motif, the site was created by teams working at Lockheed Martin Advanced Technology Center, Palo Alto, CA in the Solar and Astrophysics Research Group, the Montana State University Solar Physics Research Group, and the Montana State University Conceptual Astronomy and Physics Education Research Group with funding from the NASA Learning Technology Project (LTP) program (NASA LTP SK30G4410R). The Yohkoh Movie Theater Internet Site is found at URL: http://www.lmsal.com/YPOP/ and mirrored at URL: http://solar.physics.montana.edu/YPOP/. In addition to being able to request automated movies for any dates in a 5 Gb on-line database, the user can view automatically updated daily images and movies of our Sun over the last 72 hours. Master science teachers working with the NASA funded Yohkoh Public Outreach Project have developed nine technology-based on-line lessons for K-16 classrooms. These interdisciplinary science, mathematics, and technology lessons integrate Internet resources, real-time images of the Sun, and extensive NASA image databases. Instructors are able to freely access each of the classroom-ready activities. The activities require students to use scientific inquiry skills and manage electronic information to solve problems consistent with the emphasis of the NRC National Science Education Standards.

  2. Content based Image Retrieval from Forensic Image Databases

    OpenAIRE

    Swati A. Gulhane; Dr. Ajay. A. Gurjar

    2015-01-01

    Due to the proliferation of video and image data in digital form, Content based Image Retrieval has become a prominent research topic. In forensic sciences, digital data have been widely used such as criminal images, fingerprints, scene images and so on. Therefore, the arrangement of such large image data becomes a big issue such as how to get an interested image fast. There is a great need for developing an efficient technique for finding the images. In order to find an image, im...

  3. Applying Support Vector Machine in classifying satellite images for the assessment of urban sprawl

    Science.gov (United States)

    murgante, Beniamino; Nolè, Gabriele; Lasaponara, Rosa; Lanorte, Antonio; Calamita, Giuseppe

    2013-04-01

    In last decades the spreading of new buildings, road infrastructures and a scattered proliferation of houses in zones outside urban areas, produced a countryside urbanization with no rules, consuming soils and impoverishing the landscape. Such a phenomenon generated a huge environmental impact, diseconomies and a decrease in life quality. This study analyzes processes concerning land use change, paying particular attention to urban sprawl phenomenon. The application is based on the integration of Geographic Information Systems and Remote Sensing adopting open source technologies. The objective is to understand size distribution and dynamic expansion of urban areas in order to define a methodology useful to both identify and monitor the phenomenon. In order to classify "urban" pixels, over time monitoring of settlements spread, understanding trends of artificial territories, classifications of satellite images at different dates have been realized. In order to obtain these classifications, supervised classification algorithms have been adopted. More particularly, Support Vector Machine (SVM) learning algorithm has been applied to multispectral remote data. One of the more interesting features in SVM is the possibility to obtain good results also adopting few classification pixels of training areas. SVM has several interesting features, such as the capacity to obtain good results also adopting few classification pixels of training areas, a high possibility of configuration parameters and the ability to discriminate pixels with similar spectral responses. Multi-temporal ASTER satellite data at medium resolution have been adopted because are very suitable in evaluating such phenomena. The application is based on the integration of Geographic Information Systems and Remote Sensing technologies by means of open source software. Tools adopted in managing and processing data are GRASS GIS, Quantum GIS and R statistical project. The area of interest is located south of Bari

  4. CONTENT BASED BATIK IMAGE RETRIEVAL

    Directory of Open Access Journals (Sweden)

    A. Haris Rangkuti

    2014-01-01

    Full Text Available Content Based Batik Image Retrieval (CBBIR is an area of research that focuses on image processing based on characteristic motifs of batik. Basically the image has a unique batik motif compared with other images. Its uniqueness lies in the characteristics possessed texture and shape, which has a unique and distinct characteristics compared with other image characteristics. To study this batik image must start from a preprocessing stage, in which all its color images must be removed with a grayscale process. Proceed with the feature extraction process taking motifs characteristic of every kind of batik using the method of edge detection. After getting the characteristic motifs seen visually, it will be calculated by using 4 texture characteristic function is the mean, energy, entropy and stadard deviation. Characteristic function will be added as needed. The results of the calculation of characteristic functions will be made more specific using the method of wavelet transform Daubechies type 2 and invariant moment. The result will be the index value of every type of batik. Because each motif there are the same but have different sizes, so any kind of motive would be divided into three sizes: Small, medium and large. The perfomance of Batik Image similarity using this method about 90-92%.

  5. Satellite-rocket docking ring recognition method based on mathematical morphology

    Science.gov (United States)

    Xu, Zhiqiang; Shang, Yang; Ma, Xuan

    2015-10-01

    Satellite-rocket docking ring recognition method based on mathematical morphology is presented in this paper, according to the geometric and grayscale characteristics of the docking ring typical structure. The docking ring used in this paper is a circle with a cross in the middle. Most of spacecrafts are transported into orbit by rocket, and they retain the connection component with the rocket. The tracing spacecraft should capture the target spacecraft first before operating the target spacecraft. The docking ring is one of the typical parts of a spacecraft, and it can be recognized automatically. Thereby we can capture the spacecraft through the information of the docking ring. Firstly a multi-step mathematical morphology processing is applied to the image of the target spacecraft with different structure element, followed by edge detection and line detection, and finally docking ring typical structure is located in the image by relative geometry analysis. The images used in this paper are taken of real satellite in lab. The docking ring can be recognized when the distance between the two spacecraft is different. The results of physical simulation experiment show that the method in this paper can recognize docking ring typical structure accurately when the tracing spacecraft is approaching the target spacecraft.

  6. Do roads cause deforestation? Using satellite images in econometric analysis of land use

    OpenAIRE

    Nelson, Gerald; Hellerstein, Daniel

    1997-01-01

    In this paper we demonstrate how satellite images and other geographic data can be used to predict land use. A cross-section model of land use is estimated with data for a region in central Mexico. Parameters from the model are used to examine the effects of reduced human activity. If variables that proxy human influence are changed to reflect reduced impact, "forest" area increases and "irrigated crop" area is reduced.

  7. Zenith Pass Problem of Inter-satellite Linkage Antenna Based on Program Guidance Method

    Institute of Scientific and Technical Information of China (English)

    Zhai Kun; Yang Di

    2008-01-01

    While adopting an elevation-over-azimuth architecture by an inter-satellite linkage antenna of a user satellite, a zenith pass problem always occurs when the antenna is tracing the tracking and data relay satellite (TDRS). This paper deals with this problem by way of,firstly, introducing movement laws of the inter-satellite linkage to predict the movement of the user satellite antenna followed by analyzing the potential pass moment and the actual one of the zenith pass in detail. A number of specific orbit altitudes for the user satellite that can remove the blindness zone are obtained. Finally, on the base of the predicted results from the movement laws of the inter-satellite linkage, the zenith pass tracing strategies for the user satellite antenna are designed under the program guidance using a trajectory preprocessor. Simulations have confirmed the reasonability and feasibility of the strategies in dealing with the zenith pass problem.

  8. Dynamics of polar boundary of the auroral oval derived from the IMAGE satellite data

    Science.gov (United States)

    Lukianova, R.; Kozlovsky, A.

    2013-01-01

    Based on a new database on positions of the auroral oval boundaries including measurements made by the IMAGE satellite in 2000-2002 with correct determination of the glow boundaries, statistical estimations of the latitudinal position of the polar cap boundary (PCB) are obtained depending on the IMF B y and B z , and the PCB evolution during a magnetic storm is analyzed. At zero IMF in the noon (midnight) sector, PCB is located approximately at 80° (76°) CGMLat. The PCB displacement along the noon-midnight meridian is controlled by the IMF B z , and in the noon (midnight) sector it is equal to 0.45° (0.15°) CGMLat when B z changes by 1 nT. The PCB displacement along the dawn-dusk meridian depends on the IMF B y , and it equals 0.1° CGMLat when B y changes by 1 nT. Accordingly, the north polar cap as a whole is shifted to the dawn (dusk) side at B y > 0 ( B y night boundary requires 25 h or more in order to be shifted to the pole to a latitude corresponding to B z > 0.

  9. Satellite image classification methods and Landsat 5TM bands

    CERN Document Server

    Tamouk, Jamshid; Farmanbar, Mina

    2013-01-01

    This paper attempts to find the most accurate classification method among parallelepiped, minimum distance and chain methods. Moreover, this study also challenges to find the suitable combination of bands, which can lead to better results in case combinations of bands occur. After comparing these three methods, the chain method over perform the other methods with 79% overall accuracy. Hence, it is more accurate than minimum distance with 67% and parallelepiped with 65%. On the other hand, based on bands features, and also by combining several researchers' findings, a table was created which includes the main objects on the land and the suitable combination of the bands for accurately detecting of landcover objects. During this process, it was observed that band 4 (out of 7 bands of Landsat 5TM) is the band, which can be used for increasing the accuracy of the combined bands in detecting objects on the land.

  10. Metadata for Content-Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    Adrian Sterca

    2010-12-01

    Full Text Available This paper presents an image retrieval technique that combines content based image retrieval with pre-computed metadata-based image retrieval. The resulting system will have the advantages of both approaches: the speed/efficiency of metadata-based image retrieval and the accuracy/power of content-based image retrieval.

  11. Metadata for Content-Based Image Retrieval

    OpenAIRE

    Adrian Sterca; Daniela Miron

    2010-01-01

    This paper presents an image retrieval technique that combines content based image retrieval with pre-computed metadata-based image retrieval. The resulting system will have the advantages of both approaches: the speed/efficiency of metadata-based image retrieval and the accuracy/power of content-based image retrieval.

  12. True Color Images of the Earth created with the Geostationary Satellite Instrument MSG SEVIRI

    Science.gov (United States)

    Reuter, Maximilian

    2013-04-01

    One of the most famous pictures ever taken was by the crew of Apollo 17 in 1972, showing our Earth from a distance of about 45000km. This picture was named 'Blue Marble' and it reminds us of the beauty and uniqueness of our home planet. With geostationary satellites, such views of the Earth are possible without the need to have a photographer in space. However, up to the present, the production of such Blue Marble type images from geostationary satellite data has been impaired by the lack of channels in the visible spectral region. A method for the generation of full disk MSG (METEOSAT Second Generation) SEVIRI (Scanning-Enhanced Visible and Infrared Imager) true colour composite images will be presented. The algorithm mainly uses the SEVIRI channels VIS006 (0.6μm), NIR008 (0.8μm) and NIR016 (1.6μm). The lack of information in the blue and green parts of the visible spectrum is compensated by using data from NASA's (National Aeronautics and Space Administration's) Blue Marble next generation (BMNG) project to fill a look-up table (LUT) transforming RGB (red/green/blue) false colour composite images of VIS006/NIR008/NIR016 into true colour images. Tabulated radiative transfer calculations of a pure Rayleigh atmosphere are used to add an impression of Rayleigh scattering towards the sunlit horizon. The resulting images satisfy naive expectations: clouds are white or transparent, vegetated surfaces are greenish, deserts are sandy-coloured, the ocean is dark blue to black and a narrow halo due to Rayleigh scattering is visible at the sunlit horizon. Therefore, such images are easily interpretable also for inexperienced users not familiar with the characteristics of typical MSG false colour composite images. The images can be used for scientific applications to illustrate specific meteorological conditions or for non-scientific purposes, for example, for raising awareness in the public of the Earth's worthiness of protection.

  13. TESIS experiment on XUV imaging spectroscopy of the Sun onboard the CORONAS-PHOTON satellite

    Science.gov (United States)

    Kuzin, S. V.; Zhitnik, I. A.; Bogachev, S. A.; Shestov, S. V.; Bugaenko, O. I.; Suhodrev, N. K.; Pertsov, A. A.; Mitrofanov, A. V.; Ignat'ev, A. P.; Slemzin, V. A.

    We present a brief description of new complex of space telescopes and spectrographs, TESIS, which will be placed aboard the CORONAS-PHOTON satellite. The complex is intended for high-resolution imaging observation of full Sun in the coronal spectral lines and in the spectral lines of the solar transition region. TESIS will be launched at the end of 2007 - early of 2008. About 25 % of the daily TESIS images will be free for use and for downloading from the TESIS data center that is planned to open 2 months before the TESIS launching at http://www.tesis.lebedev.ru

  14. THE NEED OF NESTED GRIDS FOR AERIAL AND SATELLITE IMAGES AND DIGITAL ELEVATION MODELS

    Directory of Open Access Journals (Sweden)

    G. Villa

    2016-06-01

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

  15. Severe thunderstorm activity over Bihar on 21st April, 2015: a simulation study by satellite based Nowcasting technique

    Science.gov (United States)

    Goyal, Suman; Kumar, Ashish; Sangar, Ghansham; Mohapatra, M.

    2016-05-01

    Satellite based Nowcasting technique is customized version of Forecast and Tracking the Evolution of Cloud Clusters (ForTraCC), it uses the extrapolation technique that allows for the tracking of Mesoscale convective systems (MCS) radiative and morphological properties and forecasts the evolution of these properties (based on cloud-top brightness temperature and area of the cloud cluster) up to 360 minutes, using infrared satellite imagery. The Thermal Infrared (TIR) channel of the weather satellite has been broadly used to study the behaviour of the cloud systems associated with deep convection. The main advantage of this approach is that for most of the globe the best statistics can only be obtained from satellite observations. Such a satellite survey would provide the statistics of MCSs covering the range of meteorological conditions needed to generalize the result and on the other hand only satellite observations can cover the very large range of space and time scale. The algorithm script is taken from Brazilian Scientist Dr. Danial Vila and implemented it into the Indian environment and made compatible with INSAT-3D hdf5 data format. For Indian region it utilizes the INSAT-3D satellite data of TIR1 (10.8 μm) channel and creates nowcast. The output is made compatible with GUI based software MIAS by generating the output in hdf5 format for better understanding and analysis of forecast. The main features of this algorithm are detection of Cloud Cluster based on Cloud Top Brightness Temperature (CTBT) and area i.e. ≤235 ºK and ≥2400 km2 respectively. The tracking technique based on MCS overlapping areas in successive images. The script has been automized in Auxiliary Data Processing System (ADPS) and generating the forecast file in every half an hour and convert the output file in geotiff format. The geotiff file is easily converted into KMZ file format using ArcGIS software to overlay it on google map and hosted on the web server.

  16. REVIEW OF PHASE BASED IMAGE MATCHING

    OpenAIRE

    Jaydeep Kale*

    2016-01-01

    This paper review the phase based image matching method. A major approach for image matching is to extract feature vectors corresponding to given images and perform image matching based on some distance metrics. One of the difficult problem with this feature based image matching is that matching performance depends upon many parameters in feature extraction process. So this paper reviews the phase based image matching methods in which 2D DFTs of given images are used to determine resemblance ...

  17. Wavelength conversion based spectral imaging

    DEFF Research Database (Denmark)

    Dam, Jeppe Seidelin

    resolution for this spectral region. Today, an increasing number of applications exists outside the spectral region covered by Si-based devices, e.g. within cleantech, medical or food imaging. We present a technology based on wavelength conversion which will extend the spectral coverage of state of the art...

  18. Parameterization of oceanic whitecap fraction based on satellite observations

    Directory of Open Access Journals (Sweden)

    M. F. M. A. Albert

    2015-08-01

    Full Text Available In this study the utility of satellite-based whitecap fraction (W values for the prediction of sea spray aerosol (SSA emission rates is explored. More specifically, the study is aimed at improving the accuracy of the sea spray source function (SSSF derived by using the whitecap method through the reduction of the uncertainties in the parameterization of W by better accounting for its natural variability. The starting point is a dataset containing W data, together with matching environmental and statistical data, for 2006. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature TB by satellite-borne radiometers at two frequencies (10 and 37 GHz. A global scale assessment of the data set to evaluate the wind speed dependence of W revealed a quadratic correlation between W and U10, as well as a relatively larger spread in the 37 GHz data set. The latter could be attributed to secondary factors affecting W in addition to U10. To better visualize these secondary factors, a regional scale assessment over different seasons was performed. This assessment indicates that the influence of secondary factors on W is for the largest part imbedded in the exponent of the wind speed dependence. Hence no further improvement can be expected by looking at effects of other factors on the variation in W explicitly. From the regional analysis, a new globally applicable quadratic W(U10 parameterization was derived. An intrinsic correlation between W and U10 that could have been introduced while estimating W from TB was determined, evaluated and presumed to lie within the error margins of the newly derived W(U10 parameterization. The satellite-based parameterization was compared to parameterizations from other studies and was applied in a SSSF to estimate the global SSA emission rate. The thus obtained SSA production for 2006 of 4.1 × 1012 kg is within previously reported estimates. While recent studies that account for

  19. Revealing glacier flow and surge dynamics from animated satellite image sequences: examples from the Karakoram

    Science.gov (United States)

    Paul, F.

    2015-04-01

    Although animated images are very popular on the Internet, they have so far found only limited use for glaciological applications. With long time-series of satellite images becoming increasingly available and glaciers being well recognized for their rapid changes and variable flow dynamics, animated sequences of multiple satellite images reveal glacier dynamics in a time-lapse mode, making the otherwise slow changes of glacier movement visible and understandable for a wide public. For this study animated image sequences were created from freely available image quick-looks of orthorectified Landsat scenes for four regions in the central Karakoram mountain range. The animations play automatically in a web-browser and might help to demonstrate glacier flow dynamics for educational purposes. The animations revealed highly complex patterns of glacier flow and surge dynamics over a 15-year time period (1998-2013). In contrast to other regions, surging glaciers in the Karakoram are often small (around 10 km2), steep, debris free, and advance for several years at comparably low annual rates (a few hundred m a-1). The advance periods of individual glaciers are generally out of phase, indicating a limited climatic control on their dynamics. On the other hand, nearly all other glaciers in the region are either stable or slightly advancing, indicating balanced or even positive mass budgets over the past few years to decades.

  20. a New Algorithm for Void Filling in a Dsm from Stereo Satellite Images in Urban Areas

    Science.gov (United States)

    Gharib Bafghi, Z.; Tian, J.; d'Angelo, P.; Reinartz, P.

    2016-06-01

    Digital Surface Models (DSM) derived from stereo-pair satellite images are the main sources for many Geo-Informatics applications like 3D change detection, object classification and recognition. However since occlusion especially in urban scenes result in some deficiencies in the stereo matching phase, these DSMs contain some voids. In order to fill the voids a range of algorithms have been proposed, mainly including interpolation alone or along with auxiliary DSM. In this paper an algorithm for void filling in DSM from stereo satellite images has been developed. Unlike common previous approaches we didn't use any external DSM to fill the voids. Our proposed algorithm uses only the original images and the unfilled DSM itself. First a neighborhood around every void in the unfilled DSM and its corresponding area in multispectral image is defined. Then it is analysed to extract both spectral and geometric texture and accordingly to assign labels to each cell in the voids. This step contains three phases comprising shadow detection, height thresholding and image segmentation. Thus every cell in void has a label and is filled by the median value of its co-labelled neighbors. The results for datasets from WorldView-2 and IKONOS are shown and discussed.

  1. Evaluation of influences of frequency and amplitude on image degradation caused by satellite vibrations

    Science.gov (United States)

    Nan, Yi-Bing; Tang, Yi; Zhang, Li-Jun; Zheng, Cheng; Wang, Jing

    2015-05-01

    Satellite vibrations during exposure will lead to pixel aliasing of remote sensors, resulting in the deterioration of image quality. In this paper, we expose the problem and discuss the characteristics of satellite vibrations, and then present a pixel mixing model. The idea of mean mixing ratio (MMR) is proposed. MMR computations for different frequencies are implemented. In the mixing model, a coefficient matrix is introduced to estimate each mixed pixel. Thus, the simulation of degraded image can be performed when the vibration attitudes are known. The computation of MMR takes into consideration the influences of various frequencies and amplitudes. Therefore, the roles of these parameters played in the degradation progress are identified. Computations show that under the same vibration amplitude, the influence of vibrations fluctuates with the variation of frequency. The fluctuation becomes smaller as the frequency rises. Two kinds of vibration imaging experiments are performed: different amplitudes with the same frequency and different frequencies with the same amplitude. Results are found to be in very good agreement with the theoretical results. MMR has a better description of image quality than modulation transfer function (MTF). The influence of vibrations is determined mainly by the amplitude rather than the frequency. The influence of vibrations on image quality becomes gradually stable with the increase of frequency. Project supported by the National Basic Research Program of China (Grant No. 2013CB329202) and the Basic Industrial Technology Project of China (Grant No. J312012B002).

  2. Using Sentinel-1 and Landsat 8 satellite images to estimate surface soil moisture content.

    Science.gov (United States)

    Mexis, Philippos-Dimitrios; Alexakis, Dimitrios D.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.

    2016-04-01

    Nowadays, the potential for more accurate assessment of Soil Moisture (SM) content exploiting Earth Observation (EO) technology, by exploring the use of synergistic approaches among a variety of EO instruments has emerged. This study is the first to investigate the potential of Synthetic Aperture Radar (SAR) (Sentinel-1) and optical (Landsat 8) images in combination with ground measurements to estimate volumetric SM content in support of water management and agricultural practices. SAR and optical data are downloaded and corrected in terms of atmospheric, geometric and radiometric corrections. SAR images are also corrected in terms of roughness and vegetation with the synergistic use of Oh and Topp models using a dataset consisting of backscattering coefficients and corresponding direct measurements of ground parameters (moisture, roughness). Following, various vegetation indices (NDVI, SAVI, MSAVI, EVI, etc.) are estimated to record diachronically the vegetation regime within the study area and as auxiliary data in the final modeling. Furthermore, thermal images from optical data are corrected and incorporated to the overall approach. The basic principle of Thermal InfraRed (TIR) method is that Land Surface Temperature (LST) is sensitive to surface SM content due to its impact on surface heating process (heat capacity and thermal conductivity) under bare soil or sparse vegetation cover conditions. Ground truth data are collected from a Time-domain reflectometer (TRD) gauge network established in western Crete, Greece, during 2015. Sophisticated algorithms based on Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) approaches are used to explore the statistical relationship between backscattering measurements and SM content. Results highlight the potential of SAR and optical satellite images to contribute to effective SM content detection in support of water resources management and precision agriculture. Keywords: Sentinel-1, Landsat 8, Soil

  3. Error analysis of satellite attitude determination using a vision-based approach

    Science.gov (United States)

    Carozza, Ludovico; Bevilacqua, Alessandro

    2013-09-01

    Improvements in communication and processing technologies have opened the doors to exploit on-board cameras to compute objects' spatial attitude using only the visual information from sequences of remote sensed images. The strategies and the algorithmic approach used to extract such information affect the estimation accuracy of the three-axis orientation of the object. This work presents a method for analyzing the most relevant error sources, including numerical ones, possible drift effects and their influence on the overall accuracy, referring to vision-based approaches. The method in particular focuses on the analysis of the image registration algorithm, carried out through on-purpose simulations. The overall accuracy has been assessed on a challenging case study, for which accuracy represents the fundamental requirement. In particular, attitude determination has been analyzed for small satellites, by comparing theoretical findings to metric results from simulations on realistic ground-truth data. Significant laboratory experiments, using a numerical control unit, have further confirmed the outcome. We believe that our analysis approach, as well as our findings in terms of error characterization, can be useful at proof-of-concept design and planning levels, since they emphasize the main sources of error for visual based approaches employed for satellite attitude estimation. Nevertheless, the approach we present is also of general interest for all the affine applicative domains which require an accurate estimation of three-dimensional orientation parameters (i.e., robotics, airborne stabilization).

  4. Cloud invigoration and suppression by aerosols over the tropical region based on satellite observations

    Directory of Open Access Journals (Sweden)

    F. Niu

    2011-02-01

    Full Text Available Aerosols may modify cloud properties and precipitation via a variety of mechanisms with varying and contradicting consequences. Using a large ensemble of satellite data acquired by the Moderate Resolution Imaging Spectroradiometer onboard the Earth Observing System's Aqua platform, the CloudSat cloud profiling radar and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO satellite over the tropical oceans, we identified two distinct responses of clouds and precipitation to increases in aerosol loading. Cloud-top temperatures decrease significantly with increasing aerosol index (AI over oceans and aerosol optical depth (AOT over land for mixed-phase clouds with warm cloud bases; no significant changes were found for liquid clouds. The distinct responses are explained by two mechanisms, namely, the aerosol invigoration effect and the microphysical effect. Aerosols can significantly invigorate convection mainly through ice processes, while precipitation from liquid clouds is suppressed through aerosol microphysical processes. Precipitation rates are found to increase with AI for mixed-phase clouds, but decrease for liquid clouds, suggesting that the dominant effect differs for the two types of clouds. These effects change the overall distribution of precipitation rates, leading to more or heavier rains in dirty environments than in cleaner ones.

  5. SIRF: Simultaneous Satellite Image Registration and Fusion in a Unified Framework.

    Science.gov (United States)

    Chen, Chen; Li, Yeqing; Liu, Wei; Huang, Junzhou

    2015-11-01

    In this paper, we propose a novel method for image fusion with a high-resolution panchromatic image and a low-resolution multispectral (Ms) image at the same geographical location. The fusion is formulated as a convex optimization problem which minimizes a linear combination of a least-squares fitting term and a dynamic gradient sparsity regularizer. The former is to preserve accurate spectral information of the Ms image, while the latter is to keep sharp edges of the high-resolution panchromatic image. We further propose to simultaneously register the two images during the fusing process, which is naturally achieved by virtue of the dynamic gradient sparsity property. An efficient algorithm is then devised to solve the optimization problem, accomplishing a linear computational complexity in the size of the output image in each iteration. We compare our method against six state-of-the-art image fusion methods on Ms image data sets from four satellites. Extensive experimental results demonstrate that the proposed method substantially outperforms the others in terms of both spatial and spectral qualities. We also show that our method can provide high-quality products from coarsely registered real-world IKONOS data sets. Finally, a MATLAB implementation is provided to facilitate future research. PMID:26186776

  6. Automated bias-compensation of rational polynomial coefficients of high resolution satellite imagery based on topographic maps

    Science.gov (United States)

    Oh, Jaehong; Lee, Changno

    2015-02-01

    As the need for efficient methods to accurately update and refine geospatial satellite image databases is increasing, we have proposed the use of 3-dimensional digital maps for the fully-automated RPCs bias compensation of high resolution satellite imagery. The basic idea is that the map features are scaled and aligned to the image features, except for the local shift, through the RPCs-based image projection, and then the shifts are automatically determined over the entire image space by template-based edge matching of the heterogeneous data set. This enables modeling of RPCs bias compensation parameters for accurate georeferencing. The map features are selected based on four suggested rules. Experiments were carried out for three Kompsat-2 images and stereo IKONOS images with 1:5000 scale Korean national topographic maps. Image matching performance is discussed with justification of the parameter selection, and the georeferencing accuracy is analyzed. The experimental results showed the automated approach can achieve one-pixel level of georeferencing accuracy, enabling economical hybrid map creation as well as large scale map updates.

  7. Satellite-based Observation of Arctic River Dynamics

    Science.gov (United States)

    Overeem, I.; Brakenridge, R.; Hudson, B.

    2015-12-01

    One of the indicators of a warming Arctic region is an intensification of the hydrological cycle, with increasing permafrost and glacial melt and possibly more precipitation resulting in higher river runoff. Indeed, a significant increase of nearly 10% in annual river flux has been observed in 13 major rivers throughout the entire Arctic region over the last 30 years. However, direct measurements are extremely sparse for 100's of smaller-scale tundra river systems, as well as for proglacial rivers around the Greenland Ice Sheet margin. Observations at in-situ gauging stations are hampered by seasonal ice coverage, break-up and freeze-up dynamics, unstable banks, and difficult access. To overcome such difficulties, we develop remote-sensing based river discharge measurement techniques using a variety of satellite sensors, including reflectance in the near-infrared band of MODIS, LANDSAT, and brightness temperature from the passive microwave sensors AMSR-E and AMSR-2. We use varying inundation of the river channel and floodplain throughout a season to quantify the changing Arctic river flux. A new approach to detect river ice break up in spring has been developed, and is now undergoing validation. To calibrate the remote sensing signal to daily river discharge, we employ either in-situ short observation records, or a numerical distributed hydrological model driven by daily reanalysis climate data. Quantitative reconstructions of meltwater fluxes in rivers along the Greenland Ice Sheet margin obtained so far show a dampened response of these rivers to Greenland Ice Sheet melt. Techniques are now deployed to map river dynamics along the Chukchi Sea and Beaufort Sea coasts, and show shifts in break-up dynamics and flooding patterns. Once calibrated, satellite-based reconstructions have the potential to lengthen short observational records to a ~15 year timespan.

  8. Concepts for on-board satellite image registration. Volume 2: IAS prototype performance evaluation standard definition. [NEEDS Information Adaptive System

    Science.gov (United States)

    Daluge, D. R.; Ruedger, W. H.

    1981-01-01

    Problems encountered in testing onboard signal processing hardware designed to achieve radiometric and geometric correction of satellite imaging data are considered. These include obtaining representative image and ancillary data for simulation and the transfer and storage of a large quantity of image data at very high speed. The high resolution, high speed preprocessing of LANDSAT-D imagery is considered.

  9. Multifractal analysis of satellite images. (Polish Title: Multifraktalna analiza zobrazowan satelitarnych)

    Science.gov (United States)

    Wawrzaszek, A.; Krupiński, M.; Drzewiecki, W.; Aleksandrowicz, S.

    2015-12-01

    Research presented in this paper is focused on the efficiency assessment of multifractal description as a tool for Image Information Mining. Large datasets of very high spatial resolution satellite images (WorldView-2 and EROS-A) have been analysed. The results have confirmed the superiority of multifractals as global image descriptors in comparison to monofractals. Moreover, their usefulness in image classification by using decision trees classifiers was confirmed, also in comparison with textural features. Filtration process preceding fractal and multifractal features estimations was also proved to improve classification results. Additionally, airborne hyperspectral data have been initially analysed. Fractal dimension shows high potential for the description of hyperspectral data. To summarise all conducted tests indicate the usefulness of multifractal formalism in various aspects of remote sensing. Prepared methodology can be further developed and used for more specific tasks, for example in change detection or in the description of hyperspectal data complexity.

  10. Fovea based image quality assessment

    Science.gov (United States)

    Guo, Anan; Zhao, Debin; Liu, Shaohui; Cao, Guangyao

    2010-07-01

    Humans are the ultimate receivers of the visual information contained in an image, so the reasonable method of image quality assessment (IQA) should follow the properties of the human visual system (HVS). In recent years, IQA methods based on HVS-models are slowly replacing classical schemes, such as mean squared error (MSE) and Peak Signal-to-Noise Ratio (PSNR). IQA-structural similarity (SSIM) regarded as one of the most popular HVS-based methods of full reference IQA has apparent improvements in performance compared with traditional metrics in nature, however, it performs not very well when the images' structure is destroyed seriously or masked by noise. In this paper, a new efficient fovea based structure similarity image quality assessment (FSSIM) is proposed. It enlarges the distortions in the concerned positions adaptively and changes the importances of the three components in SSIM. FSSIM predicts the quality of an image through three steps. First, it computes the luminance, contrast and structure comparison terms; second, it computes the saliency map by extracting the fovea information from the reference image with the features of HVS; third, it pools the above three terms according to the processed saliency map. Finally, a commonly experimental database LIVE IQA is used for evaluating the performance of the FSSIM. Experimental results indicate that the consistency and relevance between FSSIM and mean opinion score (MOS) are both better than SSIM and PSNR clearly.

  11. Categorizing natural disaster damage assessment using satellite-based geospatial techniques

    Science.gov (United States)

    Myint, S.W.; Yuan, M.; Cerveny, R.S.; Giri, C.

    2008-01-01

    Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's C, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.

  12. A PSEUDO RELEVANCE BASED IMAGE RETRIEVAL MODEL

    OpenAIRE

    Kamini Thakur; Preetika Saxena

    2015-01-01

    Image retrieval is the basic requirement, task now a day. Content based image retrieval is the popular image retrieval system by which the target image to be retrieved based on the useful features of the given image. CBIR has an active and fast growing research area in both image processing and data mining. In marine ecosystems the captured images having lower resolution, transformation invariant and translation capabilities. Therefore, accurate image extraction according to the u...

  13. Edge-based correlation image registration for multispectral imaging

    Science.gov (United States)

    Nandy, Prabal

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  14. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  15. ORTHO-RECTIFICATION OF HJ-1A/1B MULTI-SPECTRAL IMAGE BASED ON THE GCP IMAGE DATABASE

    Directory of Open Access Journals (Sweden)

    G. Li

    2012-07-01

    Full Text Available HJ satellite is the abbreviation of the Small Satellite Constellation of Environment and Disaster Monitoring and Forecasting in China, which plays a very important role in forecasting and monitoring the environment problems and natural disasters. The ortho-rectification of HJ images aided by GCP (Ground Control Point image database is presented in this paper. The GCP image database is constructed from historical LandSat-TM images and the GCP chip consists of image and geographic attribute information. Then auto-searching and matching algorithm is introduced and mis-matching elimination method is presented. The imaging model based on collinearity equation and the polynomial description of the attitude and position of scanning line is utilized for ortho-rectification. Four scene images are experimented and compared, and the result demonstrated the feasibility and high efficiency of the whole work flow.

  16. Methodology for the detection of land cover changes in time series of daily satellite images. Application to burned area detection

    Directory of Open Access Journals (Sweden)

    J.A. Moreno-Ruiz

    2014-12-01

    Full Text Available We have developed a methodology for detection of observable phenomena at pixel level over time series of daily satellite images, based on using a Bayesian classifier. This methodology has been applied successfully to detect burned areas in the North American boreal forests using the LTDR dataset. The LTDR dataset represents the longest time series of global daily satellite images with 0.05° (~5 km of spatial resolution. The proposed methodology has several stages: 1 pre-processing daily images to obtain composite images of n days; 2 building of space of statistical variables or attributes to consider; 3 designing an algorithm, by selecting and filtering the training cases; 4 obtaining probability maps related to the considered thematic classes; 5 post-processing to improve the results obtained by applying multiple techniques (filters, ranges, spatial coherence, etc.. The generated results are analyzed using accuracy metrics derived from the error matrix (commission and omission errors, percentage of estimation and using scattering plots against reference data (correlation coefficient and slope of the regression line. The quality of the results obtained improves, in terms of spatial and timing accuracy, to other burned area products that use images of higher spatial resolution (500 m and 1 km, but they are only available after year 2000 as MCD45A1 and BA GEOLAND-2: the total burned area estimation for the study region for the years 2001-2011 was 28.56 millions of ha according to reference data and 12.41, 138.43 and 19.41 millions of ha for the MCD45A1, BA GEOLAND-2 and BA-LTDR burned area products, respectively.

  17. Post Launch Calibration and Testing of the Advanced Baseline Imager on the GOES-R Satellite

    Science.gov (United States)

    Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.

    2016-01-01

    The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United State's National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.

  18. Object-Based Image Compression

    Science.gov (United States)

    Schmalz, Mark S.

    2003-01-01

    Image compression frequently supports reduced storage requirement in a computer system, as well as enhancement of effective channel bandwidth in a communication system, by decreasing the source bit rate through reduction of source redundancy. The majority of image compression techniques emphasize pixel-level operations, such as matching rectangular or elliptical sampling blocks taken from the source data stream, with exemplars stored in a database (e.g., a codebook in vector quantization or VQ). Alternatively, one can represent a source block via transformation, coefficient quantization, and selection of coefficients deemed significant for source content approximation in the decompressed image. This approach, called transform coding (TC), has predominated for several decades in the signal and image processing communities. A further technique that has been employed is the deduction of affine relationships from source properties such as local self-similarity, which supports the construction of adaptive codebooks in a self-VQ paradigm that has been called iterated function systems (IFS). Although VQ, TC, and IFS based compression algorithms have enjoyed varying levels of success for different types of applications, bit rate requirements, and image quality constraints, few of these algorithms examine the higher-level spatial structure of an image, and fewer still exploit this structure to enhance compression ratio. In this paper, we discuss a fourth type of compression algorithm, called object-based compression, which is based on research in joint segmentaton and compression, as well as previous research in the extraction of sketch-like representations from digital imagery. Here, large image regions that correspond to contiguous recognizeable objects or parts of objects are segmented from the source, then represented compactly in the compressed image. Segmentation is facilitated by source properties such as size, shape, texture, statistical properties, and spectral

  19. Fuel type characterization based on coarse resolution MODIS satellite data

    Directory of Open Access Journals (Sweden)

    Lanorte A

    2007-01-01

    Full Text Available Fuel types is one of the most important factors that should be taken into consideration for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. In the present study, forest fuel mapping is considered from a remote sensing perspective. The purpose is to delineate forest types by exploring the use of coarse resolution satellite remote sensing MODIS imagery. In order to ascertain how well MODIS data can provide an exhaustive classification of fuel properties a sample area characterized by mixed vegetation covers and complex topography was analysed. The study area is located in the South of Italy. Fieldwork fuel type recognitions, performed before, after and during the acquisition of remote sensing MODIS data, were used as ground-truth dataset to assess the obtained results. The method comprised the following three steps: (I adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; (II model construction for the spectral characterization and mapping of fuel types based on two different approach, maximum likelihood (ML classification algorithm and spectral Mixture Analysis (MTMF; (III accuracy assessment for the performance evaluation based on the comparison of MODIS-based results with ground-truth. Results from our analyses showed that the use of remotely sensed MODIS data provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 73% for ML classifier and higher than 83% for MTMF.

  20. Fuel type characterization based on coarse resolution MODIS satellite data

    Directory of Open Access Journals (Sweden)

    Lasaponara R

    2008-02-01

    Full Text Available Fuel types is one of the most important factors that should be taken into consideration for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. In the present study, forest fuel mapping is considered from a remote sensing perspective. The purpose is to delineate forest types by exploring the use of coarse resolution satellite remote sensing MODIS imagery. In order to ascertain how well MODIS data can provide an exhaustive classification of fuel properties a sample area characterized by mixed vegetation covers and complex topography was analysed. The study area is located in the South of Italy. Fieldwork fuel type recognitions, performed before, after and during the acquisition of remote sensing MODIS data, were used as ground-truth dataset to assess the obtained results. The method comprised the following three steps: (Iadaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; (II model construction for the spectral characterization and mapping of fuel types based on two different approach, maximum likelihood (ML classification algorithm and spectral Mixture Analysis (MTMF; (III accuracy assessment for the performance evaluation based on the comparison of MODIS-based results with ground-truth. Results from our analyses showed that the use of remotely sensed MODIS data provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 73% for ML classifier and higher than 83% for MTMF.

  1. Three-Axis Satellite Attitude Control Based on Magnetic Torquing

    DEFF Research Database (Denmark)

    Wisniewski, Rafal

    1995-01-01

    Recently small satellite missions have gained considerable interest due to low-cost launch opportunities and technilogical improvement of micro-electronics.......Recently small satellite missions have gained considerable interest due to low-cost launch opportunities and technilogical improvement of micro-electronics....

  2. Solar resources estimation combining digital terrain models and satellite images techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bosch, J.L.; Batlles, F.J. [Universidad de Almeria, Departamento de Fisica Aplicada, Ctra. Sacramento s/n, 04120-Almeria (Spain); Zarzalejo, L.F. [CIEMAT, Departamento de Energia, Madrid (Spain); Lopez, G. [EPS-Universidad de Huelva, Departamento de Ingenieria Electrica y Termica, Huelva (Spain)

    2010-12-15

    One of the most important steps to make use of any renewable energy is to perform an accurate estimation of the resource that has to be exploited. In the designing process of both active and passive solar energy systems, radiation data is required for the site, with proper spatial resolution. Generally, a radiometric stations network is used in this evaluation, but when they are too dispersed or not available for the study area, satellite images can be utilized as indirect solar radiation measurements. Although satellite images cover wide areas with a good acquisition frequency they usually have a poor spatial resolution limited by the size of the image pixel, and irradiation must be interpolated to evaluate solar irradiation at a sub-pixel scale. When pixels are located in flat and homogeneous areas, correlation of solar irradiation is relatively high, and classic interpolation can provide a good estimation. However, in complex topography zones, data interpolation is not adequate and the use of Digital Terrain Model (DTM) information can be helpful. In this work, daily solar irradiation is estimated for a wide mountainous area using a combination of Meteosat satellite images and a DTM, with the advantage of avoiding the necessity of ground measurements. This methodology utilizes a modified Heliosat-2 model, and applies for all sky conditions; it also introduces a horizon calculation of the DTM points and accounts for the effect of snow covers. Model performance has been evaluated against data measured in 12 radiometric stations, with results in terms of the Root Mean Square Error (RMSE) of 10%, and a Mean Bias Error (MBE) of +2%, both expressed as a percentage of the mean value measured. (author)

  3. New perspectives for satellite-based archaeological research in the ancient territory of Hierapolis (Turkey

    Directory of Open Access Journals (Sweden)

    R. Lasaponara

    2008-11-01

    Full Text Available This paper deals with the use of satellite QuickBird images to find traces of past human activity in the ancient territory of Hierapolis (Turkey. This is one of the most important archaeological sites in Turkey, and in 1988 it was inscribed in the UNESCO World Heritage list. Although over the years the archaeological site of Hierapolis has been excavated, restored and well documented, up to now the territory around the ancient urban area is still largely unknown. The current research project, still in progress, aims to search the area neighbouring Hierapolis believed to have been under the control of the city for a long time and, therefore, expected to be very rich in archaeological evidence. In order to investigate a large area around the ancient Hierapolis and discover potential archaeological remains, QuickBird images were adopted.

    Results from satellite-based analysis allowed us to find several unknown rural settlements dating back to early Imperial Roman and the Byzantine age. Two significant test sites were focused on in this paper in order to characterize the different spectral responses observed for different types of archaeological features (shadow and soil marks. Principal Component Analysis and spectral indices were computed to enhance archaeological marks and make identification easier. The capability of the QuickBird data set (panchromatic, multispectral channel, PCA and spectral indices in searching for archaeological marks was assessed in a quantitative way by using a specific indicator.

  4. Object-based locust habitat mapping using high-resolution multispectral satellite data in the southern Aral Sea basin

    Science.gov (United States)

    Navratil, Peter; Wilps, Hans

    2013-01-01

    Three different object-based image classification techniques are applied to high-resolution satellite data for the mapping of the habitats of Asian migratory locust (Locusta migratoria migratoria) in the southern Aral Sea basin, Uzbekistan. A set of panchromatic and multispectral Système Pour l'Observation de la Terre-5 satellite images was spectrally enhanced by normalized difference vegetation index and tasseled cap transformation and segmented into image objects, which were then classified by three different classification approaches: a rule-based hierarchical fuzzy threshold (HFT) classification method was compared to a supervised nearest neighbor classifier and classification tree analysis by the quick, unbiased, efficient statistical trees algorithm. Special emphasis was laid on the discrimination of locust feeding and breeding habitats due to the significance of this discrimination for practical locust control. Field data on vegetation and land cover, collected at the time of satellite image acquisition, was used to evaluate classification accuracy. The results show that a robust HFT classifier outperformed the two automated procedures by 13% overall accuracy. The classification method allowed a reliable discrimination of locust feeding and breeding habitats, which is of significant importance for the application of the resulting data for an economically and environmentally sound control of locust pests because exact spatial knowledge on the habitat types allows a more effective surveying and use of pesticides.

  5. Wavelet Based Image Denoising Technique

    Directory of Open Access Journals (Sweden)

    Sachin D Ruikar

    2011-03-01

    Full Text Available This paper proposes different approaches of wavelet based image denoising methods. The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. Wavelet algorithms are useful tool for signal processing such as image compression and denoising. Multi wavelets can be considered as an extension of scalar wavelets. The main aim is to modify the wavelet coefficients in the new basis, the noise can be removed from the data. In this paper, we extend the existing technique and providing a comprehensive evaluation of the proposed method. Results based on different noise, such as Gaussian, Poisson’s, Salt and Pepper, and Speckle performed in this paper. A signal to noise ratio as a measure of the quality of denoising was preferred.

  6. Featured-Based Algorithm for the Automated Registration of Multisensorial / Multitemporal Oceanographic Satellite Imagery

    OpenAIRE

    Javier Marcello; Francisco Eugenio

    2009-01-01

    Spatial registration of multidate or multisensorial images is required for many applications in remote sensing. Automatic image registration, which has been extensively studied in other areas of image processing, is still a complex problem in the framework of remote sensing. In this work we explore an alternative strategy for a fully automatic and operational registration system capable of registering multitemporal and multisensorial remote sensing satellite images with high accuracy and avoi...

  7. Graph-based Image Inpainting

    OpenAIRE

    Defferrard, Michaël

    2014-01-01

    The project goal was to explore the applications of spectral graph theory to address the inpainting problem of large missing chunks. We used a non-local patch graph representation of the image and proposed a structure detector which leverages the graph representation and influences the fill-order of our exemplar-based algorithm. Our method achieved state-of-the-art performances.

  8. High-resolution satellite image segmentation using Hölder exponents

    Indian Academy of Sciences (India)

    Debasish Chakraborty; Gautam Kumar Sen; Sugata Hazra

    2009-10-01

    Texture in high-resolution satellite images requires substantial amendment in the conventional segmentation algorithms. A measure is proposed to compute the Hölder exponent (HE) to assess the roughness or smoothness around each pixel of the image. The localized singularity information is incorporated in computing the HE. An optimum window size is evaluated so that HE reacts to localized singularity. A two-step iterative procedure for clustering the transformed HE image is adapted to identify the range of HE, densely occupied in the kernel and to partition Hölder exponents into a cluster that matches with the range. Hölder exponent values (noise or not associated with the other cluster) are clubbed to a nearest possible cluster using the local maximum likelihood analysis.

  9. Global root zone storage capacity from satellite-based evaporation

    Science.gov (United States)

    Wang-Erlandsson, Lan; Bastiaanssen, Wim G. M.; Gao, Hongkai; Jägermeyr, Jonas; Senay, Gabriel B.; van Dijk, Albert I. J. M.; Guerschman, Juan P.; Keys, Patrick W.; Gordon, Line J.; Savenije, Hubert H. G.

    2016-04-01

    This study presents an "Earth observation-based" method for estimating root zone storage capacity - a critical, yet uncertain parameter in hydrological and land surface modelling. By assuming that vegetation optimises its root zone storage capacity to bridge critical dry periods, we were able to use state-of-the-art satellite-based evaporation data computed with independent energy balance equations to derive gridded root zone storage capacity at global scale. This approach does not require soil or vegetation information, is model independent, and is in principle scale independent. In contrast to a traditional look-up table approach, our method captures the variability in root zone storage capacity within land cover types, including in rainforests where direct measurements of root depths otherwise are scarce. Implementing the estimated root zone storage capacity in the global hydrological model STEAM (Simple Terrestrial Evaporation to Atmosphere Model) improved evaporation simulation overall, and in particular during the least evaporating months in sub-humid to humid regions with moderate to high seasonality. Our results suggest that several forest types are able to create a large storage to buffer for severe droughts (with a very long return period), in contrast to, for example, savannahs and woody savannahs (medium length return period), as well as grasslands, shrublands, and croplands (very short return period). The presented method to estimate root zone storage capacity eliminates the need for poor resolution soil and rooting depth data that form a limitation for achieving progress in the global land surface modelling community.

  10. A Comparison of Satellite-Based Radar and Passive Microwave Estimates of Global Wilson Current Source

    Science.gov (United States)

    Peterson, M. J.; Deierling, W.; Liu, C.; Mach, D. M.; Kalb, C. P.

    2014-12-01

    A passive microwave algorithm for estimating the electrical footprint of charged clouds has been developed and applied to satellite observations taken by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), which has a domain spanning the entire tropics up to 36 degrees latitude, and compared with lightning-based estimates of global electricity and the Carnegie curve. While these results show considerable agreement with historical observations for convective storms, this method has difficulty characterizing electricity in stratiform clouds and storms at different stages of the convective lifecycle. The algorithm also does not take advantage of the full suite of observations available in the 16-year TRMM dataset, which also includes Precipitation Radar (PR) observations of the structure of storms overflown by the satellite. As a first step towards building an algorithm that can characterize electrical input to the Global Electric Circuit (GEC) from a wide variety of storms across the globe, this study compares passive microwave-based approximations of global electricity with precipitation radar-based approximations in order to determine the relative skill each platform has in describing the "battery" of the GEC and to identify a possible pathway towards a combined metric that can use the strengths of both instruments to better describe electrified clouds.

  11. The Black Sea coastal zone in the high resolution satellite images

    Science.gov (United States)

    Yurovskaya, Maria; Dulov, Vladimir; Kozlov, Igor

    2016-04-01

    Landsat data with spatial resolution of 30-100 m provide the ability of regular monitoring of ocean phenomena with scale of 100-1000 m. Sentinel-1 is equipped with C-band synthetic aperture radar. The images allow recognizing the features that affect either the sea surface roughness, or its color characteristics. The possibilities of using the high spatial resolution satellite data are considered for observation and monitoring of Crimean coastal zone. The analyzed database includes all Landsat-8 (Level 1) multi-channel images from January 2013 to August 2015 and all Sentinel-1 radar images in May-August 2015. The goal of the study is to characterize the descriptiveness of these data for research and monitoring of the Crimean coastal areas. The observed marine effects are reviewed and the physical mechanisms of their signatures in the satellite images are described. The effects associated with the roughness variability are usually manifested in all bands, while the subsurface phenomena are visible only in optical data. Confidently observed structures include internal wave trains, filamentous natural slicks, which reflect the eddy coastal dynamics, traces of moving ships and the oil films referred to anthropogenic pollution of marine environment. The temperature fronts in calm conditions occur due to surfactant accumulation in convergence zone. The features in roughness field can also be manifested in Sentinel-1 data. Subsurface processes observed in Landsat-8 images primarily include transport and distribution of suspended matter as a result of floods and sandy beach erosion. The surfactant always concentrates on the sea surface in contaminated areas, so that these events are also observed in Sentinel-1 images. A search of wastewater discharge manifestations is performed. The investigation provides the basis for further development of approaches to obtain quantitative characteristics of the phenomena themselves. Funding by Russian Science Foundation under grant 15

  12. A Knowledge-Based Simulated Annealing Algorithm to Multiple Satellites Mission Planning Problems

    OpenAIRE

    Da-Wei Jin; Li-Ning Xing

    2013-01-01

    The multiple satellites mission planning is a complex combination optimization problem. A knowledge-based simulated annealing algorithm is proposed to the multiple satellites mission planning problems. The experimental results suggest that the proposed algorithm is effective to the given problem. The knowledge-based simulated annealing method will provide a useful reference for the improvement of existing optimization approaches.

  13. A Miniature-Based Image Retrieval System

    OpenAIRE

    Islam, Md Saiful; Ali, Md. Haider

    2010-01-01

    Due to the rapid development of World Wide Web (WWW) and imaging technology, more and more images are available in the Internet and stored in databases. Searching the related images by the querying image is becoming tedious and difficult. Most of the images on the web are compressed by methods based on discrete cosine transform (DCT) including Joint Photographic Experts Group(JPEG) and H.261. This paper presents an efficient content-based image indexing technique for searching similar images ...

  14. NIR- and SWIR-based on-orbit vicarious calibrations for satellite ocean color sensors.

    Science.gov (United States)

    Wang, Menghua; Shi, Wei; Jiang, Lide; Voss, Kenneth

    2016-09-01

    The near-infrared (NIR) and shortwave infrared (SWIR)-based atmospheric correction algorithms are used in satellite ocean color data processing, with the SWIR-based algorithm particularly useful for turbid coastal and inland waters. In this study, we describe the NIR- and two SWIR-based on-orbit vicarious calibration approaches for satellite ocean color sensors, and compare results from these three on-orbit vicarious calibrations using satellite measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). Vicarious calibration gains for VIIRS spectral bands are derived using the in situ normalized water-leaving radiance nLw(λ) spectra from the Marine Optical Buoy (MOBY) in waters off Hawaii. The SWIR vicarious gains are determined using VIIRS measurements from the South Pacific Gyre region, where waters are the clearest and generally stable. Specifically, vicarious gain sets for VIIRS spectral bands of 410, 443, 486, 551, and 671 nm derived from the NIR method using the NIR 745 and 862 nm bands, the SWIR method using the SWIR 1238 and 1601 nm bands, and the SWIR method using the SWIR 1238 and 2257 nm bands are (0.979954, 0.974892, 0.974685, 0.965832, 0.979042), (0.980344, 0.975344, 0.975357, 0.965531, 0.979518), and (0.980820, 0.975609, 0.975761, 0.965888, 0.978576), respectively. Thus, the NIR-based vicarious calibration gains are consistent with those from the two SWIR-based approaches with discrepancies mostly within ~0.05% from three data processing methods. In addition, the NIR vicarious gains (745 and 862 nm) derived from the two SWIR methods are (0.982065, 1.00001) and (0.981811, 1.00000), respectively, with the difference ~0.03% at the NIR 745 nm band. This is the fundamental basis for the NIR-SWIR combined atmospheric correction algorithm, which has been used to derive improved satellite ocean color products over open oceans and turbid coastal/inland waters. Therefore, a unified

  15. A Hybrid Algorithm for Satellite Data Transmission Schedule Based on Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    LI Yun-feng; WU Xiao-yue

    2008-01-01

    A hybrid scheduling algorithm based on genetic algorithm is proposed in this paper for reconnaissance satellite data transmission. At first, based on description of satellite data transmission request, satellite data transmission task modal and satellite data transmission scheduling problem model are established. Secondly, the conflicts in scheduling are discussed. According to the meaning of possible conflict, the method to divide possible conflict task set is given. Thirdly, a hybrid algorithm which consists of genetic algorithm and heuristic information is presented. The heuristic information comes from two concepts, conflict degree and conflict number. Finally, an example shows the algorithm's feasibility and performance better than other traditional algorithms.

  16. Advancing satellite-based solar power forecasting through integration of infrared channels for automatic detection of coastal marine inversion layer

    Energy Technology Data Exchange (ETDEWEB)

    Kostylev, Vladimir; Kostylev, Andrey; Carter, Chris; Mahoney, Chad; Pavlovski, Alexandre; Daye, Tony [Green Power Labs Inc., Dartmouth, NS (Canada); Cormier, Dallas Eugene; Fotland, Lena [San Diego Gas and Electric Co., San Diego, CA (United States)

    2012-07-01

    The marine atmospheric boundary layer is a layer or cool, moist maritime air with the thickness of a few thousand feet immediately below a temperature inversion. In coastal areas as moist air rises from the ocean surface, it becomes trapped and is often compressed into fog above which a layer of stratus clouds often forms. This phenomenon is common for satellite-based solar radiation monitoring and forecasting. Hour ahead satellite-based solar radiation forecasts are commonly using visible spectrum satellite images, from which it is difficult to automatically differentiate low stratus clouds and fog from high altitude clouds. This provides a challenge for cloud motion tyracking and cloud cover forecasting. San Diego Gas and Electric {sup registered} (SDG and E {sup registered}) Marine Layer Project was undertaken to obtain information for integration with PV forecasts, and to develop a detailed understanding of long-term benefits from forecasting Marine Layer (ML) events and their effects on PV production. In order to establish climatological ML patterns, spatial extent and distribution of marine layer, we analyzed visible and IR spectrum satellite images (GOES WEST) archive for the period of eleven years (2000 - 2010). Historical boundaries of marine layers impact were established based on the cross-classification of visible spectrum (VIS) and infrared (IR) images. This approach is successfully used by us and elsewhere for evaluating cloud albedo in common satellite-based techniques for solar radiation monitoring and forecasting. The approach allows differentiation of cloud cover and helps distinguish low laying fog which is the main consequence of marine layer formation. ML occurrence probability and maximum extent inland was established for each hour and day of the analyzed period and seasonal/patterns were described. SDG and E service area is the most affected region by ML events with highest extent and probability of ML occurrence. Influence of ML was the

  17. Field survey report and satellite image interpretation of the 2013 Super Typhoon Haiyan in the Philippines

    Directory of Open Access Journals (Sweden)

    E. Mas

    2014-05-01

    Full Text Available Three weeks after the deadly Bohol earthquake of magnitude Mw 7.2, which claimed at least 222 victims; another disaster struck the Philippines. This time, Super Typhoon Haiyan, also known as Typhoon Yolanda in the Philippines, devastated the Eastern Visayas islands on 8 November 2013. Its classification as a Super Typhoon was based on its maximum sustained 1 min surface wind speed of 315 km h−1, which is equivalent to a strong Category 5 hurricane on the Saffir–Simpson Scale. This was one of the deadliest typhoon events in the Philippines' history, after the 1897 and 1912 tropical cyclones. At least 6268 individuals have been reported dead and 1061 people are missing. In addition, a wide area of destruction was observed in the Eastern Visayas, on Samar and Leyte Islands. The International Research Institute of Disaster Science (IRIDeS at Tohoku University in Sendai, Japan has deployed several teams for damage recognition, relief support and collaboration with regard to this disaster event. One of the teams, the hazard and damage evaluation team, visited the affected areas in the Eastern Visayas in mid-January 2014. In this paper, we summarize the rapid damage assessment conducted days after the event and report on the inundation measurements and the damage surveyed in the field. Damage interpretation results by satellite images were qualitatively confirmed for the Tacloban city area on Leyte Island, the most populated city in the Eastern Visayas. During the survey, significant damage was observed from wind and storm surges on poorly designed housing on the east coast of Leyte Island. Damage, mainly from surface waves and winds was observed on the east coast of Samar Island.

  18. Testing object oriented techniques for Corine Land Cover classification by satellite images with medium spatial resolution

    Directory of Open Access Journals (Sweden)

    Lamonaca A

    2007-01-01

    Full Text Available This work aims to assess the potential of segmentation and object oriented classification techniques of satellite images with medium spatial resolution, for land use/cover (Corine Land Cover, CLC mapping. The tested procedures are assessed both in term of thematic accuracy and working time, with reference to a study area of about 4000 km2 in central Italy. The automatic procedure is carried out by segmentation of the pan-sharpened image and by subsequent classification using membership and standard nearest neighbour functions. Results are evaluated by sample circular photoplots taken from digital IT2000 orthophotos coverage. In terms of overall accuracy, object oriented classification achieves better results than conventional on screen interpretation. The classification shows difficulties for the identification of the "mixed" classes of CLC nomenclature system; however, even in these cases the object oriented techniques provide higher producer and user accuracy than on screen interpretation. On the whole, since they are able to produce more objective and more accurate cartographic products at similar costs, the application of the tested automatic techniques seems to be preferred to the conventional on screen interpretation for satellite images with medium spatial resolution.

  19. Determination of quasi-static microaccelerations onboard a satellite using video images of moving objects

    Science.gov (United States)

    Levtov, V. L.; Romanov, V. V.; Boguslavsky, A. A.; Sazonov, V. V.; Sokolov, S. M.; Glotov, Yu. N.

    2009-12-01

    A space experiment aimed at determination of quasi-static microaccelerations onboard an artificial satellite of the Earth using video images of the objects executing free motion is considered. The experiment was carried out onboard the Foton M-3 satellite. Several pellets moved in a cubic box fixed on the satellite’s mainframe and having two transparent adjacent walls. Their motion was photographed by a digital video camera. The camera was installed facing one of the transparent walls; a mirror was placed at an angle to another transparent wall. Such an optical system allowed us to have in a single frame two images of the pellets from differing viewpoints. The motion of the pellets was photographed on time intervals lasting 96 s. Pauses between these intervals were also equal to 96 s. A special processing of a separate image allowed us to determine coordinates of the pellet centers in the camera’s coordinate system. The sequence of frames belonging to a continuous interval of photography was processed in the following way. The time dependence of each coordinate of every pellet was approximated by a second degree polynomial using the least squares method. The coefficient of squared time is equal to a half of the corresponding microacceleration component. As has been shown by processing made, the described method of determination of quasi-static microaccelerations turned out to be sufficiently sensitive and accurate.

  20. Detection of High Local Groundwater Inflow to Rock Tunnels using ASTER Satellite Images

    Directory of Open Access Journals (Sweden)

    M. Sharafi

    2013-09-01

    Full Text Available High local groundwater flow into rock tunnels may lead to a potential hazard and is an important factor influencing construction time and costs. Geological features such as fault zones and open fractures can be the source of very high local groundwater inflows. Having a reliable estimation of location groundwater inflows is essential before excavation of tunnels. To reduce the costs and time of field works, remote sensing investigations can be a good solution. The main aim of the present study is to propose a methodology for detecting the geomorphic markers of cuesta in the high local groundwater inflow to Nosoud tunnel using the satellite imagery data. For this purpose, a reflectance image from the ASTER satellite sensor was used. Our Experiments show that cuesta springs, caused by hydraulic fracturing, can be detected using the normalized difference vegetation index (NDVI map, computed on the ASTER image, and analyzing the topographic and morphometric features of the area. Moreover, observations in tunnel excavation stage showed that crossing through open fractures in hard and thick layers is the major cause of water inflow into the tunnel, which corresponds to the surface hydrogeological evidences obtained from the ASTER image.

  1. Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring

    Directory of Open Access Journals (Sweden)

    Pauline Dusseux

    2014-06-01

    Full Text Available The aim of this study was to assess the ability of optical images, SAR (Synthetic Aperture Radar images and the combination of both types of data to discriminate between grasslands and crops in agricultural areas where cloud cover is very high most of the time, which restricts the use of visible and near-infrared satellite data. We compared the performances of variables extracted from four optical and five SAR satellite images with high/very high spatial resolutions acquired during the growing season. A vegetation index, namely the NDVI (Normalized Difference Vegetation Index, and two biophysical variables, the LAI (Leaf Area Index and the fCOVER (fraction of Vegetation Cover were computed using optical time series and polarization (HH, VV, HV, VH. The polarization ratio and polarimetric decomposition (Freeman–Durden and Cloude–Pottier were calculated using SAR time series. Then, variables derived from optical, SAR and both types of remotely-sensed data were successively classified using the Support Vector Machine (SVM technique. The results show that the classification accuracy of SAR variables is higher than those using optical data (0.98 compared to 0.81. They also highlight that the combination of optical and SAR time series data is of prime interest to discriminate grasslands from crops, allowing an improved classification accuracy.

  2. New dynamic routing algorithm based on MANET in LEO/MEO satellite network

    Institute of Scientific and Technical Information of China (English)

    LI Zhe; LI Dong-ni; WANG Guang-xing

    2006-01-01

    The features of low earth orbit/medium earth orbit (LEO/MEO) satellite networks routing algorithm based on inter-satellite link are analyzed and the similarities between satellite networks and mobile Ad Hoc network (MANET) are pointed out.The similar parts in MANET routing protocol are used in the satellite network for reference.A new dynamic routing algorithm based on MANET in LEO/MEO satellite networks,which fits for the LEO/MEO satellite communication system,is proposed.At the same time,the model of the algorithm is simulated and features are analyzed.It is shown that the algorithm has strong adaptability.It can give the network high autonomy,perfect function,low system overhead and great compatibility.

  3. An Algorithm of Inter Satellite Two-Way Time Transfer Based on Mobile Satellite

    OpenAIRE

    Feijiang Huang; Xiaochun Lu; Guangcan Liu; Tao Han; Fang Cheng; Feng Liu

    2013-01-01

    Two-way time transfer is one of the most accurate time synchronization methods applied to spacecrafts and ground stations to carry out time transfer. As this method doesn’t require the knowledge of locations of two satellites in advance and it offsets the negative influence of transmission path and other additional delays, this method has boosted the time synchronization accuracy. However, in the process of time synchronization, this method demands that the aircrafts, who conduct time synchro...

  4. A Novel Sampling Method for Satellite-Based Offshore Wind Resource Estimation

    DEFF Research Database (Denmark)

    Badger, Merete; Badger, Jake; Hasager, Charlotte Bay;

    wind resources. The method is applied within a wind and solar resource assessment study for the United Arab Emirates funded by MASDAR and coordinated by UNEP. Thirty years of NCEP/NCAR reanalysis data are used to define approximately 100 geostrophic wind classes. These wind classes show...... climatologically representative large-scale meteorological conditions for the region of interest. The wind classes are used to make the most representative selection of satellite images from the ENVISAT image catalogue. A minimum of one satellite image is chosen per wind class. The frequency of occurrence of each...

  5. Image Retrieval Based on Fractal Dictionary Parameters

    OpenAIRE

    Yuanyuan Sun; Rudan Xu; Lina Chen; Xiaopeng Hu

    2013-01-01

    Content-based image retrieval is a branch of computer vision. It is important for efficient management of a visual database. In most cases, image retrieval is based on image compression. In this paper, we use a fractal dictionary to encode images. Based on this technique, we propose a set of statistical indices for efficient image retrieval. Experimental results on a database of 416 texture images indicate that the proposed method provides a competitive retrieval rate, compared to the existi...

  6. Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO

    Science.gov (United States)

    Choi, Michael K.

    2014-01-01

    This paper uses phase change material (PCM) in the scan cavity of an imager or sounder on satellites in geostationary orbit (GEO) to maintain the telescope temperature stable. When sunlight enters the scan aperture, solar heating causes the PCM to melt. When sunlight stops entering the scan aperture, the PCM releases the thermal energy stored to keep the components in the telescope warm. It has no moving parts or bimetallic springs. It reduces heater power required to make up the heat lost by radiation to space through the aperture. It is an attractive thermal control option to a radiator with a louver and a sunshade.

  7. Utilization of satellite images to understand the dynamics of Pampas shallow lakes

    Directory of Open Access Journals (Sweden)

    V. S. Aliaga

    2016-06-01

    Full Text Available The aim of this study was to analyze satellite images of different spatial resolutions to interpret the morphometric behavior of six shallow lakes of the Pampas, Argentina. These are characterized by having different rainfall regimes. Morphometric response considering each location, site conditions and dry and wet extreme events is analyzed. Standardized Precipitation Index (IEP for determination of wet, dry and normal years was used. This analysis showed that the Pampas shallow lakes do not behave in the same way to the rainfall events. Its origin, socio-economic use and rainfall patterns affect their spatiotemporal variation and morphometric.

  8. Scheduling satellite-based SAR acquisition for sequential assimilation of water level observations into flood modelling

    OpenAIRE

    Garcia-Pintado, Javier; Neal, Jeff; Mason, David,; Dance, Sarah; Bates, Paul

    2013-01-01

    Satellite-based Synthetic Aperture Radar (SAR) has proved useful for obtaining information on flood extent, which, when intersected with a Digital Elevation Model (DEM) of the floodplain, provides water level observations that can be assimilated into a hydrodynamic model to decrease forecast uncertainty. With an increasing number of operational satellites with SAR capability, information on the relationship between satellite first visit and revisit times and forecast performance is required t...

  9. A Collective Detection Based GPS Receiver for Small Satellites Project

    Data.gov (United States)

    National Aeronautics and Space Administration — To solve the problem of autonomous navigation on small satellite platforms less than 20 kg, we propose to develop an onboard orbit determination receiver for small...

  10. Wireless electricity (Power) transmission using solar based power satellite technology

    International Nuclear Information System (INIS)

    In the near future due to extensive use of energy, limited supply of resources and the pollution in environment from present resources e.g. (wood, coal, fossil fuel) etc, alternative sources of energy and new ways to generate energy which are efficient, cost effective and produce minimum losses are of great concern. Wireless electricity (Power) transmission (WET) has become a focal point as research point of view and nowadays lies at top 10 future hot burning technologies that are under research these days. In this paper, we present the concept of transmitting power wirelessly to reduce transmission and distribution losses. The wired distribution losses are 70 – 75% efficient. We cannot imagine the world without electric power which is efficient, cost effective and produce minimum losses is of great concern. This paper tells us the benefits of using WET technology specially by using Solar based Power satellites (SBPS) and also focuses that how we make electric system cost effective, optimized and well organized. Moreover, attempts are made to highlight future issues so as to index some emerging solutions.

  11. Using Satellite Based Techniques to Combine Volcanic Ash Detection Methods

    Science.gov (United States)

    Hendrickson, B. T.; Kessinger, C.; Herzegh, P.; Blackburn, G.; Cowie, J.; Williams, E.

    2006-12-01

    Volcanic ash poses a serious threat to aircraft avionics due to the corrosive nature of the silicate particles. Aircraft encounters with ash have resulted in millions of dollars in damage and loss of power to aircraft engines. Accurate detection of volcanic ash for the purpose of avoiding these hazardous areas is of the utmost importance to ensure aviation safety as well as to minimize economic loss. Satellite-based detection of volcanic ash has been used extensively to warn the aviation community of its presence through the use of multi-band detection algorithms. However, these algorithms are generally used individually rather than in combination and require the intervention of a human analyst. Automation of the detection and warning of the presence of volcanic ash for the aviation community is a long term goal of the Federal Aviation Administration Oceanic Weather Product Development Team. We are exploring the use of data fusion techniques within a fuzzy logic framework to perform a weighted combination of several multi-band detection algorithms. Our purpose is to improve the overall performance of volcanic ash detection and to test whether automation is feasible. Our initial focus is on deep, stratospheric eruptions.

  12. Assessment of Total Suspended Sediment Distribution under Varying Tidal Conditions in Deep Bay: Initial Results from HJ-1A/1B Satellite CCD Images

    Directory of Open Access Journals (Sweden)

    Liqiao Tian

    2014-10-01

    Full Text Available Using Deep Bay in China as an example, an effective method for the retrieval of total suspended sediment (TSS concentration using HJ-1A/1B satellite images is proposed. The factors driving the variation of the TSS spatial distribution are also discussed. Two field surveys, conducted on August 29 and October 26, 2012, showed that there was a strong linear relationship (R2 = 0.9623 between field-surveyed OBS (optical backscatter measurements (5-31NTU and laboratory-analyzed TSS concentrations (9.89–35.58 mg/L. The COST image-based atmospheric correction procedure and the pseudo-invariant features (PIF method were combined to remove the atmospheric effects from the total radiance measurements obtained with different CCDs onboard the HJ-1A/1B satellites. Then, a simple and practical retrieval model was established based on the relationship between the satellite-corrected reflectance band ratio of band 3 and band 2 (Rrs3/Rrs2 and in-situ TSS measurements. The R2 of the regression relationship was 0.807, and the mean relative error (MRE was 12.78%, as determined through in-situ data validation. Finally, the influences of tide cycles, wind factors (direction and speed and other factors on the variation of the TSS spatial pattern observed from HJ-1A/1B satellite images from September through November of 2008 are discussed. The results show that HJ-1A/1B satellite CCD images can be used to estimate TSS concentrations under different tides in the study area over synoptic scales without using simultaneous in-situ atmospheric parameters and spectrum data. These findings provide strong informational support for numerical simulation studies on the combined influence of tide cycles and other associated hydrologic elements in Deep Bay.

  13. Online self-service processing system of ZY-3 satellite: a prospective study of image cloud services

    Science.gov (United States)

    Wang, Hongyan; Wang, Huabin; Shi, Shaoyu

    2015-12-01

    The strong demands for satellite images are increasing not only in professional fields, but also in the non-professionals. But the online map services with up-to-date satellite images can serve few demands. One challenge is how to provide online processing service, which need to handle real-time online data-intensive geospatial computation and visualization. Under the background of the development of cloud computing technology, the problem can be figured out partly. The other challenge is how to implement user-customized online processing without professional background and knowledge. An online self-service processing system of ZY-3 Satellite images is designed to implement an on-demand service mode in this paper. It will work with only some simple parameters being set up for the non-professionals without having to care about the specific processing steps. And the professionals can assemble the basic processing services to a service chain, which can work out a more complex processing and a better result. This intelligent self-service online system for satellite images processing, which is called the prototype of satellite image cloud service in this paper, is accelerated under the development of cloud computing technology and researches on data-intensive computing. To realize the goal, the service mode and framework of the online self-service processing system of ZY-3 Satellite images are figured out in this paper. The details of key technologies are also discussed, including user space virtualization management, algorithm-level parallel image processing, image service chain construction, etc. And the experimental system is built up as a prospective study of image cloud services.

  14. Automatic Urban Illegal Building Detection Using Multi-Temporal Satellite Images and Geospatial Information Systems

    Science.gov (United States)

    Khalili Moghadam, N.; Delavar, M. R.; Hanachee, P.

    2015-12-01

    With the unprecedented growth of urban population and urban development, we are faced with the growing trend of illegal building (IB) construction. Field visit, as the currently used method of IB detection, is time and man power consuming, in addition to its high cost. Therefore, an automatic IB detection is required. Acquiring multi-temporal satellite images and using image processing techniques for automatic change detection is one of the optimum methods which can be used in IB monitoring. In this research an automatic method of IB detection has been proposed. Two-temporal panchromatic satellite images of IRS-P5 of the study area in a part of Tehran, the city map and an updated spatial database of existing buildings were used to detect the suspected IBs. In the pre-processing step, the images were geometrically and radiometrically corrected. In the next step, the changed pixels were detected using K-means clustering technique because of its quickness and less user's intervention required. Then, all the changed pixels of each building were identified and the change percentage of each building with the standard threshold of changes was compared to detect the buildings which are under construction. Finally, the IBs were detected by checking the municipality database. The unmatched constructed buildings with municipal database will be field checked to identify the IBs. The results show that out of 343 buildings appeared in the images; only 19 buildings were detected as under construction and three of them as unlicensed buildings. Furthermore, the overall accuracies of 83%, 79% and 75% were obtained for K-means change detection, detection of under construction buildings and IBs detection, respectively.

  15. AUTOMATIC URBAN ILLEGAL BUILDING DETECTION USING MULTI-TEMPORAL SATELLITE IMAGES AND GEOSPATIAL INFORMATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    N. Khalili Moghadam

    2015-12-01

    Full Text Available With the unprecedented growth of urban population and urban development, we are faced with the growing trend of illegal building (IB construction. Field visit, as the currently used method of IB detection, is time and man power consuming, in addition to its high cost. Therefore, an automatic IB detection is required. Acquiring multi-temporal satellite images and using image processing techniques for automatic change detection is one of the optimum methods which can be used in IB monitoring. In this research an automatic method of IB detection has been proposed. Two-temporal panchromatic satellite images of IRS-P5 of the study area in a part of Tehran, the city map and an updated spatial database of existing buildings were used to detect the suspected IBs. In the pre-processing step, the images were geometrically and radiometrically corrected. In the next step, the changed pixels were detected using K-means clustering technique because of its quickness and less user’s intervention required. Then, all the changed pixels of each building were identified and the change percentage of each building with the standard threshold of changes was compared to detect the buildings which are under construction. Finally, the IBs were detected by checking the municipality database. The unmatched constructed buildings with municipal database will be field checked to identify the IBs. The results show that out of 343 buildings appeared in the images; only 19 buildings were detected as under construction and three of them as unlicensed buildings. Furthermore, the overall accuracies of 83%, 79% and 75% were obtained for K-means change detection, detection of under construction buildings and IBs detection, respectively.

  16. Satellite based wind resource assessment over the South China Sea

    OpenAIRE

    Badger, Merete; Astrup, Poul; Hasager, Charlotte Bay; Chang, Rui; Zhu, Rong

    2014-01-01

    Wind maps from satellites cover large areas and show horizontal wind speed variations offshore in great detail. This information is an excellent supplement to mast observations, which are limited to specific points, and to model simulations, which are typically run at coarser resolution. Wind maps from satellite synthetic aperture radar (SAR) data are particularly suitable for offshore wind energy applications because they offer a spatial resolution up to 500 m and include coastal seas. In th...

  17. A content-based image retrieval method for optical colonoscopy images based on image recognition techniques

    Science.gov (United States)

    Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro

    2015-03-01

    This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.

  18. 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.

  19. Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images

    International Nuclear Information System (INIS)

    The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. - Highlights: • Leaf biochemical alterations in the rainforest are caused by petroleum pollution. • Lower levels of chlorophyll content are symptom of vegetation stress in polluted sites. • Increased foliar water content was found in vegetation near polluted sites. • Vegetation stress was detected by using vegetation indices from satellite images. • Polluted sites and hydrocarbon seepages in rainforest can be identified from space. - Hydrocarbon pollution in the Amazon forest is observed for first time from satellite data

  20. Detection of ancient Egyptian archaeological sites using satellite remote sensing and digital image processing

    Science.gov (United States)

    Corrie, Robert K.

    2011-11-01

    Satellite remote sensing is playing an increasingly important role in the detection and documentation of archaeological sites. Surveying an area from the ground using traditional methods often presents challenges due to the time and costs involved. In contrast, the multispectral synoptic approach afforded by the satellite sensor makes it possible to cover much larger areas in greater spectral detail and more cost effectively. This is especially the case for larger scale regional surveys, which are helping to contribute to a better understanding of ancient Egyptian settlement patterns. This study presents an overview of satellite remote sensing data products, methodologies, and image processing techniques for detecting lost or undiscovered archaeological sites with reference to Egypt and the Near East. Key regions of the electromagnetic spectrum useful for site detection are discussed, including the visible near-infrared (VNIR), shortwave infrared (SWIR), thermal infrared (TIR), and microwave (radar). The potential of using Google Earth as both a data provider and a visualization tool is also examined. Finally, a case study is presented for detecting tell sites in Egypt using Landsat ETM+, ASTER, and Google Earth imagery. The results indicated that principal components analysis (PCA) was successfully able to detect and differentiate tell sites from modern settlements in Egypt's northwestern Nile Delta region.

  1. TIRCIS: Hyperspectral Thermal Infrared Imaging Using a Small-Satellite Compliant Fourier-Transform Imaging Spectrometer, for Natural Hazard Applications

    Science.gov (United States)

    Wright, R.; Lucey, P. G.; Crites, S.; Garbeil, H.; Wood, M.

    2015-12-01

    Many natural hazards, including wildfires, volcanic eruptions, and, from the perspective of climate-related hazards, urban heat islands, could be better quantified via the routine availability of hyperspectral thermal infrared remote sensing data from orbit. However, no sensors are currently in operation that provide such data at high-to-moderate spatial resolution (e.g. Landsat-class resolution). In this presentation we will describe a prototype instrument, developed using funding provided by NASA's Instrument Incubator Program, that can make these important measurements. Significantly, the instrument has been designed such that its size, mass, power, and cost are consistent with its integration into small satellite platforms, or deployment as part of small satellite constellations. The instrument, TIRCIS (Thermal Infra-Red Compact Imaging Spectrometer), uses a Fabry-Perot interferometer, an uncooled microbolometer array, and push-broom scanning to acquire hyperspectral image data cubes. Radiometric calibration is provided by blackbody targets while spectral calibration is achieved using monochromatic light sources. Neither the focal plane nor the optics need to be cooled, and the instrument has a mass of <10 kg and dimensions of 53 cm × 25 cm × 22 cm. Although the prototype has four moving parts, this can easily be reduced to one. The current optical design yields a 120 m ground sample size given an orbit of 500 km. Over the wavelength interval of 7.5 to 14 microns up to 90 spectral samples are possible, by varying the physical design of the interferometer. Our performance model indicates signal-to-noise ratios of the order of about 200 to 300:1. In this presentation we will provide an overview of the instrument design, fabrication, results from our initial laboratory characterization, and some of the application areas in which small-satellite-ready instruments such as TIRCIS could make a valuable contribution to the study of natural hazards.

  2. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-01-01

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

  3. Vision-based localization for on-orbit servicing of a partially cooperative satellite

    Science.gov (United States)

    Oumer, Nassir W.; Panin, Giorgio; Mülbauer, Quirin; Tseneklidou, Anastasia

    2015-12-01

    This paper proposes ground-in-the-loop, model-based visual localization system based on transmitted images to ground, to aid rendezvous and docking maneuvers between a servicer and a target satellite. In particular, we assume to deal with a partially cooperative target, i.e. passive and without fiducial markers, but supposed at least to keep a controlled attitude, up to small fluctuations, so that the approach mainly involves translational motion. For the purpose of localization, video cameras provide an effective and relatively inexpensive solution, working at a wide range of distances with an increasing accuracy and robustness during the approach. However, illumination conditions in space are especially challenging, due to the direct sunlight exposure and to the glossy surface of a satellite, that creates strong reflections and saturations and therefore a high level of background clutter and missing detections. We employ a monocular camera for mid-range tracking (20 - 5 m) and stereo camera at close-range (5 - 0.5 m), with the respective detection and tracking methods, both using intensity edges and robustly dealing with the above issues. Our tracking system has been extensively verified at the facility of the European Proximity Operations Simulator (EPOS) of DLR, which is a very realistic ground simulation able to reproduce sunlight conditions through a high power floodlight source, satellite surface properties using multilayer insulation foils, as well as orbital motion trajectories with ground-truth data, by means of two 6 DOF industrial robots. Results from this large dataset show the effectiveness and robustness of our method against the above difficulties.

  4. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Directory of Open Access Journals (Sweden)

    Haris Akram Bhatti

    2016-06-01

    Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  5. Primena satelitskih snimaka za dopunu sadržaja topografskih karata / An application of satellite images for improving the content of topographic maps

    Directory of Open Access Journals (Sweden)

    Miodrag D. Regodić

    2010-10-01

    Full Text Available Neažurnost sadržaja topografskih karata (TK, uslovljena ponajviše stvarnim ekonomskim teškoćama pri izradi novih i dopuni postojećih izdanja, kao i nedovoljnost i sve teže stanje pri izradi ostalih geotopografskih materijala (GTM, u velikoj meri otežavaju geotopografsko obezbeđenje (GTOb vojske u miru, kao i u svim periodima pripreme i vođenja ratnih dejstava. Rešenje ovog problema je u iznalaženju adekvatnog načina upotrebe proizvoda svih vrsta daljinskih snimanja, a naročito u obradi kvalitetnih satelitskih snimaka. Kao najbolji pokazatelj velikih mogućnosti daljinske detekcije, korišćenjem satelitskih snimaka, u kartografskoj praksi primenom kvalitetnih softverskih rešenja, u radu je predstavljena dopuna topografske karte nedostajućim topografskim sadržajem. / Lack of updated content of topographic maps (TMs, mainly due to economic issues regarding the publishing of existing or revised TMs, substantially affects geo-topographic supply (GTS of the Army both in peace and warfare time, as well as shortage of other geo-topographic materials (GTMs. The solution to this problem is in finding an appropriate method of using products of all types of remote sensing, high quality satellite images in particular. Having shown the best possibilities of remote sensing while using satellite images in mapping through the quality software solutions, the author presents an addition to topographic maps based on missing topographic data. Introduction Numerous natural and social phenomena are constantly observed, surveyed, registered and analyzed. Permanent or periodical satellite surveillance and recording for different purposes are growing in importance. The purposes can range from meteorological issues, through study of large water surfaces to military intelligence, etc. These recording can be used in making topographic, thematic and working maps as well as other geo-topographic material. Processing and analyzing of ikonos2 satellite images

  6. A Study on Coastline Extraction and Its Trend Based on Remote Sensing Image Data Mining

    OpenAIRE

    Yun Zhang; Xueming Li; Jianli Zhang; Derui Song

    2013-01-01

    In this paper, data mining theory is applied to carry out the field of the pretreatment of remote sensing images. These results show that it is an effective method for carrying out the pretreatment of low-precision remote sensing images by multisource image matching algorithm with SIFT operator, geometric correction on satellite images at scarce control points, and other techniques; the result of the coastline extracted by the edge detection method based on a chromatic aberration Canny operat...

  7. Image Compression of Neural Network Based on Corner Block

    Directory of Open Access Journals (Sweden)

    Wenjing Zhang

    2014-01-01

    Full Text Available Most information received by the human is acquired through vision. However, image has the largest data amount in three information forms. If the image is not compressed, high transmission rate for digital image transmission and tremendous capacity for digital image storage can hinder the development of digital image. For example, for a color image whose resolution rate is 1280×1024, each pixel needs 24B for storage, and the total data amount is about 3.75MB. If the earth satellite transmits the acquired image to the earth at 30 frames per second, the transmitting data size in 1 second is about 112.5MB. Under the condition of the existing communication capacity, if the image is not compressed, the real-time transmission of most multimedia information can’t be completed. High-speed transmission and storage of digital image has become the biggest obstacle of promoting digital image communication. So it is necessary to compress image. Data compression not only can rapidly transmit various information sources, improve the utilization rage of information channel and reduce transmitted power, but also can save energy and reduce storage capacity. More and more attentions of people have been paid to the application of artificial neural network to image compression, the reason for which is that artificial neural network has good fault tolerance, self-organization and adaptivity compared with traditional compression methods. So the predetermined data coding algorithm is not needed in the process of image compression. Neural network can independently complete the image coding and compression according to the characteristics of image. The paper combines corner detection technology with artificial neural network image compression, and designs a new neural network image compression encoding based on corner block with reasonable structure, high compression rate and rapid convergence rate

  8. Intercomparison of total precipitable water measurements made by satellite-borne microwave radiometers and ground-based GPS instruments

    Science.gov (United States)

    Mears, Carl A.; Wang, Junhong; Smith, Deborah; Wentz, Frank J.

    2015-03-01

    High-quality, high temporal resolution measurements of total precipitable water (TPW) can be made by evaluating the vapor-dependent delay of radio signals reaching land-based Global Positioning System (GPS) receivers from GPS satellites. These measurements are available since the mid-1990s when the GPS system became operational. Over the world's oceans, satellite-borne microwave imaging radiometers have been making measurements of TPW for more than 25 years. In this work, we perform an intercomparison of collocated TPW measurements made by these two disparate systems using measurements from 26 GPS stations located on small islands. The two types of measurements agree well, with typical satellite-station mean differences of less than 1.0 kg m-2. Analysis revealed several cases of inhomogeneities in the GPS data set, and two deficiencies in the Remote Sensing Systems satellite data, demonstrating the usefulness of intercomparison for improving the accuracy of both types of data. After the individual station, biases were removed, the standard deviation of the overall differences between individual satellites and GPS measurements ranged between 1.60 and 1.94 kg m-2. Twelve GPS stations had overlap time periods long enough to evaluate difference trends, yielding 59 satellite-station pairs when paired with different satellites. More than half of the pairs (39 of 59) did not show a significant trend. The 20 pairs with significant trends did not show trends of predominantly one sign, suggesting that neither system is plagued by a system-wide drift in TPW.

  9. Content based Image Retrieval from Forensic Image Databases

    Directory of Open Access Journals (Sweden)

    Swati A. Gulhane

    2015-03-01

    Full Text Available Due to the proliferation of video and image data in digital form, Content based Image Retrieval has become a prominent research topic. In forensic sciences, digital data have been widely used such as criminal images, fingerprints, scene images and so on. Therefore, the arrangement of such large image data becomes a big issue such as how to get an interested image fast. There is a great need for developing an efficient technique for finding the images. In order to find an image, image has to be represented with certain features. Color, texture and shape are three important visual features of an image. Searching for images using color, texture and shape features has attracted much attention. There are many content based image retrieval techniques in the literature. This paper gives the overview of different existing methods used for content based image retrieval and also suggests an efficient image retrieval method for digital image database of criminal photos, using dynamic dominant color, texture and shape features of an image which will give an effective retrieval result.

  10. Object-based Image Analysis Using VHR Satellite Imagery for Monitoring the Dismantling of a Refugee Camp after a Crisis: The Case of Lukole, Tanzania. GI_Forum 2014 – Geospatial Innovation for Society|

    OpenAIRE

    Tiede, Dirk; Lüthje, Fritjof; Stängel, Matthias; Füreder, Petra; Lang, Stefan

    2016-01-01

    The use of HR and VHR (high/very high spatial resolution) imagery and OBIA (objectbased image analysis) offers new possibilities for monitoring activities in and around refugee camps to manage, understand, and assess developments and impacts of the camp on its environment (see for example TIEDE et al. 2013, HAGENLOCHER et al. 2012). Here we demonstrate how VHR imagery in combination with OBIA can be used to retrieve and create valuable information about a remote refugee camp and its surroundi...

  11. Digital image-based titrations.

    Science.gov (United States)

    Gaiao, Edvaldo da Nobrega; Martins, Valdomiro Lacerda; Lyra, Wellington da Silva; de Almeida, Luciano Farias; da Silva, Edvan Cirino; Araújo, Mário César Ugulino

    2006-06-16

    The exploitation of digital images obtained from a CCD camera (WebCam) as a novel instrumental detection technique for titration is proposed for the first time. Named of digital image-based (DIB) titration, it also requires, as a traditional titration (for example, spectrophotometric, potentiometric, conductimetric), a discontinuity in titration curves where there is an end point, which is associated to the chemical equivalence condition. The monitored signal in the DIB titration is a RGB-based value that is calculated, for each digital image, by using a proposed procedure based on the red, green, and blue colour system. The DIB titration was applied to determine HCl and H3PO4 in aqueous solutions and total alkalinity in mineral and tap waters. Its results were compared to the spectrophotometric (SPEC) titration and, by applying the paired t-test, no statistic difference between the results of both methods was verified at the 95% confidence level. Identical standard deviations were obtained by both titrations in the determinations of HCl and H3PO4, with a slightly better precision for DIB titration in the determinations of total alkalinity. The DIB titration shows to be an efficient and promising tool for quantitative chemical analysis and, as it employs an inexpensive device (WebCam) as analytical detector, it offers an economically viable alternative to titrations that need instrumental detection. PMID:17723410

  12. Use of multi-temporal SPOT-5 satellite images for land degradation assessment in Cameron Highlands, Malaysia using Geospatial techniques

    Science.gov (United States)

    Nampak, Haleh; Pradhan, Biswajeet

    2016-07-01

    Soil erosion is the common land degradation problem worldwide because of its economic and environmental impacts. Therefore, land-use change detection has become one of the major concern to geomorphologists, environmentalists, and land use planners due to its impact on natural ecosystems. The objective of this paper is to evaluate the relationship between land use/cover changes and land degradation in the Cameron highlands (Malaysia) through multi-temporal remotely sensed satellite images and ancillary data. Land clearing in the study area has resulted increased soil erosion due to rainfall events. Also unsustainable development and agriculture, mismanagement and lacking policies contribute to increasing soil erosion rates. The LULC distribution of the study area was mapped for 2005, 2010, and 2015 through SPOT-5 satellite imagery data which were classified based on object-based classification. A soil erosion model was also used within a GIS in order to study the susceptibility of the areas affected by changes to overland flow and rain splash erosion. The model consists of four parameters, namely soil erodibility, slope, vegetation cover and overland flow. The results of this research will be used in the selection of the areas that require mitigation processes which will reduce their degrading potential. Key words: Land degradation, Geospatial, LULC change, Soil erosion modelling, Cameron highlands.

  13. An automatic building reconstruction method: a structural approach using high resolution satellite images

    OpenAIRE

    Lafarge, Florent; Descombes, Xavier; Zerubia, Josiane; Deseilligny, Marc-Pierrot

    2006-01-01

    We present an automatic 3D city model of dense urban areas from high resolution satellite data. The proposed method is developed using a structural approach : we construct complex buildings by merging simple parametric models with rectangular ground footprint. To do so, an automatic building extraction method based on marked point processes is used to provide rectangular building footprints. A collection of 3D parametric models is defined in order to be fixed onto these building footprints. A...

  14. Analysis Of Usefulness Of Satellite Image Processing Methods For Investigations Of Cultural Heritage Resources

    Science.gov (United States)

    Osińska-Skotak, Katarzyna; Zapłata, Rafał

    2015-12-01

    The paper presents the analysis of usefulness of WorldView-2 satellite image processing, which enhance information concerning the cultural heritage objects. WorldView-2 images are characterised by the very high spatial resolution and high spectral resolution; that is why they create new possibilities for many applications, including investigations of the cultural heritage. The vicinities of Iłża have been selected as the test site for presented investigations. The presented results of works are the effect of research works, which were performed in the frames of the scientific project "Utilisation of laser scanning and remote sensing in protection, investigations and inventory of the cultural heritage. Development of non-invasive, digital methods of documenting and recognising the architectural and archaeological heritage", as the part of "The National Programme for the Development of Humanities" of the Minister of Science and Higher Education in the period of 2012-2015.

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

    Science.gov (United States)

    Sowmya, Arcot; Trinder, John

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

  16. Classification of poplar stand areas by high-resolution satellite images

    Directory of Open Access Journals (Sweden)

    Grignetti A

    2009-09-01

    Full Text Available This work concerns the classification of different crown cover classes of Poplar stands, using high spatial resolution images (Ikonos and Quickbird satellites, in order to provide poplar monitoring. The test sites are two agricultural areas, located in the alluvial plain of northern Italy, close to Alessandria. In order to enhance spectral differences among classes, textural and high-pass filters were applied and vegetation indices (ratio, difference and normalized difference were processed. Images were then classified by means of an object-oriented approach which include a segmentation process followed by the application of a Standard Nearest Neighbor classifier on different data sets of spectral images (mean and standard deviation images and shape indices (shape, compactness. The data sets were defined using the Feature Space Optimization tool available in the Definiens®Developer7 software. From a set of attributes, this tool selects the best combination that produces the largest separability among the classes. The shape of the polygons matched the agricultural plots and the classification results were compared with the reference map defined by means of aerial photo interpretation and ground surveys. New poplar classes were defined in order to improve classification results. The accuracy values obtained were satisfactory (close to 73% for Ikonos and 82% for Quickbird images and they constitute a basis for automated recognition of poplar plantations and for updating poplar stands assessments.

  17. Content Base Image Retrieval Using Phong Shading

    OpenAIRE

    Uday Pratap Singh; Sanjeev Jain; Gulfishan Firdose Ahmed

    2010-01-01

    The digital image data is rapidly expanding in quantity and heterogeneity. The traditional information retrieval techniques does not meet the user’s demand, so there is need to develop an efficient system for content based image retrieval. Content based image retrieval means retrieval of images from database on the basis of visual features of image like as color, texture etc. In our proposed method feature are extracted after applying Phong shading on input image. Phong shading, flattering ou...

  18. Estimating deforestation in tropical humid and dry forests in Madagascar from 2000 to 2010 using multi-date Land sat satellite images and the random farests classifier

    OpenAIRE

    Grinand, C.; Rakotomalala, F.; Gond, V.; Vaudry, R.; Bernoux, Martial; Vieilledent, G.

    2013-01-01

    High resolution and low uncertainty deforestation maps covering large spatial areas in tropical countries are needed to plan efficient forest conservation and management programs such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Using an open-source free software (R, GRASS and QGis) and an original statistical approach combining multi-date land cover observations based on Landsat satellite images and the random forests classifier, we obtained up-to-date deforestati...

  19. Targeted Satellite Image Classification for Urban Map Updating Using Geospatial Information System Platform

    Science.gov (United States)

    Davoodianidaliki, M.; Abedini, A.

    2015-12-01

    Traditional map production and updating methods which usually involve field surveying and/or photogrammetry, while established and used for a long time, are time consuming and costly. Whereas satellite imagery have provided great amounts of data with high resolutions suitable for different geospatial applications. This paper focuses on taking advantage of geospatial information systems for enabling automated supervised classification of satellite images in urban areas. Such ability is provided through some attributes that determine whether features in current map have changed or not. The overall process consists of three stages: i: Geo database upgrade for addition of some attributes; ii: Classification by Support Vector Machine (SVM) and iii: Change analysis. The proposed method is applied on a sample data of Worldview 3 image of Hormozgan, Iran. The obtained results show that using such method not only can automate supervised classification but also can decrease misclassification errors through local training. Also its independent of classification method provides the ability to deploy other classification methods.

  20. Polar low climatology over the Nordic and Barents seas based on satellite passive microwave data

    Science.gov (United States)

    Smirnova, Julia E.; Golubkin, Pavel A.; Bobylev, Leonid P.; Zabolotskikh, Elizaveta V.; Chapron, Bertrand

    2015-07-01

    A new climatology of polar lows over the Nordic and Barents seas for 14 seasons (1995/1996-2008/2009) is presented. For the first time in climatological studies of polar lows an approach based on satellite passive microwave data was adopted for polar low identification. A total of 637 polar lows were found in 14 extended winter seasons by combining total atmospheric water vapor content and sea surface wind speed fields retrieved from Special Sensor Microwave/Imager data. As derived, the polar low activity in the Norwegian and Barents Seas is found to be almost equal, and the main polar low genesis area is located northeastward of the North Cape. For the Barents Sea, a significant correlation is found between the number of polar lows and mean sea ice extent. Individual indicative polar low characteristics (i.e., diameter, lifetime, distance traveled, translation speed, and maximum wind speed) are also presented.

  1. Building high dimensional imaging database for content based image search

    Science.gov (United States)

    Sun, Qinpei; Sun, Jianyong; Ling, Tonghui; Wang, Mingqing; Yang, Yuanyuan; Zhang, Jianguo

    2016-03-01

    In medical imaging informatics, content-based image retrieval (CBIR) techniques are employed to aid radiologists in the retrieval of images with similar image contents. CBIR uses visual contents, normally called as image features, to search images from large scale image databases according to users' requests in the form of a query image. However, most of current CBIR systems require a distance computation of image character feature vectors to perform query, and the distance computations can be time consuming when the number of image character features grows large, and thus this limits the usability of the systems. In this presentation, we propose a novel framework which uses a high dimensional database to index the image character features to improve the accuracy and retrieval speed of a CBIR in integrated RIS/PACS.

  2. Image Signature Based Mean Square Error for Image Quality Assessment

    Institute of Scientific and Technical Information of China (English)

    CUI Ziguan; GAN Zongliang; TANG Guijin; LIU Feng; ZHU Xiuchang

    2015-01-01

    Motivated by the importance of Human visual system (HVS) in image processing, we propose a novel Image signature based mean square error (ISMSE) metric for full reference Image quality assessment (IQA). Efficient image signature based describer is used to predict visual saliency map of the reference image. The saliency map is incorporated into luminance diff erence between the reference and distorted images to obtain image quality score. The eff ect of luminance diff erence on visual quality with larger saliency value which is usually corresponding to foreground objects is highlighted. Experimental results on LIVE database release 2 show that by integrating the eff ects of image signature based saliency on luminance dif-ference, the proposed ISMSE metric outperforms several state-of-the-art HVS-based IQA metrics but with lower complexity.

  3. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    Science.gov (United States)

    Wang, Teng; Wei, Shengji; Jónsson, Sigurjón

    2015-09-01

    Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (earthquake.

  4. Hierarchical content-based image retrieval by dynamic indexing and guided search

    Science.gov (United States)

    You, Jane; Cheung, King H.; Liu, James; Guo, Linong

    2003-12-01

    This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

  5. Global Crop Monitoring: A Satellite-Based Hierarchical Approach

    Directory of Open Access Journals (Sweden)

    Bingfang Wu

    2015-04-01

    Full Text Available Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, the CropWatch system has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The approach adopts a hierarchical system covering four spatial levels of detail: global, regional, national (thirty-one key countries including China and “sub-countries” (for the nine largest countries. The thirty-one countries encompass more that 80% of both production and exports of maize, rice, soybean and wheat. The methodology resorts to climatic and remote sensing indicators at different scales. The global patterns of crop environmental growing conditions are first analyzed with indicators for rainfall, temperature, photosynthetically active radiation (PAR as well as potential biomass. At the regional scale, the indicators pay more attention to crops and include Vegetation Health Index (VHI, Vegetation Condition Index (VCI, Cropped Arable Land Fraction (CALF as well as Cropping Intensity (CI. Together, they characterize crop situation, farming intensity and stress. CropWatch carries out detailed crop condition analyses at the national scale with a comprehensive array of variables and indicators. The Normalized Difference Vegetation Index (NDVI, cropped areas and crop conditions are integrated to derive food production estimates. For the nine largest countries, CropWatch zooms into the sub-national units to acquire detailed information on crop condition and production by including new indicators (e.g., Crop type proportion. Based on trend analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. The hierarchical approach adopted by CropWatch is the basis of the analyses of climatic and crop conditions assessments published in the quarterly “CropWatch bulletin” which

  6. Using NASA's Aura Satellite Data for Inquiry Based Classroom Instruction

    Science.gov (United States)

    Carter, B. L.; Stockman, S.; Bojkov, B.

    2007-12-01

    NASA's Earth Observing Satellite Aura was launched in 2004, and since that time has been collecting a wealth of data that contributes to scientists' understanding of the complexity of air quality issues. The Aura spacecraft monitors five of the six EPA criteria pollutants (NO2, SO2, O3, aerosols, and CO). Data from one of the criteria pollutants, NO2, are now available in a format useful to educators and students. The data by itself is not enough for students to engage in the scientific reasoning process. Thus, inquiry-driven supporting material in the form of lessons, project based learning scenarios, and curricular support for online data have all been adapted as part of the scaffolding necessary to help students gain an understanding of issues pertaining to air quality. These materials are delivered online which makes them readily accessible to the education community. Currently, NO2 data are available for manipulation using tools such as GoogleEarth and MY NASA DATA (http://mynasadata.larc.nasa.gov). These tools are used to investigate common relationships between spatial distribution and variability of NO2 concentrations. Through guided investigations in the Earth Exploration Toolbook (http://serc.carleton.edu/eet/index.html) or MY NASA DATA, students gain an understanding of NO2 variability. Students are then asked to extrapolate their knowledge and understanding to investigate other air quality issues relating to NO2. Within the coming year, the lessons built around Aura data will be introduced in professional development workshops. Feedback from those attending the professional development workshops about how the data and lessons are used in the classroom will be used to help shape future lesson development on new data. Subsequent data on criteria pollutants of SO2, aerosols, and O3 will soon be made available in a similar format to the education community, helping to further student understanding of the complex nature of air quality issues.

  7. Multi-Platform Satellite Based Estimates of Runoff in Ungauged Areas

    Science.gov (United States)

    Seo, J. Y.; Lee, S.-I.

    2015-10-01

    Over the past decades, extreme weather events such as floods and droughts have been on a steady increase. Especially, ungauged or hard-to-reach areas turn out to be the most affected areas by the unexpected water-related disasters. It is usually due to insufficient observation data, and deterioration of infra-structures as well as inadequate water management system. For such reasons, reliable estimation of runoff is important for the planning and the implementation of water projects in ungauged areas. North Korea, whose terrain is mostly hilly and mountainous, has become vulnerable to floods and droughts due to poor watershed management based on unreliable hydrological information along with rapid deforestation. Runoff estimation using data from multi-platform satellites having broad spatio-temporal coverage could be of a valuable substitute for ground-observed measurements. In this study, monthly runoff in North Korea (38°N - 43°N, 124°E - 131°E) was estimated by combining space-borne data from multi-platform satellites with ground observations. Period of analysis is from January 2003 to December 2013. Data sets used for this study are as in the following: {1} Terrestrial Water Storage Anomaly (TWSA) from Gravity Recovery and Climate Experiment (GRACE), (2) Evapotranspiration from Moderate Resolution Imaging Spectroradiometer (MODIS), (3) Satellite-observed precipitation from Tropical Rainfall Measurement Mission (TRMM), and (4) Ground-observed precipitation from World Meterological Organization (WMO) (see Figure 1 and Table 1). These components are balanced with the terrestrial water storage change, and runoff can be estimated from eq. (1).

  8. Assessment of satellite-based aerosol optical depth using continuous lidar observation

    Science.gov (United States)

    Lin, C. Q.; Li, C. C.; Lau, A. K. H.; Yuan, Z. B.; Lu, X. C.; Tse, K. T.; Fung, J. C. H.; Li, Y.; Yao, T.; Su, L.; Li, Z. Y.; Zhang, Y. Q.

    2016-09-01

    Due to a reliance on solar radiation, the aerosol optical depth (AOD) is observed only during the day by passive satellite-based instruments such as the MODerate resolution Imaging Spectroradiometer (MODIS). Research on urban air quality, atmospheric turbidity, and evolution of aerosols in the atmospheric boundary layer, however, requires 24-h measurement of aerosols. A lidar system is capable of detecting the vertical distribution of the aerosol extinction coefficient and calculating the AOD throughout the day, but routinely lidar observation is still quite limited and the results from MODIS and lidar sometimes are contradictory in China. In this study, long-term lidar observations from 2005 to 2009 over Hong Kong were analyzed with a focus on identification of the reasons for different seasonal variation in the AOD data obtained from MODIS and lidar. The lidar-retrieved AOD shows the lowest average level, but has the most significant diurnal variation during the summer. When considering only a 5-h period between 10:00 a.m. and 3:00 p.m. local time to match satellite passages, the average of the lidar-retrieved AOD doubles during the summer and exceeds that during the winter. This finding is consistent with the MODIS observation of a higher AOD during the summer and a lower AOD during the winter. The increase in the aerosol extinction coefficient in the upper level of the mixing layer makes the greatest contribution to the increase in the AOD at midday during the summer. These assessments suggest that large over-estimation may occur when long-term averages of AOD are estimated from passive satellite observations.

  9. Towards a protocol for validating satellite-based Land Surface Temperature: Theoretical considerations

    Science.gov (United States)

    Schneider, Philipp; Ghent, Darren J.; Corlett, Gary C.; Prata, Fred; Remedios, John J.

    2013-04-01

    Land Surface Temperature (LST) and emissivity are important parameters for environmental monitoring and earth system modelling. LST has been observed from space for several decades using a wide variety of satellite instruments with different characteristics, including both platforms in low-earth orbit and in geostationary orbit. This includes for example the series of Advanced Very High Resolution Radiometers (AVHRR) delivering a continuous thermal infrared (TIR) data stream since the early 1980s, the series of Along-Track Scanning Radiometers (ATSR) providing TIR data since 1991, and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard NASA's Terra and Aqua platforms, providing data since the year 2000. In addition, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard of the geostationary Meteosat satellites is now providing LST at unprecedented sub-hour frequency. The data record provided by such instruments is extremely valuable for a wide variety of applications, including climate change, land/atmosphere feedbacks, fire monitoring, modelling, land cover change, geology, crop- and water management. All of these applications, however, require a rigorous validation of the data in order to assess the product quality and the associated uncertainty. Here we report on recent work towards developing a protocol for validation of satellite-based Land Surface Temperature products. Four main validation categories are distinguished within the protocol: A) Comparison with in situ observations, B) Radiance-based validation, C) Inter-comparison with similar LST products, and D) Time-series analysis. Each category is further subdivided into several quality classes, which approximately reflect the validation accuracy that can be achieved by the different approaches, as well as the complexity involved with each method. Advice on best practices is given for methodology common to all categories. For each validation category, recommendations

  10. The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

    Science.gov (United States)

    Patterson, Maria T.; Anderson, Nicholas; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert L.; Handy, Matthew; Ly, Vuong; Mandl, Daniel J.; Pederson, Shane; Pivarski, James; Powell, Ray; Spring, Jonathan; Wells, Walt; Xia, John

    2016-01-01

    Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for

  11. Bipartite graph-based control flow checking for COTS-based small satellites

    Directory of Open Access Journals (Sweden)

    Wang Honghao

    2015-06-01

    Full Text Available Single event upset (SEU effect, caused by highly energized particles in aerospace, threatens the reliability and security of small satellites composed of commercial-off-the-shelves (COTS. SEU-induced control flow errors (CFEs may cause unpredictable behavior or crashes of COTS-based small satellites. This paper proposes a generic software-based control flow checking technique (CFC and bipartite graph-based control flow checking (BGCFC. To simplify the types of illegal branches, it transforms the conventional control flow graph into the equivalent bipartite graph. It checks the legality of control flow at runtime by comparing a global signature with the expected value and introduces consecutive IDs and bitmaps to reduce the time and memory overhead. Theoretical analysis shows that BGCFC can detect all types of inter-node CFEs with constant time and memory overhead. Practical tests verify the result of theoretical analysis. Compared with previous techniques, BGCFC achieves the highest error detection rate, lower time and memory overhead; the composite result in evaluation factor shows that BGCFC is the most effective one among all these techniques. The results in both theory and practice verify the applicability of BGCFC for COTS-based small satellites.

  12. Wind wave characteristics based on visual Observations and satellite altimetry

    Science.gov (United States)

    Grigorieva, V. G.; Badulin, S. I.

    2016-01-01

    Joint analysis of wind wave characteristics derived from the Voluntary Observing Ship data (VOS) and satellite altimetry is presented as the first step of the synthesis of different data sources. Global distributions of significant wave heights and periods along with wind speed are constructed using various techniques and empirical parameterizations. Good qualitative and quantitative agreement of VOS and satellite altimetry is found especially for regions with high spatio-temporal density of observations. The problems and prospects of the further development of the study are discussed in the context of global wave climatology and marine safety.

  13. Satellite imaging and vector-borne diseases: the approach of the French National Space Agency (CNES).

    Science.gov (United States)

    Marechal, Fabienne; Ribeiro, Nathalie; Lafaye, Murielle; Güell, Antonio

    2008-11-01

    Tele-epidemiology consists in studying human and animal epidemic, the spread of which is closely tied to environmental factors, using data from earth-orbiting satellites. By combining various data originated from satellites such as SPOT (vegetation indexes), Meteosat (winds and cloud masses) and other Earth observation data from Topex/Poseidon and Envisat (wave height, ocean temperature and colour) with hydrology data (number and distribution of lakes, water levels in rivers and reservoirs) and clinical data from humans and animals (clinical cases and serum use), predictive mathematical models can be constructed. A number of such approaches have been tested in the last three years. In Senegal, for example, Rift Valley fever epidemics are being monitored using a predictive model based on the rate at which water holes dry out after the rainy season, which affects the number of mosquito eggs which carry the virus. PMID:19021103

  14. Comprehensive Spectral Signal Investigation of a Larch Forest Combining - and Satellite-Based Measurements

    Science.gov (United States)

    Landmann, J. M.; Rutzinger, M.; Bremer, M.; chmidtner, K.

    2016-06-01

    Collecting comprehensive knowledge about spectral signals in areas composed by complex structured objects is a challenging task in remote sensing. In the case of vegetation, shadow effects on reflectance are especially difficult to determine. This work analyzes a larch forest stand (Larix decidua MILL.) in Pinnis Valley (Tyrol, Austria). The main goal is extracting the larch spectral signal on Landsat 8 (LS8) Operational Land Imager (OLI) images using ground measurements with the Cropscan Multispectral Radiometer with five bands (MSR5) simultaneously to satellite overpasses in summer 2015. First, the relationship between field spectrometer and OLI data on a cultivated grassland area next to the forest stand is investigated. Median ground measurements for each of the grassland parcels serve for calculation of the mean difference between the two sensors. Differences are used as "bias correction" for field spectrometer values. In the main step, spectral unmixing of the OLI images is applied to the larch forest, specifying the larch tree spectral signal based on corrected field spectrometer measurements of the larch understory. In order to determine larch tree and shadow fractions on OLI pixels, a representative 3D tree shape is used to construct a digital forest. Benefits of this approach are the computational savings compared to a radiative transfer modeling. Remaining shortcomings are the limited capability to consider exact tree shapes and nonlinear processes. Different methods to implement shadows are tested and spectral vegetation indices like the Normalized Difference Vegetation Index (NDVI) and Greenness Index (GI) can be computed even without considering shadows.

  15. Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

    Science.gov (United States)

    Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

    2013-12-01

    Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output

  16. Remote Sensing Image Deblurring Based on Grid Computation

    Institute of Scientific and Technical Information of China (English)

    LI Sheng-yang; ZHU Chong-guang; GE Ping-ju

    2006-01-01

    In general, there is a demand for real-time processing of mass quantity remote sensing images. However, the task is not only data-intensive but also computating-intensive. Distributed processing is a hot topic in remote sensing processing and image deblurring is also one of the most important needs. In order to satisfy the demand for quick processing and deblurring of mass quantity satellite images, we developed a distributed, grid computation-based platform as well as a corresponding middleware for grid computation. Both a constrained power spectrum equalization algorithm and effective block processing measures, which can avoid boundary effect, were applied during the processing. The result is satisfactory since computation efficiency and visual effect were greatly improved. It can be concluded that the technology of spatial information grids is effective for mass quantity remote sensing image processing.

  17. Graph Cuts based Image Segmentation using Fuzzy Rule Based System

    OpenAIRE

    Khokher, M. R.; A. Ghafoor; A.M. Siddiqui

    2012-01-01

    This work deals with the segmentation of gray scale, color and texture images using graph cuts. From input image, a graph is constructed using intensity, color and texture profiles of the image simultaneously. Based on the nature of image, a fuzzy rule based system is designed to find the weight that should be given to a specific image feature during graph development. The graph obtained from the fuzzy rule based weighted average of different image features is further used in normalized graph...

  18. A Large Scale Problem Based Learning inter-European Student Satellite Construction Project

    DEFF Research Database (Denmark)

    Nielsen, Jens Frederik Dalsgaard; Alminde, Lars; Bisgaard, Morten;

    2006-01-01

    A LARGE SCALE PROBLEM BASED LEARNING INTER-EUROPEAN STUDENT SATELLITE CONSTRUCTION PROJECT This paper describes the pedagogical outcome of a large scale PBL experiment. ESA (European Space Agency) Education Office launched January 2004 an ambitious project: Let students from all over Europe build a...... construction since the first Danish satellite Ørsted launched in 1999. In 2001 the AAU student satellite program was established. The aim of this project is to launch pico satellites (10 cm x 10 cm x 10 cm, 1 kg) developed and constructed by students every second or third year. The first satellite - Cubesat...... were conducted at the local "Houston" in Aalborg. The paper deals with the experiences from participating in a successful large scale inter cultural problem based engineering project including a variety of engineering disciplines as mechanical construction, communication system, power supply, attitude...

  19. Neural network multispectral satellite images classification of volcanic ash plumes in a cloudy scenario

    Directory of Open Access Journals (Sweden)

    Matteo Picchiani

    2015-03-01

    Full Text Available This work shows the potential use of neural networks in the characterization of eruptive events monitored by satellite, through fast and automatic classification of multispectral images. The algorithm has been developed for the MODIS instrument and can easily be extended to other similar sensors. Six classes have been defined paying particular attention to image regions that represent the different surfaces that could possibly be found under volcanic ash clouds. Complex cloudy scenarios composed by images collected during the Icelandic eruptions of the Eyjafjallajökull (2010 and Grimsvötn (2011 volcanoes have been considered as test cases. A sensitivity analysis on the MODIS TIR and VIS channels has been performed to optimize the algorithm. The neural network has been trained with the first image of the dataset, while the remaining data have been considered as independent validation sets. Finally, the neural network classifier’s results have been compared with maps classified with several interactive procedures performed in a consolidated operational framework. This comparison shows that the automatic methodology proposed achieves a very promising performance, showing an overall accuracy greater than 84%, for the Eyjafjalla - jökull event, and equal to 74% for the Grimsvötn event. 

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

    Science.gov (United States)

    Kavzoglu, T.; Yildiz, M.

    2014-09-01

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

  1. Differences between satellite- and ground-based urban heat island effect - Case study for the Budapest agglomeration area

    Science.gov (United States)

    Pongracz, R.; Bartholy, J.; Lelovics, E.; Dezso, Z. S.; Dobi, I.

    2012-04-01

    Urban heat island (UHI) is defined as the positive temperature anomaly occurring between built-in areas and their surroundings. For detailed analysis of UHI in a particular area, different approaches can be used. Here, two different techniques (ground-based and satellite-based) are applied to the Budapest agglomeration area and the results are compared. (1) Hourly recorded air temperature observations are available from six automatically operating climatological stations of the Hungarian Meteorological Service. Two stations are located in the downtown of Budapest (Kitaibel Pál street and Lágymányos); two stations can be found in the suburbs (Újpest and Pestszentlőrinc); and two stations are in the rural region (Penc - located to the northeast from the capital, and Kakucs - to the southeast from Budapest). These ground-based observations at the Budapest weather stations provide air temperature data at standard 2 m height above surface. However, due to the limited station number, this approach is not suitable for detailed evaluation of spatial UHI distribution. (2) Remotely sensed surface temperature values are available from seven thermal infrared channel measurements of the multi-spectral radiometer sensor called MODIS (Moderate Resolution Imaging Spectroradiometer), which is one of the sensors on-board satellites Terra and Aqua. They were launched to polar orbit as part of the NASA's Earth Observing System in December 1999, and in May 2002, respectively. Satellite Terra (Aqua) provides surface temperature fields around 09-10 UTC (12-13 UTC) and 20-21 UTC (02-03 UTC) with 1 km spatial resolution. The whole agglomeration has been divided into urban and rural pixels using the MODIS Land Cover Product categories, distance from the city centre, satellite images of the Google Earth, and GTOPO-30 global digital elevation model. However, the main disadvantage of this method is that for UHI analysis, data can be used only in case of clear sky conditions, which occurs

  2. HST/WFPC2 Imaging of the Dwarf Satellites And XI and And XIII : HB Morphology and RR Lyraes

    CERN Document Server

    Yang, Soung-Chul

    2011-01-01

    We present a study of the stellar populations in two faint M31 dwarf satellites, Andromeda XI and Andromeda XIII. Using archival images from the Wide Field Planetary Camera 2 (WFPC2) onboard the Hubble Space Telescope (HST), we characterize the horizontal branch (HB) morphologies and the RR Lyrae (RRL) populations of these two faint dwarf satellites. Our new template light curve fitting routine (RRFIT) has been used to detect and characterize RRL populations in both galaxies. The mean periods of RRab (RR0) stars in And XI and And XIII are $$=0.621 $\\pm$ 0.026 (error1) $\\pm$ 0.022 (error2), and $$=0.648 $\\pm$ 0.026 (error1) $\\pm$ 0.022 (error2) respectively, where "error1" represents the standard error of the mean, while "error2" is based on our synthetic light curve simulations. The RRL populations in these galaxies show a lack of RRab stars with high amplitudes ($Amp(V) > 1.0 $ mag) and relatively short periods ($P_{ab}$ $\\sim$ 0.5 days), yet their period -- V band amplitude (P-Amp(V)) relations track the re...

  3. VALIDATION OF SATELLITE-BASED SOIL MOISTURE ALGORITHMS

    Science.gov (United States)

    Validation is an important but particularly challenging task for passive microwave remote sensing of soil moisture from Earth orbit. The key issue is spatial scale; conventional measurements of soil moisture are made at a point whereas satellite sensors provide an integrated area/volume value for a ...

  4. The improved model of estimating global whitecap coverage based on satellite data

    Institute of Scientific and Technical Information of China (English)

    REN Danqin; HUA Feng; YANG Yongzeng; SUN Baonan

    2016-01-01

    The pro and con of whitecap parameterizations and a statistical wave breaking model are discussed. An improved model is derived by combining satellite-based parameterization and the wave breaking model. The appropriate constants for the general wave state are obtained by considering the breaking condition of the wave slope and fitting with the satellite-based parameterization. The result is close to the constants based on the whitecap data from Monahan. Comparing with satellite-based data and the original model’s results, the improved model's results are consistent with satellite-based data and previous studies. The global seasonal distributions of the whitecap coverage averaged from 1998 to 2008 are presented. Spatial and seasonal features of the whitecap coverage are analyzed.

  5. Development of methods for inferring cloud thickness and cloud-base height from satellite radiance data

    Science.gov (United States)

    Smith, William L., Jr.; Minnis, Patrick; Alvarez, Joseph M.; Uttal, Taneil; Intrieri, Janet M.; Ackerman, Thomas P.; Clothiaux, Eugene

    1993-01-01

    Cloud-top height is a major factor determining the outgoing longwave flux at the top of the atmosphere. The downwelling radiation from the cloud strongly affects the cooling rate within the atmosphere and the longwave radiation incident at the surface. Thus, determination of cloud-base temperature is important for proper calculation of fluxes below the cloud. Cloud-base altitude is also an important factor in aircraft operations. Cloud-top height or temperature can be derived in a straightforward manner using satellite-based infrared data. Cloud-base temperature, however, is not observable from the satellite, but is related to the height, phase, and optical depth of the cloud in addition to other variables. This study uses surface and satellite data taken during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (13 Nov. - 7 Dec. 1991, to improve techniques for deriving cloud-base height from conventional satellite data.

  6. The ESRC: A Web-based Environmental Satellite Resource Center

    Science.gov (United States)

    Abshire, W. E.; Guarente, B.; Dills, P. N.

    2009-12-01

    The COMET® Program has developed an Environmental Satellite Resource Center (known as the ESRC), a searchable, database-driven Website that provides easy access to a wide range of useful information training materials on polar-orbiting and geostationary satellites. Primarily sponsored by the NPOESS Program and NOAA, the ESRC is a tool for users seeking reliable sources of satellite information, training, and data. First published in September 2008, and upgraded in April 2009, the site is freely available at: http://www.meted.ucar.edu/esrc. Additional contributions to the ESRC are sought and made on an ongoing basis. The ESRC was created in response to a broad community request first made in May 2006. The COMET Program was asked to develop the site to consolidate and simplify access to reliable, current, and diverse information, training materials, and data associated with environmental satellites. The ESRC currently includes over 400 significant resources from NRL, CIMSS, CIRA, NASA, VISIT, NESDIS, and EUMETSAT, and improves access to the numerous satellite resources available from COMET’s MetEd Website. The ESRC is designed as a community site where organizations and individuals around the globe can easily submit their resources via online forms by providing a small set of metadata. The ESRC supports languages other than English and multi-lingual character sets have been tested. COMET’s role is threefold: 1) maintain the site, 2) populate it with our own materials, including smaller, focused learning objects derived from our larger training modules, and 3) provide the necessary quality assurance and monitoring to ensure that all resources are appropriate and well described before being made available. Our presentation will demonstrate many of the features and functionality of searching for resources using the ESRC, and will outline the steps for users to make their own submissions. For the site to reach its full potential, submissions representing diverse

  7. A near real-time satellite-based global drought climate data record

    International Nuclear Information System (INIS)

    Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

  8. Application of the Mean-shift Segmentation Parameters Estimator (MSPE to VHSR satellite images: Tetuan-Morocco

    Directory of Open Access Journals (Sweden)

    O. Benarchid

    2015-06-01

    Full Text Available Image segmentation is considered as crucial step dealing with Object-Based Image Analysis (OBIA and different segmentation results could be achieved by combining possible parameters values. Optimal parameters selection is usually carried out on the basis of visual interpretation; therefore, defining optimal combinations is a challenging task. In the present research, Mean-shift Segmentation Parameters estimator (MSPE proposed tool is applied to automate the selection of segmentation parameters values to Very High Spatial Resolution (VHSR satellite images in the region of Tetuan city (Northern Morocco. MSPE estimates the parameters values for the Mean-shift Segmentation (MS algorithm. However, this algorithm needs as inputs: i existing vector database and, ii spectral data to define automatically the segmentation parameter values. Finally, application of the MSPE method on different landscape’ types show accurate results with Under-Segmentation (US values ≤0.20 for industrial, residential and rural zones, while for dense residential area values of 0.35.

  9. Use of high resolution satellite images for tracking of changes in the lineament structure, caused by earthquakes

    CERN Document Server

    Arellano-Baeza, A A; Trejo-Soto, M

    2007-01-01

    Over the last decades strong efforts have been made to apply new spaceborn technologies to the study and possible forecast of strong earthquakes. In this study we use ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. A lineament is a straight or a somewhat curved feature in an image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. "The Lineament Extraction and Stripes Statistic Analysis" (LESSA) software package, developed by Zlatopolsy (1992, 1997). We assume that the lineaments allow to detect, at least partially, the presence ruptures in the Earths crust, and therefore enable one to follow the changes in the system of faults and fractures associated with strong earthquakes. We analysed 6 earthquakes occurred in the Pacific coast of the South America and XXX with the Richter scale magnitude >4.5. They were located in the regions with small season...

  10. Additive and Multiplicative Noise Removal Framework for Large Scale Color Satellite Images on OpenMP and GPUs

    Directory of Open Access Journals (Sweden)

    Banpot Dolwithayakul

    2013-03-01

    Full Text Available The satellite images are usually contaminated with multiplicative noises and some additive noises [1, 2]. Due to the large size of images, the removal process of these two types of noises at real-time is time consuming. The use of many-core processors such as GPUs may be advantageous in reducing the time of denoising. However, with the limitation of the GPU memory and the memory transfer cost, the proper design for denoising the large images is required. In this paper, we introduce the novel method for denoising both additive and multiplicative noises on multiple GPUs. The method is extended from [8] to perform a large-image denoising. It considers the proper data fitting to the GPU memory, memory utilization and thread utilization on both the CPU and GPUs. The speedup on the computation time of upto 87.29 times can be achieved compared with the sequential computation on the color 4096×4096 satellite image.

  11. Aerosol climatology over Nile Delta based on MODIS, MISR and OMI satellite data

    Science.gov (United States)

    Marey, H. S.; Gille, J. C.; El-Askary, H. M.; Shalaby, E. A.; El-Raey, M. E.

    2011-10-01

    Since 1999 Cairo and the Nile delta region have suffered from air pollution episodes called the "black cloud" during the fall season. These have been attributed to either burning of agriculture waste or long-range transport of desert dust. Here we present a detailed analysis of the optical and microphysical aerosol properties, based on satellite data. Monthly mean values of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) at 550 nm were examined for the 10 yr period from 2000-2009. Significant monthly variability is observed in the AOD with maxima in April or May (~0.5) and October (~0.45), and a minimum in December and January (~0.2). Monthly mean values of UV Aerosol Index (UVAI) retrieved by the Ozone Monitoring Instrument (OMI) for 4 yr (2005-2008) exhibit the same AOD pattern. The carbonaceous aerosols during the black cloud periods are confined to the planetary boundary layer (PBL), while dust aerosols exist over a wider range of altitudes, as shown by Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) aerosol profiles. The monthly climatology of Multi-angle Imaging SpectroRadiometer (MISR) data show that the aerosols during the black cloud periods are spherical with a higher percentage of small and medium size particles, whereas the spring aerosols are mostly large non-spherical particles. All of the results show that the air quality in Cairo and the Nile delta region is subject to a complex mixture of air pollution types, especially in the fall season, when biomass burning contributes to a background of urban pollution and desert dust.

  12. Aerosol climatology over Nile Delta based on MODIS, MISR and OMI satellite data

    Directory of Open Access Journals (Sweden)

    H. S. Marey

    2011-10-01

    Full Text Available Since 1999 Cairo and the Nile delta region have suffered from air pollution episodes called the "black cloud" during the fall season. These have been attributed to either burning of agriculture waste or long-range transport of desert dust. Here we present a detailed analysis of the optical and microphysical aerosol properties, based on satellite data. Monthly mean values of Moderate Resolution Imaging Spectroradiometer (MODIS aerosol optical depth (AOD at 550 nm were examined for the 10 yr period from 2000–2009. Significant monthly variability is observed in the AOD with maxima in April or May (~0.5 and October (~0.45, and a minimum in December and January (~0.2. Monthly mean values of UV Aerosol Index (UVAI retrieved by the Ozone Monitoring Instrument (OMI for 4 yr (2005–2008 exhibit the same AOD pattern. The carbonaceous aerosols during the black cloud periods are confined to the planetary boundary layer (PBL, while dust aerosols exist over a wider range of altitudes, as shown by Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO aerosol profiles. The monthly climatology of Multi-angle Imaging SpectroRadiometer (MISR data show that the aerosols during the black cloud periods are spherical with a higher percentage of small and medium size particles, whereas the spring aerosols are mostly large non-spherical particles. All of the results show that the air quality in Cairo and the Nile delta region is subject to a complex mixture of air pollution types, especially in the fall season, when biomass burning contributes to a background of urban pollution and desert dust.

  13. Aerosol Climatology over Nile Delta based on MODIS, MISR and OMI satellite data

    Directory of Open Access Journals (Sweden)

    H. S. Marey

    2011-04-01

    Full Text Available Since 1999 Cairo and the Nile delta region have suffered from air pollution episodes called the "black cloud" during the fall season. These have been attributed to either burning of agriculture waste or long-range transport of desert dust. Here we present a detailed analysis of the optical and microphysical aerosol properties, based on satellite data. Monthly mean values of Moderate Resolution Imaging Spectroradiometer (MODIS aerosol optical depth (AOD at 550 nm were examined for the 10 yr 2000–2009. Significant monthly variability is observed with maxima in April or May (~0.5 and October (~0.45, and a minimum in December and January (~0.2. Monthly mean values of UV Aerosol Index (UVAI retrieved by the Ozone Monitoring Instrument (OMI for 4 yr (2005–2008 exhibit the same AOD pattern. The carbonaceous aerosols during the black cloud periods are confined to the planetary boundary layer (PBL, while dust aerosols exist over a wider range of altitudes, as shown by Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO aerosol profiles. The monthly climatology of Multi-angle Imaging SpectroRadiometer (MISR data show that the aerosols during the black cloud periods are spherical with a higher percentage of small and medium size particles, whereas the spring aerosols are mostly large non-spherical particles. All of the results show that the air quality in Cairo and the Nile delta region is subject to a complex mixture of air pollution types, especially in the fall season, when biomass burning contributes to a background of urban pollution and desert dust.

  14. Object-Based Greenhouse Horticultural Crop Identification from Multi-Temporal Satellite Imagery: A Case Study in Almeria, Spain

    Directory of Open Access Journals (Sweden)

    Manuel A. Aguilar

    2015-06-01

    Full Text Available Greenhouse detection and mapping via remote sensing is a complex task, which has already been addressed in numerous studies. In this research, the innovative goal relies on the identification of greenhouse horticultural crops that were growing under plastic coverings on 30 September 2013. To this end, object-based image analysis (OBIA and a decision tree classifier (DT were applied to a set consisting of eight Landsat 8 OLI images collected from May to November 2013. Moreover, a single WorldView-2 satellite image acquired on 30 September 2013, was also used as a data source. In this approach, basic spectral information, textural features and several vegetation indices (VIs derived from Landsat 8 and WorldView-2 multi-temporal satellite data were computed on previously segmented image objects in order to identify four of the most popular autumn crops cultivated under greenhouse in Almería, Spain (i.e., tomato, pepper, cucumber and aubergine. The best classification accuracy (81.3% overall accuracy was achieved by using the full set of Landsat 8 time series. These results were considered good in the case of tomato and pepper crops, being significantly worse for cucumber and aubergine. These results were hardly improved by adding the information of the WorldView-2 image. The most important information for correct classification of different crops under greenhouses was related to the greenhouse management practices and not the spectral properties of the crops themselves.

  15. Image matching navigation based on fuzzy information

    Institute of Scientific and Technical Information of China (English)

    田玉龙; 吴伟仁; 田金文; 柳健

    2003-01-01

    In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.

  16. CONTENT BASED IMAGE RETRIEVAL : A REVIEW

    OpenAIRE

    Shereena V.B; Julie M.David

    2014-01-01

    In a content-based image retrieval system (CBIR), the main issue is to extract the image features that effectively represent the image contents in a database. Such an extraction requires a detailed evaluation of retrieval performance of image features. This paper presents a review of fundamental aspects of content based image retrieval including feature extraction of color and texture features. Commonly used color features including color moments, color histogram and color corr...

  17. A Shape Based Image Search Technique

    Directory of Open Access Journals (Sweden)

    Aratrika Sarkar

    2014-08-01

    Full Text Available This paper describes an interactive application we have developed based on shaped-based image retrieval technique. The key concepts described in the project are, imatching of images based on contour matching; iimatching of images based on edge matching; iiimatching of images based on pixel matching of colours. Further, the application facilitates the matching of images invariant of transformations like i translation ; ii rotation; iii scaling. The key factor of the system is, the system shows the percentage unmatched of the image uploaded with respect to the images already existing in the database graphically, whereas, the integrity of the system lies on the unique matching techniques used for optimum result. This increases the accuracy of the system. For example, when a user uploads an image say, an image of a mango leaf, then the application shows all mango leaves present in the database as well other leaves matching the colour and shape of the mango leaf uploaded.

  18. Cost Analysis of Algorithm Based Billboard Manger Based Handover Method in LEO satellite Networks

    Directory of Open Access Journals (Sweden)

    Suman Kumar Sikdar

    2012-12-01

    Full Text Available Now-a-days LEO satellites have an important role in global communication system. They have some advantages like low power requirement and low end-to-end delay, more efficient frequency spectrum utilization between satellites and spot beams over GEO and MEO. So in future they can be used as a replacement of modern terrestrial wireless networks. But the handover occurrence is more due to the speed of the LEOs. Different protocol has been proposed for a successful handover among which BMBHO is more efficient. But it had a problem during the selection of the mobile node during handover. In our previous work we have proposed an algorithm so that the connection can be established easily with the appropriate satellite. In this paper we will evaluate the mobility management cost of Algorithm based Billboard Manager Based Handover method (BMBHO. A simulation result shows that the cost is lower than the cost of Mobile IP of SeaHO-LEO and PatHOLEO

  19. Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia

    Science.gov (United States)

    Sousa, Adélia M. O.; Gonçalves, Ana Cristina; Mesquita, Paulo; Marques da Silva, José R.

    2015-03-01

    Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands.