WorldWideScience

Sample records for satellite based multispectral

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

    Energy Technology Data Exchange (ETDEWEB)

    Clodius, W.B.; Weber, P.G.; Borel, C.C.; Smith, B.W.

    1998-09-01

    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.

  2. [In-Flight Radiometric Calibration for ZY-3 Satellite Multispectral Sensor by Modified Reflectance-Based Method].

    Science.gov (United States)

    Han, Jie; Xie, Yong; Gu, Xing-fa; Yu, Tao; Liu, Qi-yue; Gao, Rong-jun

    2015-03-01

    Through integrating multi-spectral sensor characteristics of ZY-3 satellite, a modified reflectance-based method is proposed and used to achieve ZY-3 satellite multispectral sensor in-flight radiometric calibration. This method chooses level 1A image as data source and establishes geometric model to get an accurate observation geometric parameters at calibration site according to the information provided in image auxiliary documentation, which can reduce the influences on the calibration accuracy from image resampling and observation geometry errors. We use two-point and multi-points methods to calculate the absolute radiometric calibration coefficients of ZY-3 satellite multispectral sensor based on the large campaign at Dongying city, Shan Dong province. Compared with ZY-3 official calibration coefficients, multi-points method has higher accuracy than two-point method. Through analyzing the dispersion between each calibration point and the fitting line, we find that the residual error of water calibration site is larger than others, which of green band is approximately 67.39%. Treating water calibration site as an error, we filter it out using 95.4% confidence level as standard and recalculate the calibration coefficients with multi-points method. The final calibration coefficients show that the relative differences of the first three bands are less than 2% and the last band is less than 5%, which manifests that the proposed radiometric calibration method can obtain accurate and reliable calibration coefficients and is useful for other similar satellites in future.

  3. Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

    Directory of Open Access Journals (Sweden)

    Dimitris G. Stavrakoudis

    2014-07-01

    Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

  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. Satellite-based multi-spectral detection of the Widespread and Persistent Winter Fog over the Indo-Gangetic Plains

    Science.gov (United States)

    Gautam, R.; Rizvi, S.

    2015-12-01

    The Indo-Gangetic Plains (IGP), in the northern parts of south Asia, are subjected to dense haze/fog during winter months, on an annual basis. The thick fog prevalent during December/January months is both persistent and widespread in nature, often covering the entire IGP which stretches over 1500km in length. This study used multi-spectral imagery from MODIS data, to develop algorithms for daytime as well as nighttime detection of fog during winter 2000 to 2014 over the IGP. Specifically, our nighttime detection algorithm employs a bispectral thresholding technique, involving brightness temperature difference (BTD) between two spectral channels- 3.9 and 11.02μm. The theoretical basis for the detection using the 3.9 μm and 11.02 μm channels rely on the particular emissive properties of the two channels for fog droplets (Bendix and Bachmann, 1991). The small droplets found in fog are less emissive at 3.9 μm than at 11.02 μm. Brightness temperatures computed from corresponding radiance data (MODIS Level-1B) of band 22 (3.9 μm) and band 31 (11.02 μm), in conjunction with theoretical calculations from a radiative transfer (RT) model, were utilized to evaluate threshold value of BTD. Using theoretical RT calculations and automated analysis of hundreds of moderately high resolution satellite imagery (pixel resolution of 1km), our threshold cutoff for foggy pixels results in BTD value of 4 (deg) K. Additionally, to minimize contamination, we apply a spatial variability filter to discriminate the uniform texture of fog from other low-level clouds. A similar methodology based on BTD is also tested for daytime fog detection and separation from other cloud types. Furthermore, on the basis of operational multispectral retrievals of cloud properties (cloud effective radius, cloud top pressure, and cloud fraction) from MODIS, we have also processed spatial occurrences of fog climatology from 2000 to 2014. To validate our satellite retrieval algorithm of fog detection from

  6. Spatial Prediction of Coastal Bathymetry Based on Multispectral Satellite Imagery and Multibeam Data

    Directory of Open Access Journals (Sweden)

    Xavier Monteys

    2015-10-01

    Full Text Available The coastal shallow water zone can be a challenging and costly environment in which to acquire bathymetry and other oceanographic data using traditional survey methods. Much of the coastal shallow water zone worldwide remains unmapped using recent techniques and is, therefore, poorly understood. Optical satellite imagery is proving to be a useful tool in predicting water depth in coastal zones, particularly in conjunction with other standard datasets, though its quality and accuracy remains largely unconstrained. A common challenge in any prediction study is to choose a small but representative group of predictors, one of which can be determined as the best. In this respect, exploratory analyses are used to guide the make-up of this group, where we choose to compare a basic non-spatial model versus four spatial alternatives, each catering for a variety of spatial effects. Using one instance of RapidEye satellite imagery, we show that all four spatial models show better adjustments than the non-spatial model in the water depth predictions, with the best predictor yielding a correlation coefficient of actual versus predicted at 0.985. All five predictors also factor in the influence of bottom type in explaining water depth variation. However, the prediction ranges are too large to be used in high accuracy bathymetry products such as navigation charts; nevertheless, they are considered beneficial in a variety of other applications in sensitive disciplines such as environmental monitoring, seabed mapping, or coastal zone management.

  7. Visir-Sat - a Prospective Micro-Satellite Based Multi-Spectral Thermal Mission for Land Applications

    Science.gov (United States)

    Ruecker, G.; Menz, G.; Heinemann, S.; Hartmann, M.; Oertel, D.

    2015-04-01

    Current space-borne thermal infrared satellite systems aimed at land surface remote sensing retain some significant deficiencies, in particular in terms of spatial resolution, spectral coverage, number of imaging bands and temperature-emissivity separation. The proposed VISible-to-thermal IR micro-SATellite (VISIR-SAT) mission addresses many of these limitations, providing multi-spectral imaging data with medium-to-high spatial resolution (80m GSD from 800 km altitude) in the thermal infrared (up to 6 TIR bands, between 8 and 11μm) and in the mid infrared (1 or 2 MIR bands, at 4μm). These MIR/TIR bands will be co-registered with simultaneously acquired high spatial resolution (less than 30 m GSP) visible and near infrared multi-spectral imaging data. To enhance the spatial resolution of the MIR/TIR multi-spectral imagery during daytime, data fusion methods will be applied, such as the Multi-sensor Multi-resolution Technique (MMT), already successfully tested over agricultural terrain. This image processing technique will make generation of Land Surface Temperature (LST) EO products with a spatial resolution of 30 x 30 m2 possible. For high temperature phenomena such as vegetation- and peat-fires, the Fire Disturbance Essential Climate Variables (ECV) "Active fire location" and "Fire Radiative Power" will be retrieved with less than 100 m spatial resolution. Together with the effective fire temperature and the spatial extent even for small fire events the innovative system characteristics of VISIR-SAT go beyond existing and planned IR missions. The comprehensive and physically high-accuracy products from VISIR-SAT (e.g. for fire monitoring) may synergistically complement the high temperature observations of Sentinel-3 SLSTR in a unique way. Additionally, VISIR-SAT offers a very agile sensor system, which will be able to conduct intelligent and flexible pointing of the sensor's line-of-sight with the aim to provide global coverage of cloud free imagery every 5

  8. Precision Viticulture from Multitemporal, Multispectral Very High Resolution Satellite Data

    Science.gov (United States)

    Kandylakis, Z.; Karantzalos, K.

    2016-06-01

    In order to exploit efficiently very high resolution satellite multispectral data for precision agriculture applications, validated methodologies should be established which link the observed reflectance spectra with certain crop/plant/fruit biophysical and biochemical quality parameters. To this end, based on concurrent satellite and field campaigns during the veraison period, satellite and in-situ data were collected, along with several grape samples, at specific locations during the harvesting period. These data were collected for a period of three years in two viticultural areas in Northern Greece. After the required data pre-processing, canopy reflectance observations, through the combination of several vegetation indices were correlated with the quantitative results from the grape/must analysis of grape sampling. Results appear quite promising, indicating that certain key quality parameters (like brix levels, total phenolic content, brix to total acidity, anthocyanin levels) which describe the oenological potential, phenolic composition and chromatic characteristics can be efficiently estimated from the satellite data.

  9. Surface Emissivity Derived From Multispectral Satellite Data

    Science.gov (United States)

    Minnis, P.; Smith, W. L., Jr.; Young, D. F.

    1998-01-01

    Surface emissivity is critical for remote sensing of surface skin temperature and infrared cloud properties when the observed radiance is influenced by the surface radiation. It is also necessary to correctly compute the longwave flux from a surface at a given skin temperature. Surface emissivity is difficult to determine because skin temperature is an ill-defined parameter. The surface-emitted radiation may arise from a range of surface depths depending on many factors including soil moisture, vegetation, surface porosity, and heat capacity. Emissivity can be measured in the laboratory for pure surfaces. Transfer of laboratory measurements to actual Earth surfaces, however, is fraught with uncertainties because of their complex nature. This paper describes a new empirical approach for estimating surface skin temperature from a combination of brightness temperatures measured at different infrared wavelengths with satellite imagers. The method uses data from the new Geostationary Operational Environmental Satellite (GOES) imager to determine multispectral emissivities from the skin temperatures derived over the ARM Southern Great Plains domain.

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

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2006-01-01

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

  11. Unsupervised classification of changes in multispectral satellite imagery

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2004-01-01

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

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

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2006-01-01

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

  13. 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.

  14. 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.

  15. Retrieval of vegetation hydrodynamic parameters from satellite multispectral data

    Science.gov (United States)

    Forzieri, Giovanni; Degetto, Massimo; Righetti, Maurizio; Castelli, Fabio; Preti, Federico

    2013-04-01

    Riparian vegetation plays a crucial role on affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. This work explores the potential accuracies of retrieving vegetation hydrodynamic parameters through satellite multispectral data. The method is focused on estimation of vegetation height and flexural rigidity for herbaceous patterns and of plant density, tree height, stem diameter, crown base height and crown diameter of high-forest and coppice consociations for arboreal and shrub patterns. The retrieval algorithm performs: (1) classification procedure of riparian corridor; (2) land cover-based Principal Component Analysis of spectral channels; (3) explorative analysis of correlation structure between principal components and biomechanical properties and (4) model identification/estimation/validation for floodplain roughness parameterization. To capture the impacts of stiff/flexible vegetation, a GIS hydrodynamic model has been coupled with a flow resistance external routine that estimates the hydraulic roughness by using simulated water stages and the remote sensing-derived vegetation parameters. The procedure is tested along a 3-km reach of the Avisio river (Trentino Alto Adige, Italy) by comparing extended field surveys and a synchronous SPOT-5 multispectral image acquired on 28/08/2004. Results showed significant correlation values between spectral-derived information and hydrodynamic parameters. Predictive models provided high coefficients of determination, especially for mixed arboreal and shrub land covers. The generated structural parameter maps represent spatially explicit data layers that can be used as inputs to hydrodynamic models to analyze flow resistance effects in different submergence conditions of vegetation. The hydraulic modelling results showed that the new method is able to provide accurate hydraulic output data and to enhance the roughness estimation up to 73% with respect to a

  16. Satellite multispectral data for improved floodplain roughness modelling

    Science.gov (United States)

    Forzieri, Giovanni; Degetto, Massimo; Righetti, Maurizio; Castelli, Fabio; Preti, Federico

    2011-09-01

    SummaryRiparian vegetation plays a crucial role on affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. This paper explores the potential accuracies of retrieving vegetation hydrodynamic parameters through satellite multispectral data. The method is focused on estimation of vegetation height ( h g) and flexural rigidity ( MEI) for herbaceous patterns and of plant density ( M), tree height ( h), stem diameter ( Ds), crown base height ( cbh) and crown diameter ( Dc) of high-forest ( hf) and coppice ( cop) consociations for arboreal and shrub patterns. The method is organized in four sequential steps: (1) classification procedure of riparian corridor; (2) land cover-based Principal Component Analysis of spectral channels; (3) explorative analysis of correlation structure between principal components and biomechanical properties and (4) model identification/estimation/validation for floodplain roughness parameterization. To capture the hydrodynamic impacts of stiff/flexible vegetation, a GIS hydrodynamic model has been coupled with a flow resistance external routine that estimates the hydraulic roughness by using simulated water stages and the remote sensing-derived hydrodynamic parameters. The procedure is tested along a 3-km reach of the Avisio river (Trentino Alto Adige, Italy) by comparing extended field surveys and a synchronous SPOT-5 multispectral image acquired on 28/08/2004. Results showed significant correlation values between spectral-derived information and hydrodynamic parameters. Predictive models provided high coefficients of determination, especially for mixed arboreal and shrub land covers. The generated structural parameter maps represent spatially explicit data layers that can be used as inputs to hydrodynamic models to analyze flow resistance effects in different submergence conditions of vegetation. The hydraulic modelling results showed that the new method is able to provide accurate

  17. Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

    Science.gov (United States)

    Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.

    1993-01-01

    This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

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

    Directory of Open Access Journals (Sweden)

    ZHU Ying

    2015-04-01

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

  19. Crop classification using temporal stacks of multispectral satellite imagery

    Science.gov (United States)

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

    2017-05-01

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

  20. Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-06-01

    Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

  1. Benchmarking Deep Learning Frameworks for the Classification of Very High Resolution Satellite Multispectral Data

    Science.gov (United States)

    Papadomanolaki, M.; Vakalopoulou, M.; Zagoruyko, S.; Karantzalos, K.

    2016-06-01

    In this paper we evaluated deep-learning frameworks based on Convolutional Neural Networks for the accurate classification of multispectral remote sensing data. Certain state-of-the-art models have been tested on the publicly available SAT-4 and SAT-6 high resolution satellite multispectral datasets. In particular, the performed benchmark included the AlexNet, AlexNet-small and VGG models which had been trained and applied to both datasets exploiting all the available spectral information. Deep Belief Networks, Autoencoders and other semi-supervised frameworks have been, also, compared. The high level features that were calculated from the tested models managed to classify the different land cover classes with significantly high accuracy rates i.e., above 99.9%. The experimental results demonstrate the great potentials of advanced deep-learning frameworks for the supervised classification of high resolution multispectral remote sensing data.

  2. 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...

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

    Science.gov (United States)

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

    2013-01-01

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

  4. Simultaneous Fusion and Denoising of Panchromatic and Multispectral Satellite Images

    Science.gov (United States)

    Ragheb, Amr M.; Osman, Heba; Abbas, Alaa M.; Elkaffas, Saleh M.; El-Tobely, Tarek A.; Khamis, S.; Elhalawany, Mohamed E.; Nasr, Mohamed E.; Dessouky, Moawad I.; Al-Nuaimy, Waleed; Abd El-Samie, Fathi E.

    2012-12-01

    To identify objects in satellite images, multispectral (MS) images with high spectral resolution and low spatial resolution, and panchromatic (Pan) images with high spatial resolution and low spectral resolution need to be fused. Several fusion methods such as the intensity-hue-saturation (IHS), the discrete wavelet transform, the discrete wavelet frame transform (DWFT), and the principal component analysis have been proposed in recent years to obtain images with both high spectral and spatial resolutions. In this paper, a hybrid fusion method for satellite images comprising both the IHS transform and the DWFT is proposed. This method tries to achieve the highest possible spectral and spatial resolutions with as small distortion in the fused image as possible. A comparison study between the proposed hybrid method and the traditional methods is presented in this paper. Different MS and Pan images from Landsat-5, Spot, Landsat-7, and IKONOS satellites are used in this comparison. The effect of noise on the proposed hybrid fusion method as well as the traditional fusion methods is studied. Experimental results show the superiority of the proposed hybrid method to the traditional methods. The results show also that a wavelet denoising step is required when fusion is performed at low signal-to-noise ratios.

  5. Methods of Evaluating Thermodynamic Properties of Landscape Cover Using Multispectral Reflected Radiation Measurements by the Landsat Satellite

    Directory of Open Access Journals (Sweden)

    Yuriy Puzachenko

    2013-09-01

    Full Text Available The paper discusses methods of evaluating thermodynamic properties of landscape cover based on multi-spectral measurements by the Landsat satellites. Authors demonstrate how these methods could be used for studying functionality of landscapes and for spatial interpolation of Flux NET system measurements.

  6. Bolus tracking with nanofilter-based multispectral videography for capturing microvasculature hemodynamics

    Science.gov (United States)

    Najiminaini, Mohamadreza; Kaminska, Bozena; St. Lawrence, Keith; Carson, Jeffrey J. L.

    2014-04-01

    Multispectral imaging is a highly desirable modality for material-based analysis in diverse areas such as food production and processing, satellite-based reconnaissance, and biomedical imaging. Here, we present nanofilter-based multispectral videography (nMSV) in the 700 to 950 nm range made possible by the tunable extraordinary-optical-transmission properties of 3D metallic nanostructures. Measurements made with nMSV during a bolus injection of an intravascular tracer in the ear of a piglet resulted in spectral videos of the microvasculature. Analysis of the multispectral videos generated contrast measurements representative of arterial pulsation, the distribution of microvascular transit times, as well as a separation of the venous and arterial signals arising from within the tissue. Therefore, nMSV is capable of acquiring serial multispectral images relevant to tissue hemodynamics, which may have application to the detection and identification of skin cancer.

  7. Wavelet-based multispectral face recognition

    Institute of Scientific and Technical Information of China (English)

    LIU Dian-ting; ZHOU Xiao-dan; WANG Cheng-wen

    2008-01-01

    This paper proposes a novel wavelet-based face recognition method using thermal infrared (1R) and visible-light face images. The method applies the combination of Gabor and the Fisherfaces method to the reconstructed IR and visible images derived from wavelet frequency subbands. Our objective is to search for the subbands that are insensitive to the variation in expression and in illumination. The classification performance is improved by combining the multispectal information coming from the subbands that attain individually low equal error rate. Experimental results on Notre Dame face database show that the proposed wavelet-based algorithm outperforms previous multispectral images fusion method as well as monospectral method.

  8. Use and Assessment of Multi-Spectral Satellite Imagery in NWS Operational Forecasting Environments

    Science.gov (United States)

    Molthan, Andrew; Fuell, Kevin; Stano, Geoffrey; McGrath, Kevin; Schultz, Lori; LeRoy, Anita

    2015-01-01

    NOAA's Satellite Proving Grounds have established partnerships between product developers and NWS WFOs for the evaluation of new capabilities from the GOES-R and JPSS satellite systems. SPoRT has partnered with various WFOs to evaluate multispectral (RGB) products from MODIS, VIIRS and Himawari/AHI to prepare for GOES-R/ABI. Assisted through partnerships with GINA, UW/CIMSS, NOAA, and NASA Direct Broadcast capabilities.

  9. Improved global high resolution precipitation estimation using multi-satellite multi-spectral information

    Science.gov (United States)

    Behrangi, Ali

    In respond to the community demands, combining microwave (MW) and infrared (IR) estimates of precipitation has been an active area of research since past two decades. The anticipated launching of NASA's Global Precipitation Measurement (GPM) mission and the increasing number of spectral bands in recently launched geostationary platforms will provide greater opportunities for investigating new approaches to combine multi-source information towards improved global high resolution precipitation retrievals. After years of the communities' efforts the limitations of the existing techniques are: (1) Drawbacks of IR-only techniques to capture warm rainfall and screen out no-rain thin cirrus clouds; (2) Grid-box- only dependency of many algorithms with not much effort to capture the cloud textures whether in local or cloud patch scale; (3) Assumption of indirect relationship between rain rate and cloud-top temperature that force high intensity precipitation to any cold cloud; (4) Neglecting the dynamics and evolution of cloud in time; (5) Inconsistent combination of MW and IR-based precipitation estimations due to the combination strategies and as a result of above described shortcomings. This PhD dissertation attempts to improve the combination of data from Geostationary Earth Orbit (GEO) and Low-Earth Orbit (LEO) satellites in manners that will allow consistent high resolution integration of the more accurate precipitation estimates, directly observed through LEO's PMW sensors, into the short-term cloud evolution process, which can be inferred from GEO images. A set of novel approaches are introduced to cope with the listed limitations and is consist of the following four consecutive components: (1) starting with the GEO part and by using an artificial-neural network based method it is demonstrated that inclusion of multi-spectral data can ameliorate existing problems associated with IR-only precipitating retrievals; (2) through development of Precipitation Estimation

  10. D Land Cover Classification Based on Multispectral LIDAR Point Clouds

    Science.gov (United States)

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

    2016-06-01

    Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

  11. 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.

  12. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  13. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

  14. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multispectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  15. Retrieval Using Texture Features in High Resolution Multi-spectral Satellite Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Newsam, S D; Kamath, C

    2004-01-22

    Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region types. Much of the work done thus far has focused on panchromatic imagery at low to moderate spatial resolutions, such as images from Landsat 1-7 which have a resolution of 15-30 m/pixel, and from SPOT 1-5 which have a resolution of 2.5-20 m/pixel. However, it is not clear which texture representation works best for the new classes of high resolution panchromatic (60-100 cm/pixel) and multi-spectral (4 bands for red, green, blue, and near infra-red at 2.4-4 m/pixel) imagery. It is also not clear how the different spectral bands should be combined. In this paper, we investigate the retrieval performance of several different texture representations using multi-spectral satellite images from IKONOS. A query-by-example framework, along with a manually chosen ground truth dataset, allows different combinations of texture representations and spectral bands to be compared. We focus on the specific problem of retrieving inhabited regions from images of urban and rural scenes. Preliminary results show that (1) the use of all spectral bands improves the retrieval performance, and (2) co-occurrence, wavelet and Gabor texture features perform comparably.

  16. Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

    Science.gov (United States)

    Molthan, Andrew L.; Fuell, Kevin K.; Knaff, John; Lee, Thomas

    2012-01-01

    Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low-Earth orbits. The NASA Short-term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA s Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channel s available from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard METEOSAT-9. This broader suite includes products that discriminate between air mass types associated with synoptic-scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Similarly, researchers at NOAA/NESDIS and CIRA have developed air mass discrimination capabilities using channels available from the current GOES Sounders. Other applications of multispectral composites include combinations of high and low frequency, horizontal and vertically polarized passive microwave brightness temperatures to discriminate tropical cyclone structures and other synoptic-scale features. Many of these capabilities have been transitioned for evaluation and operational use at NWS Weather Forecast Offices and National Centers through collaborations with SPoRT and CIRA. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES-R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar-Orbiting Partnership (S-NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross

  17. 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.

  18. Multispectral sensing of natural resources with the MSTI-3 satellite

    Science.gov (United States)

    Griggs, Michael; Myers, William A.; Baker, H. Vernon

    1995-01-01

    The third satellite in the miniature sensor technology integration (MSTI) program includes two infrared imaging sensors with filter wheels, and a visible imaging spectrometer, with a common telescope and gimballed scan mirror assembly. These sensors will provide high spatial and spectral resolution imagery in the visible and 2.5 - 4.5 micrometers spectral regions. These spectral regions can provide information on the atmospheric aerosol optical thickness and size distribution; the vegetation index and crop classification; upper atmosphere temperatures, and tropospheric water vapor. In addition, the highly accurate pointing and tracking capability of the scan mirror permits a long look at particular events such as volcanic eruptions, major oil-spills, desert dust storms, forest fires and air pollution episodes. This tracking capability could also support ground truth calibration of other satellite sensors.

  19. Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

    Science.gov (United States)

    Clark, M. L.; Kilham, N. E.

    2015-12-01

    Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as

  20. Assessing suitability of multispectral satellites for mapping benthic macroalgal cover in turbid coastal waters by means of model simulations

    Science.gov (United States)

    Kutser, Tiit; Vahtmäe, Ele; Martin, Georg

    2006-04-01

    One of the objectives of monitoring benthic algal cover is to observe short- and long-term changes in species distribution and structure of coastal benthic habitats as indicators of ecological state. Mapping benthic algal cover with conventional methods (diving) provides great accuracy and high resolution, yet is very expensive and is limited by the time and manpower necessary. We measured reflectance spectra of three indicator species for the Baltic Sea: Cladophora glomerata (green macroalgae), Furcellaria lumbricalis (red macroalgae), and Fucus vesiculosus (brown macroalgae) and used a bio-optical model in an attempt to estimate whether these algae are separable from each other and sandy bottom or deep water by means of satellite remote sensing. Our modelling results indicate that to some extent it is possible to map the studied species with multispectral satellite sensors in turbid waters. However, the depths where the macroalgae can be detected are often shallower than the maximum depths where the studied species usually grow. In waters deeper than just a few meters, the differences between the studied bottom types are seen only in band 2 (green) of the multispectral sensors under investigation. It means that multispectral sensors are capable of detecting difference in brightness only in one band which is insufficient for recognition of different bottom types in waters where no or few in situ data are available. Configuration of MERIS spectral bands allows the recognition of red, green and brown macroalgae based on their spectral signatures provided the algal belts are wider than MERIS spatial resolution. Commercial stock of F. lumbricalis in West-Estonian Archipelago covers area where MERIS 300 m spatial resolution is adequate. However, strong attenuation of light in the water column and signal to noise ratio of the sensor do not allow mapping of Furcellaria down to maximum depths where it occurs.

  1. Crop classification using HJ satellite multispectral data in the North China Plain

    Science.gov (United States)

    Jia, Kun; Wu, Bingfang; Li, Qiangzi

    2013-01-01

    The HJ satellite constellation is designed for environment and disaster monitoring by the Chinese government. This paper investigates the performance of multitemporal multispectral charge-coupled device (CCD) data on board HJ-1-A and HJ-1-B for crop classification in the North China Plain. Support vector machine classifier is selected for the classification using different combinations of multitemporal HJ multispectral data. The results indicate that multitemporal HJ CCD data could effectively identify wheat fields with an overall classification accuracy of 91.7%. Considering only single temporal data, 88.2% is the best classification accuracy achieved using the data acquired at the flowering time of wheat. The performance of the combination of two temporal data acquired at the jointing and flowering times of wheat is almost as well as using all three temporal data, indicating that two appropriate temporal data are enough for wheat classification, and much more data have little effect on improving the classification accuracy. Moreover, two temporal data acquired over a larger time interval achieves better results than that over a smaller interval. However, the field borders and smaller cotton fields cannot be identified effectively by HJ multispectral data, and misclassification phenomenon exists because of the relatively coarse spatial resolution.

  2. Multispectral image compression based on DSC combined with CCSDS-IDC.

    Science.gov (United States)

    Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

    2014-01-01

    Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

  3. High-resolution multispectral satellite imagery for extracting bathymetric information of Antarctic shallow lakes

    Science.gov (United States)

    Jawak, Shridhar D.; Luis, Alvarinho J.

    2016-05-01

    High-resolution pansharpened images from WorldView-2 were used for bathymetric mapping around Larsemann Hills and Schirmacher oasis, east Antarctica. We digitized the lake features in which all the lakes from both the study areas were manually extracted. In order to extract the bathymetry values from multispectral imagery we used two different models: (a) Stumpf model and (b) Lyzenga model. Multiband image combinations were used to improve the results of bathymetric information extraction. The derived depths were validated against the in-situ measurements and root mean square error (RMSE) was computed. We also quantified the error between in-situ and satellite-estimated lake depth values. Our results indicated a high correlation (R = 0.60 0.80) between estimated depth and in-situ depth measurements, with RMSE ranging from 0.10 to 1.30 m. This study suggests that the coastal blue band in the WV-2 imagery could retrieve accurate bathymetry information compared to other bands. To test the effect of size and dimension of lake on bathymetry retrieval, we distributed all the lakes on the basis of size and depth (reference data), as some of the lakes were open, some were semi frozen and others were completely frozen. Several tests were performed on open lakes on the basis of size and depth. Based on depth, very shallow lakes provided better correlation (≈ 0.89) compared to shallow (≈ 0.67) and deep lakes (≈ 0.48). Based on size, large lakes yielded better correlation in comparison to medium and small lakes.

  4. Multispectral image pansharpening based on the contourlet transform

    Energy Technology Data Exchange (ETDEWEB)

    Amro, Israa; Mateos, Javier, E-mail: iamro@correo.ugr.e, E-mail: jmd@decsai.ugr.e [Departamento de Ciencias de la Computacion e I.A., Universidad de Granada, 18071 Granada (Spain)

    2010-02-01

    Pansharpening is a technique that fuses the information of a low resolution multispectral image (MS) and a high resolution panchromatic image (PAN), usually remote sensing images, to provide a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets based algorithms. Recently, the contourlet transform has been proposed. This transform combines the advantages of the wavelets transform with a more efficient directional information representation. In this paper we propose a new pansharpening method based on contourlets, compare with its wavelet counterpart and assess its performance numerically and visually.

  5. Pan-Sharpening Approaches Based on Unmixing of Multispectral Remote Sensing Imagery

    Science.gov (United States)

    Palubinskas, G.

    2016-06-01

    Model based analysis or explicit definition/listing of all models/assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods `better' satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two models/assumptions: spectral consistency for high resolution multispectral data (physical relationship between multispectral and panchromatic data in a high resolution scale) and spatial consistency for multispectral data (so-called Wald's protocol first property or relationship between multispectral data in different resolution scales). Two methods, one based on a linear unmixing model and another one based on spatial unmixing, are described/proposed/modified which respect models assumed and thus can produce correct or physically justified fusion results. Earlier mentioned property `better' should be measurable quantitatively, e.g. by means of so-called quality measures. The difficulty of a quality assessment task in multi-resolution image fusion or pan-sharpening is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions used are not valid or not fulfilled. From a model based view it follows naturally that a quality assessment measure can be defined as a combination of error model residuals using common or general models assumed in all fusion methods. Thus in this paper a comparison of the two earlier proposed/modified pan-sharpening methods is performed. Preliminary experiments based on visual analysis are carried out in the urban area of Munich city for optical remote sensing multispectral data and panchromatic imagery of the WorldView-2 satellite sensor.

  6. A Web-GIS Procedure Based on Satellite Multi-Spectral and Airborne LIDAR Data to Map the Road blockage Due to seismic Damages of Built-Up Urban Areas

    Science.gov (United States)

    Costanzo, Antonio; Montuori, Antonio; Silva, Juan Pablo; Silvestri, Malvina; Musacchio, Massimo; Buongiorno, Maria Fabrizia; Stramondo, Salvatore

    2016-08-01

    In this work, a web-GIS procedure to map the risk of road blockage in urban environments through the combined use of space-borne and airborne remote sensing sensors is presented. The methodology concerns (1) the provision of a geo-database through the integration of space-borne multispectral images and airborne LiDAR data products; (2) the modeling of building vulnerability, based on the corresponding 3D geometry and construction time information; (3) the GIS-based mapping of road closure due to seismic- related building collapses based on the building characteristic height and the width of the road. Experimental results, gathered for the Cosenza urban area, allow demonstrating the benefits of both the proposed approach and the GIS-based integration of multi-platforms remote sensing sensors and techniques for seismic road assessment purposes.

  7. Multi-Spectral Satellite Imagery and Land Surface Modeling Supporting Dust Detection and Forecasting

    Science.gov (United States)

    Molthan, A.; Case, J.; Zavodsky, B.; Naeger, A. R.; LaFontaine, F.; Smith, M. R.

    2014-12-01

    Current and future multi-spectral satellite sensors provide numerous means and methods for identifying hazards associated with polluting aerosols and dust. For over a decade, the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center in Huntsville has focused on developing new applications from near real-time data sources in support of the operational weather forecasting community. The SPoRT Center achieves these goals by matching appropriate analysis tools, modeling outputs, and other products to forecast challenges, along with appropriate training and end-user feedback to ensure a successful transition. As a spinoff of these capabilities, the SPoRT Center has recently focused on developing collaborations to address challenges with the public health community, specifically focused on the identification of hazards associated with dust and pollution aerosols. Using multispectral satellite data from the SEVIRI instrument on the Meteosat series, the SPoRT team has leveraged EUMETSAT techniques for identifying dust through false color (RGB) composites, which have been used by the National Hurricane Center and other meteorological centers to identify, monitor, and predict the movement of dust aloft. Similar products have also been developed from the MODIS and VIIRS instruments onboard the Terra and Aqua, and Suomi-NPP satellites, respectively, and transitioned for operational forecasting use by offices within NOAA's National Weather Service. In addition, the SPoRT Center incorporates satellite-derived vegetation information and land surface modeling to create high-resolution analyses of soil moisture and other land surface conditions relevant to the lofting of wind-blown dust and identification of other, possible public-health vectors. Examples of land surface modeling and relevant predictions are shown in the context of operational decision making by forecast centers with potential future applications to public health arenas.

  8. Multispectral image fusion based on fractal features

    Science.gov (United States)

    Tian, Jie; Chen, Jie; Zhang, Chunhua

    2004-01-01

    Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the

  9. Automated satellite cloud analysis: a multispectral approach to the problem of snow/cloud discrimination

    OpenAIRE

    Allen, Robert C. Jr.

    1987-01-01

    Approved for public release; distribution is unlimited An algorithm is developed and evaluated for discriminating among clouds, snow cover and clear land. The multispectral technique uses daytime images of AVHRR channels 1 (0.63^m). 3 (3.7jim) and 4 (11.0[im). Reflectance is derived for channel 3 by using the channel 4 emission temperature to estimate and remove the channel 3 thermal emission. Separation of clouds from snow and land is based primarily on this derived channel...

  10. Use of multispectral satellite imagery and hyperspectral endmember libraries for urban land cover mapping at the metropolitan scale

    Science.gov (United States)

    Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank

    2016-10-01

    The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.

  11. Fusion of multispectral and multitemporal satellite data for urban environmental changes analysis

    Science.gov (United States)

    Zoran, Maria

    2010-05-01

    Environmental urban changes assessment is providing information on environmental quality for identifying the major issues, priority areas of the policy making, planning and management. Effective planning is based on the completely and precisely understanding of the environmental parameters in urban area. Remote sensing is a key application in global-change science, being very useful for urban climatology and landuse-landcover dynamics and morphology analysis. Multi-spectral and multi-temporal satellite imagery (LANDSAT TM and ETM, MODIS and IKONOS) for Bucharest urban area over 1988 - 2008 period provides the most reliable technique of monitoring of different urban structures regarding the net radiation and heat fluxes associated with urbanization at the regional scale. The main objectives of this investigation aimed :to develop and validate new techniques for mapping and monitoring land cover and land use within and around Bucharest urban area using satellite sensor images and new digital framework data ; to analyze the spatial pattern of land cover and the detailed morphology of urban land use across the study area, and hence quantify the degree of order and structure that underlies the apparently irregular geometry of land use parcels; to devise a methodology for automatic updating of digital urban land-use maps; to develop an improved information base on urban land-use and land-use change for land-use/transportation models, urban development planning, urban ecology and local plans. Bucharest town, the biggest industrial, commercial center in Romania has experienced a rapid urban expansion during the last decades. A large amount of forest and agricultural land has been converted into housing, infrastructure and industrial estates. The resultant impervious urban surface alters the surface energy balance and surface runoff, which in turn could pose serious environmental problems for its inhabitants (e.g., urban waterlogged and thermal pollution). The changes over

  12. Use of shadow for enhancing mapping of perennial desert plants from high-spatial resolution multispectral and panchromatic satellite imagery

    Science.gov (United States)

    Alsharrah, Saad A.; Bouabid, Rachid; Bruce, David A.; Somenahalli, Sekhar; Corcoran, Paul A.

    2016-07-01

    Satellite remote-sensing techniques face challenges in extracting vegetation-cover information in desert environments. The limitations in detection are attributed to three major factors: (1) soil background effect, (2) distribution and structure of perennial desert vegetation, and (3) tradeoff between spatial and spectral resolutions of the satellite sensor. In this study, a modified vegetation shadow model (VSM-2) is proposed, which utilizes vegetation shadow as a contextual classifier to counter the limiting factors. Pleiades high spatial resolution, multispectral (2 m), and panchromatic (0.5 m) images were utilized to map small and scattered perennial arid shrubs and trees. We investigated the VSM-2 method in addition to conventional techniques, such as vegetation indices and prebuilt object-based image analysis. The success of each approach was evaluated using a root sum square error metric, which incorporated field data as control and three error metrics related to commission, omission, and percent cover. Results of the VSM-2 revealed significant improvements in perennial vegetation cover and distribution accuracy compared with the other techniques and its predecessor VSM-1. Findings demonstrated that the VSM-2 approach, using high-spatial resolution imagery, can be employed to provide a more accurate representation of perennial arid vegetation and, consequently, should be considered in assessments of desertification.

  13. Multispectral Snapshot Imagers Onboard Small Satellite Formations for Multi-Angular Remote Sensing

    Science.gov (United States)

    Nag, Sreeja; Hewagama, Tilak; Georgiev, Georgi; Pasquale, Bert; Aslam, Shahid; Gatebe, Charles K.

    2017-01-01

    Multispectral snapshot imagers are capable of producing 2D spatial images with a single exposure at selected, numerous wavelengths using the same camera, therefore operate differently from push broom or whiskbroom imagers. They are payloads of choice in multi-angular, multi-spectral imaging missions that use small satellites flying in controlled formation, to retrieve Earth science measurements dependent on the targets Bidirectional Reflectance-Distribution Function (BRDF). Narrow fields of view are needed to capture images with moderate spatial resolution. This paper quantifies the dependencies of the imagers optical system, spectral elements and camera on the requirements of the formation mission and their impact on performance metrics such as spectral range, swath and signal to noise ratio (SNR). All variables and metrics have been generated from a comprehensive, payload design tool. The baseline optical parameters selected (diameter 7 cm, focal length 10.5 cm, pixel size 20 micron, field of view 1.15 deg) and snapshot imaging technologies are available. The spectral components shortlisted were waveguide spectrometers, acousto-optic tunable filters (AOTF), electronically actuated Fabry-Perot interferometers, and integral field spectrographs. Qualitative evaluation favored AOTFs because of their low weight, small size, and flight heritage. Quantitative analysis showed that waveguide spectrometers perform better in terms of achievable swath (10-90 km) and SNR (greater than 20) for 86 wavebands, but the data volume generated will need very high bandwidth communication to downlink. AOTFs meet the external data volume caps well as the minimum spectral (wavebands) and radiometric (SNR) requirements, therefore are found to be currently feasible in spite of lower swath and SNR.

  14. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tau Island, Territory of American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  15. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Kingman Reef, Pacific Remote Island Area, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  16. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Johnston Atoll, Pacific Remote Island Area, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  17. Mosaic of gridded multibeam bathymetry, LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Saipan Island, Commonwealth of Northern Maraina Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

  18. Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

  19. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  20. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  1. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Palmyra Atoll, Pacific Remote Island Area, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  2. 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.

  3. Multiscale, multispectral and multitemporal satellite data to identify archaeological remains in the archaeological area of Tiwanaku (Bolivia)

    Science.gov (United States)

    Masini, Nicola; Lasaponara, Rosa

    2015-04-01

    The aim of this paper is to investigate the cultural landscape of the archaeological area of Tiwanaku (Bolivia) using multiscale, multispectral and multitemporal satellite data. Geospatial analysis techniques were applied to the satellite data sets in order to enhance and map traces of past human activities and perform a spatial characterization of environmental and cultural patterns. In particular, in the Tiwanaku area, the approach based on local indicators of spatial autocorrelation (LISA) applied to ASTER data allowed us to identify traces of a possible ancient hydrographic network with a clear spatial relation with the well-known moat surrounding the core of the monumental area. The same approach applied to QuickBird data, allowed us to identify numerous traces of archaeological interest, in Mollo Kontu mound, less investigated than the monumental area. Some of these traces were in perfect accordance with the results of independent studies, other were completely unknown. As a whole, the detected features, composing a geometric pattern with roughly North-South orientation, closely match those of the other residential contexts at Tiwanaku. These new insights, captured from multitemporal ASTER and QuickBird data processing, suggested new questions on the ancient landscape and provided important information for planning future field surveys and archaeogeophyical investigations. Reference [1] Lasaponara R., Masini N. 2014. Beyond modern landscape features: New insights in thearchaeological area of Tiwanaku in Bolivia from satellite data. International Journal of Applied Earth Observation and Geoinformation, 26, 464-471, http://dx.doi.org/10.1016/j.jag.2013.09.00. [2] Tapete D., Cigna F., Masini N., Lasaponara R. 2013. Prospection and monitoring of the archaeological heritage of Nasca, Peru, with ENVISAT ASAR, Archaeological Prospection, 20, 133-147, doi: 10.1002/arp.1449. [3] Lasaponara R, N Masini, 2012 Satellite Remote Sensing, A New Tool for Archaeology (Series

  4. Multispectral Image Road Extraction Based Upon Automated Map Conflation

    Science.gov (United States)

    Chen, Bin

    Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD

  5. Application of Multispectral Satellite Data for Geological Mapping in Antarctic Environments

    Science.gov (United States)

    Pour, A. B.; Hashim, M.; Hong, J. K.

    2016-09-01

    Remote sensing imagery is capable to provide a solution to overcome the difficulties associated with geological field mapping in the Antarctic. Advanced optical and radar satellite imagery is the most applicable tool for mapping and identification of inaccessible regions in Antarctic. Consequently, an improved scientific research using remote sensing technology would be essential to provide new and more complete lithological and structural data to fill the numerous knowledge gaps on Antarctica's geology. In this investigation, Oscar coast area in Graham Land, Antarctic Peninsula (AP) was selected to conduct a remote sensing study using Landsat-7 Thematic Mapper (TM), Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Contrast-enhanced Red-Green-Blue (RGB) composites, band ratios and Relative Band Depth (RBD) image processing techniques were applied to Landsat-8 and ASTER dataset for establishing the spectral separation of the main lithologic groups exposed in the study area. The outcomes of this investigation demonstrated the applications of SWIR and TIR bands of the multispectral remote sensing datasets to identify lithological units and producing geological maps with suitable accuracy of ice-free rock regions in the Antarctic Peninsula. The results could be extended to map coverage of non-investigated regions further east and validated previously inferred geological observations concerning other rocks and mineral deposits throughout the Antarctica.

  6. Ground truth measurements plan for the Multispectral Thermal Imager (MTI) satellite

    Energy Technology Data Exchange (ETDEWEB)

    Garrett, A.J.

    2000-01-03

    Sandia National Laboratories (SNL), Los Alamos National Laboratory (LANL), and the Savannah River Technology Center (SRTC) have developed a diverse group of algorithms for processing and analyzing the data that will be collected by the Multispectral Thermal Imager (MTI) after launch late in 1999. Each of these algorithms must be verified by comparison to independent surface and atmospheric measurements. SRTC has selected 13 sites in the continental U.S. for ground truth data collections. These sites include a high altitude cold water target (Crater Lake), cooling lakes and towers in the warm, humid southeastern US, Department of Energy (DOE) climate research sites, the NASA Stennis satellite Validation and Verification (V and V) target array, waste sites at the Savannah River Site, mining sites in the Four Corners area and dry lake beds in the southwestern US. SRTC has established mutually beneficial relationships with the organizations that manage these sites to make use of their operating and research data and to install additional instrumentation needed for MTI algorithm V and V.

  7. APPLICATION OF MULTISPECTRAL SATELLITE DATA FOR GEOLOGICAL MAPPING IN ANTARCTIC ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    A. B. Pour

    2016-09-01

    Full Text Available Remote sensing imagery is capable to provide a solution to overcome the difficulties associated with geological field mapping in the Antarctic. Advanced optical and radar satellite imagery is the most applicable tool for mapping and identification of inaccessible regions in Antarctic. Consequently, an improved scientific research using remote sensing technology would be essential to provide new and more complete lithological and structural data to fill the numerous knowledge gaps on Antarctica’s geology. In this investigation, Oscar coast area in Graham Land, Antarctic Peninsula (AP was selected to conduct a remote sensing study using Landsat-7 Thematic Mapper (TM, Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER data. Contrast-enhanced Red-Green-Blue (RGB composites, band ratios and Relative Band Depth (RBD image processing techniques were applied to Landsat-8 and ASTER dataset for establishing the spectral separation of the main lithologic groups exposed in the study area. The outcomes of this investigation demonstrated the applications of SWIR and TIR bands of the multispectral remote sensing datasets to identify lithological units and producing geological maps with suitable accuracy of ice-free rock regions in the Antarctic Peninsula. The results could be extended to map coverage of non-investigated regions further east and validated previously inferred geological observations concerning other rocks and mineral deposits throughout the Antarctica.

  8. Assessing the accuracy of hyperspectral and multispectral satellite imagery for categorical and Quantitative mapping of salinity stress in sugarcane fields

    Science.gov (United States)

    Hamzeh, Saeid; Naseri, Abd Ali; AlaviPanah, Seyed Kazem; Bartholomeus, Harm; Herold, Martin

    2016-10-01

    This study evaluates the feasibility of hyperspectral and multispectral satellite imagery for categorical and quantitative mapping of salinity stress in sugarcane fields located in the southwest of Iran. For this purpose a Hyperion image acquired on September 2, 2010 and a Landsat7 ETM+ image acquired on September 7, 2010 were used as hyperspectral and multispectral satellite imagery. Field data including soil salinity in the sugarcane root zone was collected at 191 locations in 25 fields during September 2010. In the first section of the paper, based on the yield potential of sugarcane as influenced by different soil salinity levels provided by FAO, soil salinity was classified into three classes, low salinity (1.7-3.4 dS/m), moderate salinity (3.5-5.9 dS/m) and high salinity (6-9.5) by applying different classification methods including Support Vector Machine (SVM), Spectral Angle Mapper (SAM), Minimum Distance (MD) and Maximum Likelihood (ML) on Hyperion and Landsat images. In the second part of the paper the performance of nine vegetation indices (eight indices from literature and a new developed index in this study) extracted from Hyperion and Landsat data was evaluated for quantitative mapping of salinity stress. The experimental results indicated that for categorical classification of salinity stress, Landsat data resulted in a higher overall accuracy (OA) and Kappa coefficient (KC) than Hyperion, of which the MD classifier using all bands or PCA (1-5) as an input performed best with an overall accuracy and kappa coefficient of 84.84% and 0.77 respectively. Vice versa for the quantitative estimation of salinity stress, Hyperion outperformed Landsat. In this case, the salinity and water stress index (SWSI) has the best prediction of salinity stress with an R2 of 0.68 and RMSE of 1.15 dS/m for Hyperion followed by Landsat data with an R2 and RMSE of 0.56 and 1.75 dS/m respectively. It was concluded that categorical mapping of salinity stress is the best option

  9. Multispectral and panchromatic image fusion based on unsubsampled contourlet transform

    Science.gov (United States)

    Liu, Hui; Yuan, Yan; Su, Lijuan; Hu, Liang; Zhang, Siyuan

    2013-12-01

    In order to achieve the high-resolution multispectral image, we proposed an algorithm for MS image and PAN image fusion based on NSCT and improved fusion rule. This method takes into account two aspects, the spectral similarity between fused image and the original MS image and enhancing the spatial resolution of the fused image. According to local spectral similarity between MS and PAN images, it can help to select high frequency detail coefficients from PAN image, which are injected into MS image then. Thus, spectral distortion is limited; the spatial resolution is enhanced. The experimental results demonstrate that the proposed fusion algorithm perform some improvements in integrating MS and PAN images.

  10. Multispectral thermometry based on neural network

    Institute of Scientific and Technical Information of China (English)

    孙晓刚; 戴景民

    2003-01-01

    In order to overcome the effect of the assumption between emissivity and wavelength on the measurement of true temperature and spectral emissivity for most engineering materials, a neural network based method is proposed for data processing while a blackbody furnace and three optical filters with known spectral transmittance curves were used to make up a true target. The experimental results show that the calculated temperatures are in good agreement with the temperature of the blackbody furnace, and the calculated spectral emissivity curves are in good agreement with the spectral transmittance curves of the filters. The method proposed has been proved to be an effective method for solving the problem of true temperature and emissivity measurement, and it can overcome the effect of the assumption between emissivity and wavelength on the measurement of true temperature and spectral emissivity for most engineering materials.

  11. Satellite observation of lowermost tropospheric ozone by multispectral synergism of IASI thermal infrared and GOME-2 ultraviolet measurements over Europe

    Science.gov (United States)

    Cuesta, J.; Eremenko, M.; Liu, X.; Dufour, G.; Cai, Z.; Hoepfner, M.; von Clarmann, T.; Sellitto, P.; Foret, G.; Gaubert, B.; Beekmann, M.; Orphal, J. J.; Chance, K.; Spurr, R. J.; Flaud, J.

    2013-12-01

    Lowermost tropospheric ozone is a major factor determining air quality, which directly affects human health in megacities and causes damages to ecosystems. Monitoring tropospheric ozone is a key societal issue which can be addressed at the regional scale by spaceborne observation. However, current satellite retrievals of tropospheric ozone using uncoupled either ultraviolet (UV) or thermal infrared (TIR) observations show limited sensitivity to ozone at the lowermost troposphere (LMT, up to 3 km asl of altitude above sea level), which is the major concern for air quality. In this framework, we have developed a new multispectral approach for observing lowermost tropospheric ozone from space by synergism of atmospheric TIR radiances observed by IASI and earth UV reflectances measured by GOME-2. Both instruments are onboard the series of MetOp satellites (in orbit since 2006 and expected until 2022) and their scanning capabilities offer global coverage every day, with a relatively fine ground pixel resolution (12-km-diameter pixels spaced by 25 km for IASI at nadir). Our technique uses altitude-dependent Tikhonov-Phillips-type constraints, which optimize sensitivity to lower tropospheric ozone. It integrates the VLIDORT and KOPRA radiative transfer codes for simulating UV reflectance and TIR radiance, respectively. We have used our method to analyze real observations over Europe during an ozone pollution episode in the summer of 2009. The results show that the multispectral synergism of IASI (TIR) and GOME-2 (UV) enables the observation of the spatial distribution of ozone plumes in the LMT, in good agreement with the CHIMERE regional chemistry-transport model. In this case study, when high ozone concentrations extend vertically above 3 km asl, they are similarly observed over land by both the multispectral and IASI retrievals. On the other hand, ozone plumes located below 3 km asl are only clearly depicted by the multispectral retrieval (both over land and over ocean

  12. Pairwise KLT-Based Compression for Multispectral Images

    Science.gov (United States)

    Nian, Yongjian; Liu, Yu; Ye, Zhen

    2016-12-01

    This paper presents a pairwise KLT-based compression algorithm for multispectral images. Although the KLT has been widely employed for spectral decorrelation, its complexity is high if it is performed on the global multispectral images. To solve this problem, this paper presented a pairwise KLT for spectral decorrelation, where KLT is only performed on two bands every time. First, KLT is performed on the first two adjacent bands and two principle components are obtained. Secondly, one remainning band and the principal component (PC) with the larger eigenvalue is selected to perform a KLT on this new couple. This procedure is repeated until the last band is reached. Finally, the optimal truncation technique of post-compression rate-distortion optimization is employed for the rate allocation of all the PCs, followed by embedded block coding with optimized truncation to generate the final bit-stream. Experimental results show that the proposed algorithm outperforms the algorithm based on global KLT. Moreover, the pairwise KLT structure can significantly reduce the complexity compared with a global KLT.

  13. High-spatial resolution multispectral and panchromatic satellite imagery for mapping perennial desert plants

    Science.gov (United States)

    Alsharrah, Saad A.; Bruce, David A.; Bouabid, Rachid; Somenahalli, Sekhar; Corcoran, Paul A.

    2015-10-01

    The use of remote sensing techniques to extract vegetation cover information for the assessment and monitoring of land degradation in arid environments has gained increased interest in recent years. However, such a task can be challenging, especially for medium-spatial resolution satellite sensors, due to soil background effects and the distribution and structure of perennial desert vegetation. In this study, we utilised Pleiades high-spatial resolution, multispectral (2m) and panchromatic (0.5m) imagery and focused on mapping small shrubs and low-lying trees using three classification techniques: 1) vegetation indices (VI) threshold analysis, 2) pre-built object-oriented image analysis (OBIA), and 3) a developed vegetation shadow model (VSM). We evaluated the success of each approach using a root of the sum of the squares (RSS) metric, which incorporated field data as control and three error metrics relating to commission, omission, and percent cover. Results showed that optimum VI performers returned good vegetation cover estimates at certain thresholds, but failed to accurately map the distribution of the desert plants. Using the pre-built IMAGINE Objective OBIA approach, we improved the vegetation distribution mapping accuracy, but this came at the cost of over classification, similar to results of lowering VI thresholds. We further introduced the VSM which takes into account shadow for further refining vegetation cover classification derived from VI. The results showed significant improvements in vegetation cover and distribution accuracy compared to the other techniques. We argue that the VSM approach using high-spatial resolution imagery provides a more accurate representation of desert landscape vegetation and should be considered in assessments of desertification.

  14. Mapping bathymetry in an active surf zone with the WorldView2 multispectral satellite

    Science.gov (United States)

    Trimble, S. M.; Houser, C.; Brander, R.; Chirico, P.

    2015-12-01

    Rip currents are strong, narrow seaward flows of water that originate in the surf zones of many global beaches. They are related to hundreds of international drownings each year, but exact numbers are difficult to calculate due to logistical difficulties in obtaining accurate incident reports. Annual average rip current fatalities are estimated to be ~100, 53 and 21 in the United States (US), Costa Rica, and Australia respectively. Current warning systems (e.g. National Weather Service) do not account for fine resolution nearshore bathymetry because it is difficult to capture. The method shown here could provide frequent, high resolution maps of nearshore bathymetry at a scale required for improved rip prediction and warning. This study demonstrates a method for mapping bathymetry in the surf zone (20m deep and less), specifically within rip channels, because rips form at topographically low spots in the bathymetry as a result of feedback amongst waves, substrate, and antecedent bathymetry. The methods employ the Digital Globe WorldView2 (WV2) multispectral satellite and field measurements of depth to generate maps of the changing bathymetry at two embayed, rip-prone beaches: Playa Cocles, Puerto Viejo de Talamanca, Costa Rica, and Bondi Beach, Sydney, Australia. WV2 has a 1.1 day pass-over rate with 1.84m ground pixel resolution of 8 bands, including 'yellow' (585-625 nm) and 'coastal blue' (400-450 nm). The data is used to classify bottom type and to map depth to the return in multiple bands. The methodology is tested at each site for algorithm consistency between dates, and again for applicability between sites.

  15. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    Science.gov (United States)

    Blonski, Slawomir; Glasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2003-01-01

    Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

  16. Multispectral image filtering method based on image fusion

    Science.gov (United States)

    Zhang, Wei; Chen, Wei

    2015-12-01

    This paper proposed a novel filter scheme by image fusion based on Nonsubsampled ContourletTransform(NSCT) for multispectral image. Firstly, an adaptive median filter is proposed which shows great advantage in speed and weak edge preserving. Secondly, the algorithm put bilateral filter and adaptive median filter on image respectively and gets two denoised images. Then perform NSCT multi-scale decomposition on the de-noised images and get detail sub-band and approximate sub-band. Thirdly, the detail sub-band and approximate sub-band are fused respectively. Finally, the object image is obtained by inverse NSCT. Simulation results show that the method has strong adaptability to deal with the textural images. And it can suppress noise effectively and preserve the image details. This algorithm has better filter performance than the Bilateral filter standard and median filter and theirs improved algorithms for different noise ratio.

  17. Optical detection of Prorocentrum donghaiense blooms based on multispectral reflectance

    Institute of Scientific and Technical Information of China (English)

    TAO Bangyi; PAN Delu; MAO Zhihua; SHEN Yuzhang; ZHU Qiankun; CHEN Jianyu

    2013-01-01

    Prorocentrum donghaiense is one of the most common red tide causative dinoflagellates in the Changjiang (Yangtze) River Estuary and the adjacent area of the East China Sea. It causes large-scale blooms in late spring and early summer that lead to widespread ecologic and economic damage. A means for distinguish-ing dinoflagellate blooms from diatom (Skeletonema costatum) blooms is desired. On the basis of measure-ments of remote sensing reflectance [Rrs(λ)] and inherent optical parameters, the potential of using a mul-tispectral approach is assessed for discriminating the algal blooms due to P. donghaiense from those due to S. costatum. The behavior of two reflectance ratios [R1 =Rrs(560)/Rrs(532) and R2 =Rrs(708)/Rrs(665)], suggests that differentiation of P. donghaiense blooms from diatom bloom types is possible from the current band setup of ocean color sensors. It is found that there are two reflectance ratio regimes that indicate a bloom is dominated by P. donghaiense: (1) R1 >1.55 and R2 1.75 and R2 ?1.0. Various sensitivity analyses are conducted to investigate the effects of the variation in varying levels of chlorophyll concentration and colored dissolved organic matter (CDOM) as well as changes in the backscattering ratio (bbp/bp) on the efficacy of this multispectral approach. Results indicate that the intensity and inherent op-tical properties of the algal species explain much of the behavior of the two ratios. Although backscattering influences the amplitude of Rrs(λ), especially in the 530 and 560 nm bands, the discrimination between P. donghaiense and diatoms is not significantly affected by the variation of bbp/bp. Since a CDOM(440) in coastal areas of the ECS is typically lower than 1.0 m−1 in most situations, the presence of CDOM does not interfere with this discrimination, even as SCDOM varies from 0.01 to 0.026 nm−1. Despite all of these effects, the dis-crimination of P. donghaiense blooms from diatom blooms based on multispectral

  18. Delineating Tree Types in a Complex Tropical Forest Setting Using High Resolution Multispectral Satellite Imagery

    Science.gov (United States)

    Cross, M.

    2016-12-01

    An improved process for the identification of tree types from satellite imagery for tropical forests is needed for more accurate assessments of the impact of forests on the global climate. La Selva Biological Station in Costa Rica was the tropical forest area selected for this particular study. WorldView-3 imagery was utilized because of its high spatial, spectral and radiometric resolution, its availability, and its potential to differentiate species in a complex forest setting. The first-step was to establish confidence in the high spatial and high radiometric resolution imagery from WorldView-3 in delineating tree types within a complex forest setting. In achieving this goal, ASD field spectrometer data were collected of specific tree species to establish solid ground control within the study site. The spectrometer data were collected from the top of each specific tree canopy utilizing established towers located at La Selva Biological Station so as to match the near-nadir view of the WorldView-3 imagery. The ASD data was processed utilizing the spectral response functions for each of the WorldView-3 bands to convert the ASD data into a band specific reflectivity. This allowed direct comparison of the ASD spectrometer reflectance data to the WorldView-3 multispectral imagery. The WorldView-3 imagery was processed to surface reflectance using two standard atmospheric correction procedures and the proprietary DigitalGlobe Atmospheric Compensation (AComp) product. The most accurate correction process was identified through comparison to the spectrometer data collected. A series of statistical measures were then utilized to access the accuracy of the processed imagery and which imagery bands are best suited for tree type identification. From this analysis, a segmentation/classification process was performed to identify individual tree type locations within the study area. It is envisioned the results of this study will improve traditional forest classification

  19. 3D LAND COVER CLASSIFICATION BASED ON MULTISPECTRAL LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    X. Zou

    2016-06-01

    Full Text Available Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green, at 1064 nm near infrared (NIR and at 1550nm intermediate infrared (IR. It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

  20. Mapping Arctic Tundra Vegetation Communities Using Field Spectroscopy and Multispectral Satellite Data in North Alaska, USA

    Directory of Open Access Journals (Sweden)

    Scott J. Davidson

    2016-11-01

    linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (~70% resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m to patch level (<500 m using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given the spatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments.

  1. An object based approach for coastline extraction from Quickbird multispectral images

    Directory of Open Access Journals (Sweden)

    Massimiliano Basile Giannini

    2014-12-01

    Full Text Available Because of the reduced dimensions of pixels, in the last years high resolution satellite images (Quickbird, IKONOS, GeoEye, ….. are considered very important data to extract information for coastline monitoring and engineering opera planning. They can integrate detail topographic maps and aerial photos so to contribute to modifications recognition and coastal dynamics reconstruction. Many studies have been carried out on coastline detection from high resolution satellite images: unsupervised and supervised classification, segmentation, NDVI (Normalized Difference Vegetation Index and NDWI (Normalized Difference Water Index are only some of the methodological aspects that have been already considered and experimented. This paper is aimed to implement an object based approach to extract coastline from Quickbird multispectral imagery. Domitian area near Volturno River mouth in Campania Region (Italy, an interesting zone for its dynamics and evolution, is considered. Object based approach is developed for automatic detection of coastline from Quickbird imagery using the Feature Extraction Workflow implemented in ENVI Zoom software. The resulting vector polyline is performed using the smoothing algorithm named PAEK (Polynomial Approximation with Exponential Kernel.

  2. Land cover mapping of the National Park Service northwest Alaska management area using Landsat multispectral and thematic mapper satellite data

    Science.gov (United States)

    Markon, C.J.; Wesser, Sara

    1998-01-01

    A land cover map of the National Park Service northwest Alaska management area was produced using digitally processed Landsat data. These and other environmental data were incorporated into a geographic information system to provide baseline information about the nature and extent of resources present in this northwest Alaskan environment.This report details the methodology, depicts vegetation profiles of the surrounding landscape, and describes the different vegetation types mapped. Portions of nine Landsat satellite (multispectral scanner and thematic mapper) scenes were used to produce a land cover map of the Cape Krusenstern National Monument and Noatak National Preserve and to update an existing land cover map of Kobuk Valley National Park Valley National Park. A Bayesian multivariate classifier was applied to the multispectral data sets, followed by the application of ancillary data (elevation, slope, aspect, soils, watersheds, and geology) to enhance the spectral separation of classes into more meaningful vegetation types. The resulting land cover map contains six major land cover categories (forest, shrub, herbaceous, sparse/barren, water, other) and 19 subclasses encompassing 7 million hectares. General narratives of the distribution of the subclasses throughout the project area are given along with vegetation profiles showing common relationships between topographic gradients and vegetation communities.

  3. A wavelet-based method for multispectral face recognition

    Science.gov (United States)

    Zheng, Yufeng; Zhang, Chaoyang; Zhou, Zhaoxian

    2012-06-01

    A wavelet-based method is proposed for multispectral face recognition in this paper. Gabor wavelet transform is a common tool for orientation analysis of a 2D image; whereas Hamming distance is an efficient distance measurement for face identification. Specifically, at each frequency band, an index number representing the strongest orientational response is selected, and then encoded in binary format to favor the Hamming distance calculation. Multiband orientation bit codes are then organized into a face pattern byte (FPB) by using order statistics. With the FPB, Hamming distances are calculated and compared to achieve face identification. The FPB algorithm was initially created using thermal images, while the EBGM method was originated with visible images. When two or more spectral images from the same subject are available, the identification accuracy and reliability can be enhanced using score fusion. We compare the identification performance of applying five recognition algorithms to the three-band (visible, near infrared, thermal) face images, and explore the fusion performance of combing the multiple scores from three recognition algorithms and from three-band face images, respectively. The experimental results show that the FPB is the best recognition algorithm, the HMM yields the best fusion result, and the thermal dataset results in the best fusion performance compared to other two datasets.

  4. Ground-based analysis of volcanic ash plumes using a new multispectral thermal infrared camera approach

    Science.gov (United States)

    Williams, D.; Ramsey, M. S.

    2015-12-01

    Volcanic plumes are complex mixtures of mineral, lithic and glass fragments of varying size, together with multiple gas species. These plumes vary in size dependent on a number of factors, including vent diameter, magma composition and the quantity of volatiles within a melt. However, determining the chemical and mineralogical properties of a volcanic plume immediately after an eruption is a great challenge. Thermal infrared (TIR) satellite remote sensing of these plumes is routinely used to calculate the volcanic ash particle size variations and sulfur dioxide concentration. These analyses are commonly performed using high temporal, low spatial resolution satellites, which can only reveal large scale trends. What is lacking is a high spatial resolution study specifically of the properties of the proximal plumes. Using the emissive properties of volcanic ash, a new method has been developed to determine the plume's particle size and petrology in spaceborne and ground-based TIR data. A multispectral adaptation of a FLIR TIR camera has been developed that simulates the TIR channels found on several current orbital instruments. Using this instrument, data of volcanic plumes from Fuego and Santiaguito volcanoes in Guatemala were recently obtained Preliminary results indicate that the camera is capable of detecting silicate absorption features in the emissivity spectra over the TIR wavelength range, which can be linked to both mineral chemistry and particle size. It is hoped that this technique can be expanded to isolate different volcanic species within a plume, validate the orbital data, and ultimately to use the results to better inform eruption dynamics modelling.

  5. Oil Palm Tree Detection with High Resolution Multi-Spectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Panu Srestasathiern

    2014-10-01

    Full Text Available Oil palm tree is an important cash crop in Thailand. To maximize the productivity from planting, oil palm plantation managers need to know the number of oil palm trees in the plantation area. In order to obtain this information, an approach for palm tree detection using high resolution satellite images is proposed. This approach makes it possible to count the number of oil palm trees in a plantation. The process begins with the selection of the vegetation index having the highest discriminating power between oil palm trees and background. The index having highest discriminating power is then used as the primary feature for palm tree detection. We hypothesize that oil palm trees are located at the local peak within the oil palm area. To enhance the separability between oil palm tree crowns and background, the rank transformation is applied to the index image. The local peak on the enhanced index image is then detected by using the non-maximal suppression algorithm. Since both rank transformation and non-maximal suppression are window based, semi-variogram analysis is used to determine the appropriate window size. The performance of the proposed method was tested on high resolution satellite images. In general, our approach uses produced very accurate results, e.g., about 90 percent detection rate when compared with manual labeling.

  6. Preliminary analysis of the forest health state based on multispectral images acquired by Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Czapski Paweł

    2015-09-01

    Full Text Available The main purpose of this publication is to present the current progress of the work associated with the use of a lightweight unmanned platforms for various environmental studies. Current development in information technology, electronics and sensors miniaturisation allows mounting multispectral cameras and scanners on unmanned aerial vehicle (UAV that could only be used on board aircraft and satellites. Remote Sensing Division in the Institute of Aviation carries out innovative researches using multisensory platform and lightweight unmanned vehicle to evaluate the health state of forests in Wielkopolska province. In this paper, applicability of multispectral images analysis acquired several times during the growing season from low altitude (up to 800m is presented. We present remote sensing indicators computed by our software and common methods for assessing state of trees health. The correctness of applied methods is verified using analysis of satellite scenes acquired by Landsat 8 OLI instrument (Operational Land Imager.

  7. Improved Ozone and Carbon Monoxide Profile Retrievals Using Multispectral Measurements from NASA "A Train", NPP, and TROPOMI Satellites

    Science.gov (United States)

    Fu, D.; Bowman, K. W.; Kulawik, S. S.; Miyazaki, K.; Worden, J. R.; Worden, H. M.; Livesey, N. J.; Payne, V.; Luo, M.; Natraj, V.; Veefkind, P.; Aben, I.; Landgraf, J.; Flynn, L. E.; Han, Y.; Liu, X.; Strow, L. L.; Kuai, L.

    2015-12-01

    Tropospheric ozone is at the juncture of air quality and climate. Ozone directly impacts human and plant health, and directly forces the climate system through absorption of thermal radiation. Carbon monoxide is a chemical precursor of greenhouse gases CO2 and tropospheric O3, and is also an ideal tracer of transport processes due to its medium life time (weeks to months). The Aqua-AIRS and Aura-OMI instruments in the NASA "A-Train", CrIS and OMPS instruments on the NOAA Suomi-NPP, IASI and GOME-2 on METOP and TROPOMI aboard the Sentinel 5 precursor (S5p) have the potential to provide the synoptic chemical and dynamical context for ozone necessary to quantify long-range transport at global scales and to provide an anchor to the near-term constellation of geostationary sounders: NASA TEMPO, ESA Sentinel 4, and the Korean GEMS. We introduce the JPL MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) retrieval algorithm, which ingests panspectral observations across multiple platforms in a non-linear optimal estimation framework. MUSES incorporates advances in remote sensing science developed during the EOS-Aura era including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation. Its performance has been demonstrated through prototype studies for multi-satellite missions (AIRS, CrIS, TROPOMI, TES, OMI, and OMPS). We present joint tropospheric ozone retrievals from AIRS/OMI and CrIS/OMPS over global scales, and demonstrate the potential of joint carbon monoxide profiles from TROPOMI/CrIS. These results indicate that ozone can be retrieved with ~2 degrees of freedom for signal (dofs) in the troposphere, which is similar to TES. Joint CO profiles have dofs similar to the MOPITT multispectral retrieval but with higher spatial resolution and coverage. Consequently, multispectral retrievals show promise in providing continuity with NASA EOS observations and pave the way towards a new

  8. Preliminary hard and soft bottom seafloor substrate map derived from an supervised classification of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from a supervised classification from multispectral World View-2 satellite imagery of Ni'ihau Island,...

  9. Multispectral thermal imaging

    Energy Technology Data Exchange (ETDEWEB)

    Weber, P.G.; Bender, S.C.; Borel, C.C.; Clodius, W.B.; Smith, B.W. [Los Alamos National Lab., NM (United States). Space and Remote Sensing Sciences Group; Garrett, A.; Pendergast, M.M. [Westinghouse Savannah River Corp., Aiken, SC (United States). Savannah River Technology Center; Kay, R.R. [Sandia National Lab., Albuquerque, NM (United States). Monitoring Systems and Technology Center

    1998-12-01

    Many remote sensing applications rely on imaging spectrometry. Here the authors use imaging spectrometry for thermal and multispectral signatures measured from a satellite platform enhanced with a combination of accurate calibrations and on-board data for correcting atmospheric distortions. The approach is supported by physics-based end-to-end modeling and analysis, which permits a cost-effective balance between various hardware and software aspects. The goal is to develop and demonstrate advanced technologies and analysis tools toward meeting the needs of the customer; at the same time, the attributes of this system can address other applications in such areas as environmental change, agriculture, and volcanology.

  10. Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

    Science.gov (United States)

    Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

    2017-05-01

    WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

  11. Potential of multispectral synergism for observing tropospheric ozone by combining IR and UV measurements from incoming LEO (EPS-SG) and GEO (MTG) satellite sensors

    Science.gov (United States)

    Costantino, Lorenzo; Cuesta, Juan; Emili, Emanuele; Coman, Adriana; Foret, Gilles; Dufour, Gaëlle; Eremenko, Maxim; Chailleux, Yohann; Beekmann, Matthias; Flaud, Jean-Marie

    2017-04-01

    Satellite observations offer a great potential for monitoring air quality on daily and global basis. However, measurements from currently in orbit sensors do not allow to probe surface concentrations of gaseous pollutants such as tropospheric ozone (Liu et al., 2010). Using single-band approaches based on spaceborne measurements of either thermal infrared radiance (TIR, Eremenko et al., 2008) or ultraviolet reflectance (UV, Liu et al., 2010) only ozone down to the lower troposphere (3 km) may be observed. A recent multispectral method (referred to as IASI+GOME-2) combining the information of IASI and GOME-2 (both onboard MetOp satellites) spectra, respectively from the TIR and UV, has shown enhanced sensitivity for probing ozone at the lowermost troposphere (LMT, below 3 km of altitude) with maximum sensitivity down to 2.20 km a.s.l. over land, while sensitivity for IASI or GOME-2 only peaks at 3 to 4 km at lowest (Cuesta et al., 2013). Future spatial missions will be launched in the upcoming years on both low and geostationary orbits, such as EPS-SG (EUMETSAT Polar System Second Generation) and MTG (Meteosat Third Generation), carrying respectively IASI-NG (for IR) and UVNS (for UV), and IRS (for IR) and UVN (Sentinel 4, for UV). This new-generation sensors will enhance the capacity to observe ozone pollution and particularly by synergism of multispectral measurements. In this work we develop a pseudo-observation simulator and evaluate the potential of future EPS-SG and MTG satellite observations, through IASI-NG+UVNS and IRS+UVN multispectral methods to observe near-surface O3. The pseudo-real state of atmosphere (nature run) is provided by MOCAGE (MOdèle de Chimie Atmosphérique à Grande Échelle) chemical transport model. Simulations are calibrated by careful comparisons with real data, to ensure the best coherence between pseudo-reality and reality, as well as between the pseudo-observation simulator and existing satellite products. We perform full and

  12. Optimization of the Multi-Spectral Euclidean Distance Calculation for FPGA-based Spaceborne Systems

    Science.gov (United States)

    Cristo, Alejandro; Fisher, Kevin; Perez, Rosa M.; Martinez, Pablo; Gualtieri, Anthony J.

    2012-01-01

    Due to the high quantity of operations that spaceborne processing systems must carry out in space, new methodologies and techniques are being presented as good alternatives in order to free the main processor from work and improve the overall performance. These include the development of ancillary dedicated hardware circuits that carry out the more redundant and computationally expensive operations in a faster way, leaving the main processor free to carry out other tasks while waiting for the result. One of these devices is SpaceCube, a FPGA-based system designed by NASA. The opportunity to use FPGA reconfigurable architectures in space allows not only the optimization of the mission operations with hardware-level solutions, but also the ability to create new and improved versions of the circuits, including error corrections, once the satellite is already in orbit. In this work, we propose the optimization of a common operation in remote sensing: the Multi-Spectral Euclidean Distance calculation. For that, two different hardware architectures have been designed and implemented in a Xilinx Virtex-5 FPGA, the same model of FPGAs used by SpaceCube. Previous results have shown that the communications between the embedded processor and the circuit create a bottleneck that affects the overall performance in a negative way. In order to avoid this, advanced methods including memory sharing, Native Port Interface (NPI) connections and Data Burst Transfers have been used.

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

    Directory of Open Access Journals (Sweden)

    S. Wittke

    2017-05-01

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

  14. Semi-supervised segmentation of multispectral remote sensing image based on spectral clustering

    Science.gov (United States)

    Zhang, Xiangrong; Wang, Ting; Jiao, Licheng; Yang, Chun

    2009-10-01

    In this paper, a new multi-spectral remote sensing image segmentation method based on multi-parameter semi-supervised spectral clustering (STS3C) is proposed. Two types of instance-level constraints: must-link and cannot-link are incorporated into spectral cluster to construct semi-supervised spectral clustering in which the self-tuning parameter is applied to avoid the selection of the scaling parameter. Further, when STS3C is applied to multi-spectral remote sensing image segmentation, the uniform sampling technique combined with nearest neighbor rule is used to reduce the computation complexity. Segmentation results show that STS3C outperforms the semi-supervised spectral clustering with fixed parameter and the well-known clustering methods including k-means and FCM in multi-spectral remote sensing image segmentation.

  15. Vector-lifting schemes based on sorting techniques for lossless compression of multispectral images

    Science.gov (United States)

    Benazza-Benyahia, Amel; Pesquet, Jean-Christophe

    2003-01-01

    In this paper, we introduce vector-lifting schemes which allow to generate very compact multiresolution representations, suitable for lossless and progressive coding of multispectral images. These new decomposition schemes exploit simultaneously the spatial and the spectral redundancies contained in multispectral images. When the spectral bands have different dynamic ranges, we improve dramatically the performances of the proposed schemes by a reversible histogram modification based on sorting permutations. Simulation tests carried out on real images allow to evaluate the performances of this new compression method. They indicate that the achieved compression ratios are higher than those obtained with currently used lossless coders.

  16. An airborne multispectral imaging system based on two consumer-grade cameras for agricultural remote sensing

    Science.gov (United States)

    This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS) sensor with 5616 × 3744 pixels. One came...

  17. 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...

  18. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer's disease

    Science.gov (United States)

    Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

    2016-07-01

    Computer based diagnosis of Alzheimer's disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer's disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  19. An efficient algorithm for food quality control based on multispectral signatures

    Science.gov (United States)

    Valdiviezo-N., Juan C.; Urcid, Gonzalo; Toxqui, Carina; Padilla, Alfonso; Santiago, Cesar

    2013-03-01

    Multispectral imaging has motivated new applications related to quality monitoring for industrial applications due to its capability of analysis based on spectral signatures. In practice, however, a multispectral system used for such purposes is limited because of the large amount of data to be analyzed, being necessary to develop fast methods for the unsupervised classification task. This manuscript introduces a fast and efficient algorithm that is used in combination with a multispectral system for the unsupervised classification of food based on quality. In particular, given two types of fruits previously characterized, we first register a multispectral image from them and perform a dimensionality reduction by taking into account the most representative spectral bands that involve their reflection spectra. From the reduced set, the min-W and max-M lattice associative memories are computed and a subset of their columns are used as centroids of specific clusters. Then, the Euclidean distance computed between each centroid and all spectral vectors in the image allows to subdivide the image in clusters. The achieved results state that the technique is fast, reliable, and non-invasive for food classification.

  20. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

    Energy Technology Data Exchange (ETDEWEB)

    Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja [Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh 226028 (India); Bao, Le Nguyen [Duytan University, Danang 550000 (Viet Nam); Lay-Ekuakille, Aimé [Department of Innovation Engineering, University of Salento, Lecce 73100 (Italy); Le, Dac-Nhuong, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn [Duytan University, Danang 550000 (Viet Nam); Haiphong University, Haiphong 180000 (Viet Nam)

    2016-07-15

    Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  1. Monitoring the Water Quality of Lake Koronia Using Long Time-Series of Multispectral Satellite Images

    Science.gov (United States)

    Perivolioti, Triantafyllia-Maria; Mouratidis, Antonios; Doxani, Georgia; Bobori, Dimitra

    2016-08-01

    In this study, a comprehensive 30-year (1984-2016) water quality parameter database for lake Koronia - one of the most important Ramsar wetlands of Greece - was compiled from Landsat imagery. The reliability of the data was evaluated by comparing water Quality Element (QE) values computed from Landsat data against in-situ data. Water quality algorithms developed from previous studies, specifically for the determination of Water Temperature, pH, Transparency/Secchi Disk Depth (SDD), Chlorophyll a and Conductivity, were applied to Landsat images. In addition, Water Depth, as well as the distribution of floating vegetation and cyanobacterial blooms were mapped. The performed comprehensive analysis posed certain questions, regarding the applicability of single empirical models across multi- temporal, multi-sensor datasets, towards the accurate prediction of key water quality indicators for shallow inland systems. This assessment demonstrates that satellite imagery can provide an accurate method for obtaining comprehensive spatial and temporal coverage of key water quality characteristics.

  2. Mapping of Agricultural Crops from Single High-Resolution Multispectral Images—Data-Driven Smoothing vs. Parcel-Based Smoothing

    Directory of Open Access Journals (Sweden)

    Asli Ozdarici-Ok

    2015-05-01

    Full Text Available Mapping agricultural crops is an important application of remote sensing. However, in many cases it is based either on hyperspectral imagery or on multitemporal coverage, both of which are difficult to scale up to large-scale deployment at high spatial resolution. In the present paper, we evaluate the possibility of crop classification based on single images from very high-resolution (VHR satellite sensors. The main objective of this work is to expose performance difference between state-of-the-art parcel-based smoothing and purely data-driven conditional random field (CRF smoothing, which is yet unknown. To fulfill this objective, we perform extensive tests with four different classification methods (Support Vector Machines, Random Forest, Gaussian Mixtures, and Maximum Likelihood to compute the pixel-wise data term; and we also test two different definitions of the pairwise smoothness term. We have performed a detailed evaluation on different multispectral VHR images (Ikonos, QuickBird, Kompsat-2. The main finding of this study is that pairwise CRF smoothing comes close to the state-of-the-art parcel-based method that requires parcel boundaries (average difference ≈ 2.5%. Our results indicate that a single multispectral (R, G, B, NIR image is enough to reach satisfactory classification accuracy for six crop classes (corn, pasture, rice, sugar beet, wheat, and tomato in Mediterranean climate. Overall, it appears that crop mapping using only one-shot VHR imagery taken at the right time may be a viable alternative, especially since high-resolution multitemporal or hyperspectral coverage as well as parcel boundaries are in practice often not available.

  3. Identification of tissular origin of particles based on autofluorescence multispectral image analysis at the macroscopic scale

    Science.gov (United States)

    Corcel, Mathias; Devaux, Marie-Françoise; Guillon, Fabienne; Barron, Cécile

    2017-06-01

    Powders produced from plant materials are heterogeneous in relation to native plant heterogeneity, and during grinding, dissociation often occurred at the tissue scale. The tissue composition of powdery samples could be modified through dry fractionation diagrams and impact their end-uses properties. If tissue identification is often made on native plant structure, this characterization is not straightforward in destructured samples such powders. Taking advantage of the autofluorescence properties of cell wall components, multispectral image acquisition is envisioned to identify the tissular origin of particles. Images were acquired on maize stem sections and ground tissues isolated from the same stem by hand dissection. The variability in fluorescence intensity profiles was analysed using principal component analysis. The correspondence between fluorescence profiles and the different tissues observed in maize sections was assessed based on histology or known compositional heterogeneity. Similar variability was encountered in fluorescence profiles extracted from powder leading to the potential ability to predict tissular origin based on this autofluorescence multispectral signal.

  4. Viola-Jones based hybrid framework for real-time object detection in multispectral images

    Science.gov (United States)

    Kuznetsova, E.; Shvets, E.; Nikolaev, D.

    2015-12-01

    This paper describes a method for real-time object detection based on a hybrid of a Viola-Jones cascade with a convolutional neural network. This scheme allows flexible trade-offs between detection quality and computational performance. We also propose a generalization of this method to multispectral images that effectively and efficiently utilizes information from each spectral channel. The new scheme is experimentally compared to traditional Viola-Jones, showing improved detection quality with adjustable performance.

  5. On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

    Science.gov (United States)

    Kingfield, D.; de Beurs, K.

    2014-12-01

    It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

  6. Mapping Aquatic Vegetation in a Tropical Wetland Using High Spatial Resolution Multispectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Timothy G. Whiteside

    2015-09-01

    Full Text Available Vegetation plays a key role in the environmental function of wetlands. The Ramsar-listed wetlands of the Magela Creek floodplain in Northern Australia are identified as being at risk from weeds, fire and climate change. In addition, the floodplain is a downstream receiving environment for the Ranger Uranium Mine. Accurate methods for mapping wetland vegetation are required to provide contemporary baselines of annual vegetation dynamics on the floodplain to assist with analysing any potential change during and after minesite rehabilitation. The aim of this study was to develop and test the applicability of geographic object-based image analysis including decision tree classification to classify WorldView-2 imagery and LiDAR-derived ancillary data to map the aquatic vegetation communities of the Magela Creek floodplain. Results of the decision tree classification were compared against a Random Forests classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010. The decision tree classification method provided an overall accuracy of 78% which was significantly higher than the overall accuracy of the Random Forests classification (67%. Most of the error in both classifications was associated with confusion between spectrally similar classes dominated by grasses, such as Hymenachne and Pseudoraphis. In addition, the extent of the sedge Eleocharis was under-estimated in both cases. This suggests the method could be useful for mapping wetlands where statistical-based supervised classifications have achieved less than satisfactory results. Based upon the results, the decision tree method will form part of an ongoing operational monitoring program.

  7. Multi-spectral image fusion method based on two channels non-separable wavelets

    Institute of Scientific and Technical Information of China (English)

    LIU Bin; PENG JiaXiong

    2008-01-01

    A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1, -1] and its application in the fusion of multi-spectral image are presented. Many 4x4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform.

  8. Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

    Science.gov (United States)

    Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

    2017-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are

  9. Computer based satellite design

    Science.gov (United States)

    Lashbrook, David D.

    1992-06-01

    A computer program to design geosynchronous spacecraft has been developed. The program consists of four separate but interrelated executable computer programs. The programs are compiled to run on a DOS based personnel computer. The source code is written in DoD mandated Ada programming language. The thesis presents the design technique and design equations used in the program. Detailed analysis is performed in the following areas for both dual spin and three axis stabilized spacecraft configurations: (1) Mass Propellent Budget and Mass Summary; (2) Battery Cell and Solar Cell Requirements for a Payload Power Requirement; and (3) Passive Thermal Control Requirements. A user's manual is included as Appendix A, and the source code for the computer programs as Appendix B.

  10. Integration of SAR features into multispectral images based on the nonsubsampled contourlet and IHS transform

    Science.gov (United States)

    Yang, Zhixiang; He, Xiufeng; Xu, Jia

    2011-10-01

    As a new image multiscale geometric analysis tool, the nonsubsampled contourlet transform (NSCT) has many advantages such as multiscale, localization and multidirection, and can efficiently capture the geometric information of images. Therefore, when the NSCT is introduced to image fusion, the characteristics of original images can be taken better and more information for fusion can be obtained. In this paper, a novel fusion algorithm for fusion of the synthetic aperture radar (SAR) image and multispectral images using conjointly the intensity-hue-saturation (IHS) transform and NSCT is proposed. In the proposed method, atrous wavelet is adopted to extract the detail information in low frequency parts fusion, and a new salience measure named as local inner product is introduced to select the high frequency coefficients. A PALSAR HH image of ALOS satellite despeckled by the Lee-sigma filter and HJ-1 multispectral images are used to evaluate the performance and efficiency of the proposed method. The fused images of each method are evaluated by qualitative and quantitative comparison and analysis compared with some traditional fusion rules. The experimental results indicate that the proposed method has the merits of better preservation of image definition and less loss of spectral information.

  11. EDGE DETECTION IN MULTISPECTRAL IMAGES BASED ON STRUCTURAL ELEMENTS

    Directory of Open Access Journals (Sweden)

    Mehdi Ghasemi Naraghi

    2011-02-01

    Full Text Available One of the first steps of feature extraction is edge detection. There are various methods for edge detection such as sobel operator, log method and canny operator. These methods have disadvantages such as create noise and discontinues edge and image smoothing. With the notice of the daily growth multi spectral images processing and describe of these images have become very important. Because of the existence of many details of these images, necessity to robust algorithms caused to present a method to extract feature of an object. In this article An improve method for edge detection has been purposed. In this method edge is detected by morphology’s operator and their combination and with the use of various structure elements of images in satellite and remote sensing.

  12. Edge Detection in Multispectral Images Based on Structural Elements

    Directory of Open Access Journals (Sweden)

    Mehdi Ghasemi Naraghi

    2011-02-01

    Full Text Available One of the first steps of feature extraction is edge detection. There are various methods for edge detection such as sobel operator, log method and canny operator. These methods have disadvantages such as create noise and discontinues edge and image smoothing. With the notice of the daily growth multi spectral images processing and describe of these images have become very important. Because of the existence of many details of these images, necessity to robust algorithms caused to present a method to extract featureof an object. In this article An improve method for edge detection has been purposed. In this method edge is detected by morphology’s operator and their combination and with the use of various structure elements of images in satellite and remote sensing.

  13. Satellite-Based Quantum Communications

    Energy Technology Data Exchange (ETDEWEB)

    Hughes, Richard J [Los Alamos National Laboratory; Nordholt, Jane E [Los Alamos National Laboratory; McCabe, Kevin P [Los Alamos National Laboratory; Newell, Raymond T [Los Alamos National Laboratory; Peterson, Charles G [Los Alamos National Laboratory

    2010-09-20

    Single-photon quantum communications (QC) offers the attractive feature of 'future proof', forward security rooted in the laws of quantum physics. Ground based quantum key distribution (QKD) experiments in optical fiber have attained transmission ranges in excess of 200km, but for larger distances we proposed a methodology for satellite-based QC. Over the past decade we have devised solutions to the technical challenges to satellite-to-ground QC, and we now have a clear concept for how space-based QC could be performed and potentially utilized within a trusted QKD network architecture. Functioning as a trusted QKD node, a QC satellite ('QC-sat') could deliver secret keys to the key stores of ground-based trusted QKD network nodes, to each of which multiple users are connected by optical fiber or free-space QC. A QC-sat could thereby extend quantum-secured connectivity to geographically disjoint domains, separated by continental or inter-continental distances. In this paper we describe our system concept that makes QC feasible with low-earth orbit (LEO) QC-sats (200-km-2,000-km altitude orbits), and the results of link modeling of expected performance. Using the architecture that we have developed, LEO satellite-to-ground QKD will be feasible with secret bit yields of several hundred 256-bit AES keys per contact. With multiple ground sites separated by {approx} 100km, mitigation of cloudiness over any single ground site would be possible, potentially allowing multiple contact opportunities each day. The essential next step is an experimental QC-sat. A number of LEO-platforms would be suitable, ranging from a dedicated, three-axis stabilized small satellite, to a secondary experiment on an imaging satellite. to the ISS. With one or more QC-sats, low-latency quantum-secured communications could then be provided to ground-based users on a global scale. Air-to-ground QC would also be possible.

  14. 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...

  15. 3D LAND COVER CLASSIFICATION BASED ON MULTISPECTRAL LIDAR POINT CLOUDS

    OpenAIRE

    Zou, X; G. Zhao; Li, J.(Center for Underground Physics, Institute for Basic Science (IBS), Daejon, 305-811, Korea); Y. Yang; Fang, Y.

    2016-01-01

    Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable o...

  16. Adaptive FPGA NoC-based Architecture for Multispectral Image Correlation

    CERN Document Server

    Zhang, Linlin; Fresse, Virginie; Fischer, Viktor

    2009-01-01

    An adaptive FPGA architecture based on the NoC (Network-on-Chip) approach is used for the multispectral image correlation. This architecture must contain several distance algorithms depending on the characteristics of spectral images and the precision of the authentication. The analysis of distance algorithms is required which bases on the algorithmic complexity, result precision, execution time and the adaptability of the implementation. This paper presents the comparison of these distance computation algorithms on one spectral database. The result of a RGB algorithm implementation was discussed.

  17. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Directory of Open Access Journals (Sweden)

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  18. Edge-based correlation image registration for multispectral imaging

    Science.gov (United States)

    Nandy, Prabal [Albuquerque, NM

    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.

  19. Image smoothing of multispectral imagery based on the HNN and geo-statistics

    Institute of Scientific and Technical Information of China (English)

    Nguyen Quang Minh

    2011-01-01

    A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfield Neural Network (HNN) and zero semivariance value is introduced.The method utilises the smoothing effect of the semivariogram matching process to produce the smoothened sub-pixel multispectral (MS) image with smaller RMSEs in comparison with the bilinear interpolation.In fact,the zero semivariograms increase the spatial correlation between the adjacent sub-pixels of the superresolution image.Containing higher spatial correlation,the resulting super-resolution MS image has smaller RMSEs compared with the original coarse image.

  20. [Multispectral Radiation Algorithm Based on Emissivity Model Constraints for True Temperature Measurement].

    Science.gov (United States)

    Liang, Mei; Sun, Xiao-gang; Luan, Mei-sheng

    2015-10-01

    Temperature measurement is one of the important factors for ensuring product quality, reducing production cost and ensuring experiment safety in industrial manufacture and scientific experiment. Radiation thermometry is the main method for non-contact temperature measurement. The second measurement (SM) method is one of the common methods in the multispectral radiation thermometry. However, the SM method cannot be applied to on-line data processing. To solve the problems, a rapid inversion method for multispectral radiation true temperature measurement is proposed and constraint conditions of emissivity model are introduced based on the multispectral brightness temperature model. For non-blackbody, it can be drawn that emissivity is an increasing function in the interval if the brightness temperature is an increasing function or a constant function in a range and emissivity satisfies an inequality of emissivity and wavelength in that interval if the brightness temperature is a decreasing function in a range, according to the relationship of brightness temperatures at different wavelengths. The construction of emissivity assumption values is reduced from multiclass to one class and avoiding the unnecessary emissivity construction with emissivity model constraint conditions on the basis of brightness temperature information. Simulation experiments and comparisons for two different temperature points are carried out based on five measured targets with five representative variation trends of real emissivity. decreasing monotonically, increasing monotonically, first decreasing with wavelength and then increasing, first increasing and then decreasing and fluctuating with wavelength randomly. The simulation results show that compared with the SM method, for the same target under the same initial temperature and emissivity search range, the processing speed of the proposed algorithm is increased by 19.16%-43.45% with the same precision and the same calculation results.

  1. Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

    Science.gov (United States)

    Kemper, Thomas; Gueguen, Lionel; Soille, Pierre

    2012-06-01

    The enumeration of the population remains a critical task in the management of refugee/IDP camps. Analysis of very high spatial resolution satellite data proofed to be an efficient and secure approach for the estimation of dwellings and the monitoring of the camp over time. In this paper we propose a new methodology for the automated extraction of features based on differential morphological decomposition segmentation for feature extraction and interactive training sample selection from the max-tree and min-tree structures. This feature extraction methodology is tested on a WorldView-2 scene of an IDP camp in Darfur Sudan. Special emphasis is given to the additional available bands of the WorldView-2 sensor. The results obtained show that the interactive image information tool is performing very well by tuning the feature extraction to the local conditions. The analysis of different spectral subsets shows that it is possible to obtain good results already with an RGB combination, but by increasing the number of spectral bands the detection of dwellings becomes more accurate. Best results were obtained using all eight bands of WorldView-2 satellite.

  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. Chromaffin cell calcium signal and morphology study based on multispectral images

    Science.gov (United States)

    Wu, Hongxiu; Wei, Shunhui; Qu, Anlian; Zhou, Zhuan

    1998-09-01

    Increasing or decreasing the internal calcium concentration can promote or prevent programmed cell death (PCD). We therefore performed a Ca2+ imaging study using Ca2+ indicator dye fura-2 and a sensitive cooled-CCD camera with a 12 bit resolution. Monochromatic beams of light with a wavelength of 345,380 nm were isolated from light emitted by a xenon lamp using a monochromator. The concentration of free calcium can be directly calculated from the ratio of two fluorescence values taken at two appropriately selected wavelength. Fluorescent light emitted from the cells was capture using a camera system. The cell morphology study is based on multispectral scanning, with smear images provided as three monochromatic images by illumination with light of 610,535 and 470 nm wavelengths. The nuclear characteristic parameters extracted from individual nuclei by system are nuclear area, nuclear diameter, nuclear density vector. The results of the restoration of images and the performance of a primitive logic for the detection of nuclei with PCD proved the usefulness of the system and the advantages of using multispectral images in the restoration and detection procedures.

  4. [Responses of vegetation changes to climatic variations in Panxi area based on the MODIS multispectral data].

    Science.gov (United States)

    Shao, Huai-Yong; Wu, Jin-Hui; Liu, Meng; Yang, Wu-Nian

    2014-01-01

    It is an important research area to quantitatively studying the relationship between global climatic change and vegetation change based on the remote sensing technology. Panxi area is the ecological barrier of the upper reaches of the Yangtze River, and it is essential for the stability of the ecological environment of Sichuan as well as that of the whole China. The present article analyzes the vegetation change in 2001-2008 and the relationship between vegetation change and climatic variations of Panxi area, based on MODIS multispectral data and meteorological data. The results indicate that NDVI is positively correlated with temperature and precipitation. The precipitation is the major factor that affects the change of vegetation in the Panxi region and the trend of NDVI is similar with autumn precipitation; while at the same time the influence of climate has a one-month-time-lag.

  5. Inferential multi-spectral image compression based on distributed source coding

    Science.gov (United States)

    Wu, Xian-yun; Li, Yun-song; Wu, Cheng-ke; Kong, Fan-qiang

    2008-08-01

    Based on the analyses of the interferential multispectral imagery(IMI), a new compression algorithm based on distributed source coding is proposed. There are apparent push motions between the IMI sequences, the relative shift between two images is detected by the block match algorithm at the encoder. Our algorithm estimates the rate of each bitplane with the estimated side information frame. then our algorithm adopts a ROI coding algorithm, in which the rate-distortion lifting procedure is carried out in rate allocation stage. Using our algorithm, the FBC can be removed from the traditional scheme. The compression algorithm developed in the paper can obtain up to 3dB's gain comparing with JPEG2000 and significantly reduce the complexity and storage consumption comparing with 3D-SPIHT at the cost of slight degrade in PSNR.

  6. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  7. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  8. GPU-Based Volume Rendering of Noisy Multi-Spectral Astronomical Data

    CERN Document Server

    Hassan, Amr H; Barnes, David G

    2010-01-01

    Traditional analysis techniques may not be sufficient for astronomers to make the best use of the data sets that current and future instruments, such as the Square Kilometre Array and its Pathfinders, will produce. By utilizing the incredible pattern-recognition ability of the human mind, scientific visualization provides an excellent opportunity for astronomers to gain valuable new insight and understanding of their data, particularly when used interactively in 3D. The goal of our work is to establish the feasibility of a real-time 3D monitoring system for data going into the Australian SKA Pathfinder archive. Based on CUDA, an increasingly popular development tool, our work utilizes the massively parallel architecture of modern graphics processing units (GPUs) to provide astronomers with an interactive 3D volume rendering for multi-spectral data sets. Unlike other approaches, we are targeting real time interactive visualization of datasets larger than GPU memory while giving special attention to data with l...

  9. NSCT-based fusion enhancement for multispectral finger-vein images

    Science.gov (United States)

    Wu, Dongdong; Yang, Jinfeng

    2014-04-01

    Personal identification based on single-spectral finger-vein image has been widely investigated recently. However, in finger-vein imaging, finger-vein image degradation is the main factor causing lower recognition accuracy. So, to improve the finger-vein image quality, in this paper, multispectral finger-vein images (760nm and 850nm) are fused together for contrast enhancement using NSCT transformation. The proposed method can preserve the completeness and sharpness of finger-vein. Experimental results demonstrate that the proposed method is certainly powerful in enhancing finger-vein image contrast and achieves lower equal error rates in finger-vein recognition even if original images have poor contrast.

  10. Study on shallow groundwater information extraction technology based on multi-spectral data and spatial data

    Institute of Scientific and Technical Information of China (English)

    YU DeHao; DENG ZhengDong; LONG Fan; GUAN HongJun; WANG DaQing; GOU YiZheng

    2009-01-01

    Aimed at solving the difficulties, such as low efficiency and limited exploration range encountered in finding groundwater with the traditional methods, a new method was presented by using remote sensing technology in this paper. Based on multi-spectral data (ETM data) and spatial data (SRTM data),a forecasting model was built to produce a probability rating map for finding shallow groundwater in the arid and semi-arid areas. According to investigations, a conclusion is drawn that the results of the model are satisfied, which have been testified by the later geophysical exploration and drilling. Thus,the model can serve as a guide for finding groundwater in the arid and semi-arid regions.

  11. Study on shallow groundwater information extraction technology based on multi-spectral data and spatial data

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Aimed at solving the difficulties,such as low efficiency and limited exploration range encountered in finding groundwater with the traditional methods,a new method was presented by using remote sensing technology in this paper.Based on multi-spectral data(ETM data) and spatial data(SRTM data),a forecasting model was built to produce a probability rating map for finding shallow groundwater in the arid and semi-arid areas.According to investigations,a conclusion is drawn that the results of the model are satisfied,which have been testified by the later geophysical exploration and drilling.Thus,the model can serve as a guide for finding groundwater in the arid and semi-arid regions.

  12. Ground-based multispectral measurements for airborne data verification in non-operating open pit mine "Kremikovtsi"

    Science.gov (United States)

    Borisova, Denitsa; Nikolov, Hristo; Petkov, Doyno

    2013-10-01

    The impact of mining industry and metal production on the environment is presented all over the world. In our research we set focus on the impact of already non-operating ferrous "Kremikovtsi"open pit mine and related waste dumps and tailings which we consider to be the major factor responsible for pollution of one densely populated region in Bulgaria. The approach adopted is based on correct estimation of the distribution of the iron oxides inside open pit mines and the neighboring regions those considered in this case to be the key issue for the ecological state assessment of soils, vegetation and water. For this study the foremost source of data are those of airborne origin and those combined with ground-based in-situ and laboratory acquired data were used for verification of the environmental variables and thus in process of assessment of the present environmental status influenced by previous mining activities. The percentage of iron content was selected as main indicator for presence of metal pollution since it could be reliably identified by multispectral data used in this study and also because the iron compounds are widely spread in the most of the minerals, rocks and soils. In our research the number of samples from every source (air, field, lab) was taken in the way to be statistically sound and confident. In order to establish relationship between the degree of pollution of the soil and mulspectral data 40 soil samples were collected during a field campaign in the study area together with GPS measurements for two types of laboratory measurements: the first one, chemical and mineralogical analysis and the second one, non-destructive spectroscopy. In this work for environmental variables verification over large areas mulspectral satellite data from Landsat instruments TM/ETM+ and from ALI/OLI (Operational Land Imager) were used. Ground-based (laboratory and in-situ) spectrometric measurements were performed using the designed and constructed in Remote

  13. Object-based habitat mapping using very high spatial resolution multispectral and hyperspectral imagery with LiDAR data

    Science.gov (United States)

    Onojeghuo, Alex Okiemute; Onojeghuo, Ajoke Ruth

    2017-07-01

    This study investigated the combined use of multispectral/hyperspectral imagery and LiDAR data for habitat mapping across parts of south Cumbria, North West England. The methodology adopted in this study integrated spectral information contained in pansharp QuickBird multispectral/AISA Eagle hyperspectral imagery and LiDAR-derived measures with object-based machine learning classifiers and ensemble analysis techniques. Using the LiDAR point cloud data, elevation models (such as the Digital Surface Model and Digital Terrain Model raster) and intensity features were extracted directly. The LiDAR-derived measures exploited in this study included Canopy Height Model, intensity and topographic information (i.e. mean, maximum and standard deviation). These three LiDAR measures were combined with spectral information contained in the pansharp QuickBird and Eagle MNF transformed imagery for image classification experiments. A fusion of pansharp QuickBird multispectral and Eagle MNF hyperspectral imagery with all LiDAR-derived measures generated the best classification accuracies, 89.8 and 92.6% respectively. These results were generated with the Support Vector Machine and Random Forest machine learning algorithms respectively. The ensemble analysis of all three learning machine classifiers for the pansharp QuickBird and Eagle MNF fused data outputs did not significantly increase the overall classification accuracy. Results of the study demonstrate the potential of combining either very high spatial resolution multispectral or hyperspectral imagery with LiDAR data for habitat mapping.

  14. Multispectral information hiding in RGB image using bit-plane-based watermarking and its application

    Science.gov (United States)

    Shinoda, Kazuma; Watanabe, Aya; Hasegawa, Madoka; Kato, Shigeo

    2015-06-01

    Although it was expected that multispectral images would be implemented in many applications, such as remote sensing and medical imaging, their use has not been widely diffused in these fields. The development of a compact multispectral camera and display will be needed for practical use, but the format compatibility between multispectral and RGB images is also important for reducing the introduction cost and having high usability. We propose a method of embedding the spectral information into an RGB image by watermarking. The RGB image is calculated from the multispectral image, and then, the original multispectral image is estimated from the RGB image using Wiener estimation. The residual data between the original and the estimated multispectral image are compressed and embedded in the lower bit planes of the RGB image. The experimental results show that, as compared with Wiener estimation, the proposed method leads to more than a 10 dB gain in the peak signal-to-noise ratio of the reconstructed multispectral image, while there are almost no significant perceptual differences in the watermarked RGB image.

  15. Water Quality Determination of Küçükçekmece Lake, Turkey by Using Multispectral Satellite Data

    Directory of Open Access Journals (Sweden)

    Erhan Alparslan

    2009-01-01

    Full Text Available This study focuses on the analysis of the Landsat-5 TM + SPOT-Pan (1992, IRS-1C/D LISS + Pan (2000, and Landsat-5 TM (2006 satellite images that reflect the drastic land use/land cover changes in the Küçükçekmece Lake region, Istanbul. Landsat-5 TM satellite data dated 2006 was used for mapping water quality. A multiple regression analysis was carried out between the unitless planetary reflectance values derived from the satellite image and in situ water quality parameters chlorophyll a, total phosphorus, total nitrogen, turbidity, and biological and chemical oxygen demand measured at a number of stations homogenously distributed over the lake surface. The results of this study provided valuable information to local administrators on the water quality of Küçükçekmece Lake, which is a large water resource of the Istanbul Metropolitan Area. Results also show that such a methodology structured by use of reflectance values provided from satellite imagery, in situ water quality measurements, and basin land use/land cover characteristics obtained from images can serve as a powerful and rapid monitoring tool for the drinking water basins that suffer from rapid urbanization and pollution, all around the world.

  16. Satellite-based enhancement of archaeological marks through data fusion techniques

    Science.gov (United States)

    Lasaponara, Rosa; Masini, Nicola; Aiazzi, Bruno; Alparone, Luciano; Baronti, Stefano

    2008-10-01

    The application of space technology to archaeological research has been paid great attention worldwide, mainly because the current availability of very high resolution (VHR) satellite imagery, such as, IKONOS (1999) and QuickBird (2001), provide valuable data for searching large areas to find potential archaeological sites. Data from VHR satellite can be very useful for the identification, management and documentation of archaeological resources. Archaeological investigation based on the use of VHR satellite images may take benefits from the integration and synergic use of both panchromatic and multispectral data. This can be achieved by using pansharpening techniques, which allow multispectral and panchromatic images to be merged. The two basic frameworks of pansharpening techniques are Component Substitution (CS), such as Intensity-Hue-Saturation (IHS) Gram-Schmidt (GS), and multiresolution analysis (MRA), such as wavelets and Laplacian pyramids (LP). In this paper, both Gram-Schmidt and Laplacian pyramids with context adaptive (CA) detail injection models were used. QB images were processed for a relevant archaeological area in Southern Italy, the ancient Siris-Heraclea, a very significant test area because it is characterized by the presence of both surface and subsurface ancient remains. Outcomes of different pansharpening techniques have been qualitatively evaluated for both surface and subsurface remains. The visual inspection clearly suggests that the quantitative evaluation of the fusion performance for archaeological applications is a critical issue, and "ad hoc" local (i.e. context-adaptive) indices need to be developed.

  17. Potential of multispectral synergism for observing ozone pollution by combining IASI-NG and UVNS measurements from the EPS-SG satellite

    Science.gov (United States)

    Costantino, Lorenzo; Cuesta, Juan; Emili, Emanuele; Coman, Adriana; Foret, Gilles; Dufour, Gaëlle; Eremenko, Maxim; Chailleux, Yohann; Beekmann, Matthias; Flaud, Jean-Marie

    2017-04-01

    Present and future satellite observations offer great potential for monitoring air quality on a daily and global basis. However, measurements from currently orbiting satellites do not allow a single sensor to accurately probe surface concentrations of gaseous pollutants such as tropospheric ozone. Combining information from IASI (Infrared Atmospheric Sounding Interferometer) and GOME-2 (Global Ozone Monitoring Experiment-2) respectively in the TIR and UV spectra, a recent multispectral method (referred to as IASI+GOME-2) has shown enhanced sensitivity for probing ozone in the lowermost troposphere (LMT, below 3 km altitude) with maximum sensitivity down to 2.20 km a.s.l. over land, while sensitivity for IASI or GOME-2 alone only peaks at 3 to 4 km at the lowest.In this work we develop a pseudo-observation simulator and evaluate the potential of future EPS-SG (EUMETSAT Polar System - Second Generation) satellite observations, from new-generation sensors IASI-NG (Infrared Atmospheric Sounding Interferometer - New Generation) and UVNS (Ultraviolet Visible Near-infrared Shortwave-infrared), to observe near-surface O3 through the IASI-NG+UVNS multispectral method. The pseudo-real state of the atmosphere is provided by the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Échelle) chemical transport model. We perform full and accurate forward and inverse radiative transfer calculations for a period of 4 days (8-11 July 2010) over Europe.In the LMT, there is a remarkable agreement in the geographical distribution of O3 partial columns between IASI-NG+UVNS pseudo-observations and the corresponding MOCAGE pseudo-reality. With respect to synthetic IASI+GOME-2 products, IASI-NG+UVNS shows a higher correlation between pseudo-observations and pseudo-reality, which is enhanced by about 12 %. The bias on high ozone retrieval is reduced and the average accuracy increases by 22 %. The sensitivity to LMT ozone is also enhanced. On average, the degree of freedom for signal is

  18. Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition.

    Science.gov (United States)

    Park, Chulhee; Kang, Moon Gi

    2016-05-18

    A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors.

  19. High Resolution Multispectral and Thermal Remote Sensing-Based Water Stress Assessment in Subsurface Irrigated Grapevines

    Directory of Open Access Journals (Sweden)

    Carlos Zúñiga Espinoza

    2017-09-01

    Full Text Available Precision irrigation management is based on the accuracy and feasibility of sensor data assessing the plant water status. Multispectral and thermal infrared images acquired from an unmanned aerial vehicle (UAV were analyzed to evaluate the applicability of the data in the assessment of variants of subsurface irrigation configurations. The study was carried out in a Cabernet Sauvignon orchard located near Benton City, Washington. Plants were subsurface irrigated at a 30, 60, and 90 cm depth, with 15%, 30%, and 60% irrigation of the standard irrigation level as determined by the grower in commercial production management. Half of the plots were irrigated using pulse irrigation and the other half using continuous irrigation techniques. The treatments were compared to the control plots that received standard surface irrigation at a continuous rate. The results showed differences in fruit yield when the control was compared to deficit irrigated treatments (15%, 30%, 60% of standard irrigation, while no differences were found for comparisons of the techniques (pulse, continuous or depths of irrigation (30, 60, 90 cm. Leaf stomatal conductance of control and 60% irrigation treatments were statistically different compared to treatments receiving 30% and 15% irrigation. The normalized difference vegetation index (NDVI, green normalized difference vegetation index (GNDVI, and canopy temperature were correlated to fruit yield and leaf stomatal conductance. Significant correlations (p < 0.01 were observed between NDVI, GNDVI, and canopy temperature with fruit yield (Pearson’s correlation coefficient, r = 0.68, 0.73, and −0.83, respectively, and with leaf stomatal conductance (r = 0.56, 0.65, and −0.63, respectively at 44 days before harvest. This study demonstrates the potential of using low-altitude multispectral and thermal imagery data in the assessment of irrigation techniques and relative degree of plant water stress. In addition, results provide

  20. An Airborne Multispectral Imaging System Based on Two Consumer-Grade Cameras for Agricultural Remote Sensing

    Directory of Open Access Journals (Sweden)

    Chenghai Yang

    2014-06-01

    Full Text Available This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS sensor with 5616 × 3744 pixels. One camera captures normal color images, while the other is modified to obtain near-infrared (NIR images. The color camera is also equipped with a GPS receiver to allow geotagged images. A remote control is used to trigger both cameras simultaneously. Images are stored in 14-bit RAW and 8-bit JPEG files in CompactFlash cards. The second-order transformation was used to align the color and NIR images to achieve subpixel alignment in four-band images. The imaging system was tested under various flight and land cover conditions and optimal camera settings were determined for airborne image acquisition. Images were captured at altitudes of 305–3050 m (1000–10,000 ft and pixel sizes of 0.1–1.0 m were achieved. Four practical application examples are presented to illustrate how the imaging system was used to estimate cotton canopy cover, detect cotton root rot, and map henbit and giant reed infestations. Preliminary analysis of example images has shown that this system has potential for crop condition assessment, pest detection, and other agricultural applications.

  1. 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...

  2. A Space Based Solar Power Satellite System

    Science.gov (United States)

    Engel, J. M.; Polling, D.; Ustamujic, F.; Yaldiz, R.; et al.

    2002-01-01

    (SPoTS) supplying other satellites with energy. SPoTS is due to be commercially viable and operative in 2020. of Technology designed the SPoTS during a full-time design period of six weeks as a third year final project. The team, organized according to the principles of systems engineering, first conducted a literature study on space wireless energy transfer to select the most suitable candidates for use on the SPoTS. After that, several different system concepts have been generated and evaluated, the most promising concept being worked out in greater detail. km altitude. Each SPoTS satellite has a 50m diameter inflatable solar collector that focuses all received sunlight. Then, the received sunlight is further redirected by means of four pointing mirrors toward four individual customer satellites. A market-analysis study showed, that providing power to geo-stationary communication satellites during their eclipse would be most beneficial. At arrival at geo-stationary orbit, the focused beam has expended to such an extent that its density equals one solar flux. This means that customer satellites can continue to use their regular solar arrays during their eclipse for power generation, resulting in a satellite battery mass reduction. the customer satellites in geo-stationary orbit, the transmitted energy beams needs to be pointed with very high accuracy. Computations showed that for this degree of accuracy, sensors are needed, which are not mainstream nowadays. Therefore further research must be conducted in this area in order to make these high-accuracy-pointing systems commercially attractive for use on the SPoTS satellites around 2020. Total 20-year system lifetime cost for 18 SPoT satellites are estimated at approximately USD 6 billion [FY2001]. In order to compete with traditional battery-based satellite power systems or possible ground based wireless power transfer systems the price per kWh for the customer must be significantly lower than the present one

  3. Multi-spectral image enhancement algorithm based on keeping original gray level

    Science.gov (United States)

    Wang, Tian; Xu, Linli; Yang, Weiping

    2016-11-01

    Characteristics of multi-spectral imaging system and the image enhancement algorithm are introduced.Because histogram equalization and some other image enhancement will change the original gray level,a new image enhancement algorithm is proposed to maintain the gray level.For this paper, we have chosen 6 narrow-bands multi-spectral images to compare,the experimental results show that the proposed method is better than those histogram equalization and other algorithm to multi-spectral images.It also insures that histogram information contained in original features is preserved and guarantees to make use of data class information.What's more,on the combination of subjective and objective sharpness evaluation,details of the images are enhanced and noise is weaken.

  4. 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.

  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...

  6. Satellite Formation based on SDDF Method

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2014-04-01

    Full Text Available The technology of satellite formation flying has being a research focus in flight application. The relative position and velocity between satellites are basic parameters to achieve the control of formation flight during the satellite formation flying mission. In order to improve the navigation accuracy, a new filter different from Extended Kalman Filter (EKF should be adopted to estimate the errors of relative position and velocity, which is based on the nonlinearity of the kinetic model for the satellite formation flying. A nonlinear Divided Difference Filter (DDF based on Stirling interpolation formula was proposed in this paper. According to the linearity of the measurement equation for the filter, a simplified differential filter was designed by means of expanding the polynomial of the nonlinear system equation and linear approximating of the finite differential interpolation. Digital simulation experiment for the relative positioning of satellite formation flying was carried out. The result demonstrates that the filter proposed in this paper has a higher filtering accuracy, faster convergence speed and better stability. Compared with the EKF, the estimation accuracy of the relative position and velocity has improved by 77.1%and 47% respectively in the method of simplified DDF, which indicates the significance for practical applications. 

  7. Multispectral imaging system based on laser-induced fluorescence for security applications

    Science.gov (United States)

    Caneve, L.; Colao, F.; Del Franco, M.; Palucci, A.; Pistilli, M.; Spizzichino, V.

    2016-10-01

    The development of portable sensors for fast screening of crime scenes is required to reduce the number of evidences useful to be collected, optimizing time and resources. Laser based spectroscopic techniques are good candidates to this scope due to their capability to operate in field, in remote and rapid way. In this work, the prototype of a multispectral imaging LIF (Laser Induced Fluorescence) system able to detect evidence of different materials on large very crowded and confusing areas at distances up to some tens of meters will be presented. Data collected as both 2D fluorescence images and LIF spectra are suitable to the identification and the localization of the materials of interest. A reduced scan time, preserving at the same time the accuracy of the results, has been taken into account as a main requirement in the system design. An excimer laser with high energy and repetition rate coupled to a gated high sensitivity ICCD assures very good performances for this purpose. Effort has been devoted to speed up the data processing. The system has been tested in outdoor and indoor real scenarios and some results will be reported. Evidence of the plastics polypropylene (PP) and polyethilene (PE) and polyester have been identified and their localization on the examined scenes has been highlighted through the data processing. By suitable emission bands, the instrument can be used for the rapid detection of other material classes (i.e. textiles, woods, varnishes). The activities of this work have been supported by the EU-FP7 FORLAB project (Forensic Laboratory for in-situ evidence analysis in a post blast scenario).

  8. Coordinated Ground- and Space-based Multispectral Campaign to Study Equatorial Spread-F Formation

    Science.gov (United States)

    Finn, S. C.; Geddes, G.; Aryal, S.; Stephan, A. W.; Budzien, S. A.; Duggirala, P. R.; Chakrabarti, S.; Valladares, C.

    2016-12-01

    We present a concept for a multispectral campaign using coordinated data from state-of-the-art instruments aboard the International Space Station (ISS) and multiple ground-based spectrometers and digisondes deployed at low-latitudes to study the formation and development of Equatorial Spread-F (ESF). This extended observational campaign utilizes ultraviolet, visible, and radio measurements to develop a predictive capability for ESF and to study the coupling of the ionosphere-thermosphere (I-T) system during geomagnetically quiet and disturbed times. The ground-based instruments will be deployed in carefully chosen locations in the American and Indian sectors while the space-based data will provide global coverage spanning all local times and longitudes within ±51° geographic latitudes. The campaign, over an extended period covering a range of geophysical conditions, will provide the extensive data base necessary to address the important science questions. The space-based instrument suite consists of the Limb-imaging Ionospheric and Thermospheric Extreme-ultraviolet Spectrograph (LITES) and the GPS Radio Occultation and Ultraviolet Photometry-Colocated (GROUP-C) instruments, scheduled to launch to the ISS in November 2016. LITES is a compact imaging spectrograph for remote sensing of the upper atmosphere and ionosphere from 60 to 140nm and GROUP-C has a nadir-viewing FUV photometer. The ground-based instruments to be deployed for this campaign are three high-resolution imaging spectrographs capable of continuous round-the-clock airglow observations: Multiwavelength Imaging Spectrograph using Echelle grating (MISE) in India and two High Throughput and Multi-slit Imaging Spectrographs (HiT&MIS) to be deployed in Colombia and Argentina, the Low-Latitude Ionosphere Sensor Network (LISN), and the Global Ionospheric Radio Observatory (GIRO) digisondes network. We present data from the ground-based instruments, initial results from the LITES and GROUP-C instruments on

  9. Satellite-based terrestrial production efficiency modeling

    Directory of Open Access Journals (Sweden)

    Obersteiner Michael

    2009-09-01

    Full Text Available Abstract Production efficiency models (PEMs are based on the theory of light use efficiency (LUE which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP monitoring. The objectives of this review are as follows: 1 to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS identified in the literature; 2 to review each model to determine potential improvements to the general PEM methodology; 3 to review the related literature on satellite-based gross primary productivity (GPP and NPP modeling for additional possibilities for improvement; and 4 based on this review, propose items for coordinated research. This review noted a number of possibilities for improvement to the general PEM architecture - ranging from LUE to meteorological and satellite-based inputs. Current PEMs tend to treat the globe similarly in terms of physiological and meteorological factors, often ignoring unique regional aspects. Each of the existing PEMs has developed unique methods to estimate NPP and the combination of the most successful of these could lead to improvements. It may be beneficial to develop regional PEMs that can be combined under a global framework. The results of this review suggest the creation of a hybrid PEM could bring about a significant enhancement to the PEM methodology and thus terrestrial carbon flux modeling. Key items topping the PEM research agenda identified in this review include the following: LUE should not be assumed constant, but should vary by plant functional type (PFT or photosynthetic pathway; evidence is mounting that PEMs should consider incorporating diffuse radiation; continue to pursue relationships between satellite-derived variables and LUE, GPP and autotrophic respiration (Ra; there is an urgent need for

  10. Simultaneous denoising and compression of multispectral images

    Science.gov (United States)

    Hagag, Ahmed; Amin, Mohamed; Abd El-Samie, Fathi E.

    2013-01-01

    A new technique for denoising and compression of multispectral satellite images to remove the effect of noise on the compression process is presented. One type of multispectral images has been considered: Landsat Enhanced Thematic Mapper Plus. The discrete wavelet transform (DWT), the dual-tree DWT, and a simple Huffman coder are used in the compression process. Simulation results show that the proposed technique is more effective than other traditional compression-only techniques.

  11. Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island

    OpenAIRE

    Heleno, Sandra; Matias, Magda; Pina, Pedro , (O.F.M.); sousa, António Jorge

    2016-01-01

    A method for semiautomated landslide detection and mapping, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a support vector machine classifier and is tested using a GeoEye-1 multispectral image, sensed 3 days after a major damaging landslide event that occurred on Madeira Island (20 February 2010), and a pre-event lidar digital terrain model. The testing is developed in a 15 km2 wide study area,...

  12. 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....

  13. Satellite Contamination and Materials Outgassing Knowledge base

    Science.gov (United States)

    Minor, Jody L.; Kauffman, William J. (Technical Monitor)

    2001-01-01

    Satellite contamination continues to be a design problem that engineers must take into account when developing new satellites. To help with this issue, NASA's Space Environments and Effects (SEE) Program funded the development of the Satellite Contamination and Materials Outgassing Knowledge base. This engineering tool brings together in one location information about the outgassing properties of aerospace materials based upon ground-testing data, the effects of outgassing that has been observed during flight and measurements of the contamination environment by on-orbit instruments. The knowledge base contains information using the ASTM Standard E- 1559 and also consolidates data from missions using quartz-crystal microbalances (QCM's). The data contained in the knowledge base was shared with NASA by government agencies and industry in the US and international space agencies as well. The term 'knowledgebase' was used because so much information and capability was brought together in one comprehensive engineering design tool. It is the SEE Program's intent to continually add additional material contamination data as it becomes available - creating a dynamic tool whose value to the user is ever increasing. The SEE Program firmly believes that NASA, and ultimately the entire contamination user community, will greatly benefit from this new engineering tool and highly encourages the community to not only use the tool but add data to it as well.

  14. Comparison of the Distribution of Morphological Disorganization of Pigmented Lesions in a Community-based Practice versus a University-based Clinical Setting as Measured by a Multispectral Digital Skin Lesion Analysis Device: Impact on Diagnosis.

    Science.gov (United States)

    Winkelmann, Richard R; Nikolaidis, Gregory; Rigel, Darrell S; Tucker, Natalie; Speck, Laura

    2015-02-01

    To observe how a multispectral digital skin lesion analysis device was used by dermatologists in a community-based clinical setting and determine differences from a university-based environment. Use of multispectral digital skin lesion analysis was incorporated into a community-based practice by 12 dermatologists across six clinics over seven consecutive days with the data provided by the device integrated as an adjuvant to their clinical evaluation for their pigmented lesion management decisions. Multispectral digital skin lesion analysis results were collected electronically for lesions prior to biopsy, and histopathological evaluation was performed for the biopsied lesions. Multispectral digital skin lesion analysis and pathology results were then compared to assess the degree of morphological disorganization. Study of 160 consecutive patients in community-based clinical setting. Proportion of "low" and "high" disorganization lesions identified by multispectral digital skin lesion analysis. Of the 344 pigmented skin lesions analyzed by multispectral digital skin lesion analysis, 255 were high disorganization, 113 of which were biopsied. Of the 89 lesions evaluated by multispectral digital skin lesion analysis to be low disorganization, seven were biopsied and all pathology was benign. Data demonstrate a higher rate of multispectral digital skin lesion analysis low disorganization readings for pigmented skin lesions (32% for single use per patient lesions, plesions, plesions clinics providing data for the university-based clinical study (10%). Multispectral digital skin lesion analysis in the community-based clinical setting may outperform specificity results from the university-based clinical trial study, perhaps because of a higher proportion of subtle lesions encountered at high-risk pigmented lesion clinics of participating major academic centers as compared with those in a community-based practice setting.

  15. 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.

  16. Multispectral Image Feature Points

    Directory of Open Access Journals (Sweden)

    Cristhian Aguilera

    2012-09-01

    Full Text Available This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  17. SPLASSH: Open source software for camera-based high-speed, multispectral in-vivo optical image acquisition.

    Science.gov (United States)

    Sun, Ryan; Bouchard, Matthew B; Hillman, Elizabeth M C

    2010-08-02

    Camera-based in-vivo optical imaging can provide detailed images of living tissue that reveal structure, function, and disease. High-speed, high resolution imaging can reveal dynamic events such as changes in blood flow and responses to stimulation. Despite these benefits, commercially available scientific cameras rarely include software that is suitable for in-vivo imaging applications, making this highly versatile form of optical imaging challenging and time-consuming to implement. To address this issue, we have developed a novel, open-source software package to control high-speed, multispectral optical imaging systems. The software integrates a number of modular functions through a custom graphical user interface (GUI) and provides extensive control over a wide range of inexpensive IEEE 1394 Firewire cameras. Multispectral illumination can be incorporated through the use of off-the-shelf light emitting diodes which the software synchronizes to image acquisition via a programmed microcontroller, allowing arbitrary high-speed illumination sequences. The complete software suite is available for free download. Here we describe the software's framework and provide details to guide users with development of this and similar software.

  18. Integrating Indian remote sensing multi-spectral satellite and field data to estimate seagrass cover change in the Andaman and Nicobar Islands, India

    Science.gov (United States)

    Paulose, Nobi Elavumkudi; Dilipan, Elangovan; Thangaradjou, Thirunavukarassu

    2013-06-01

    Environmental resource managers and policy makers require a reliable tool to quickly assess the spatial extent of any natural resources, including seagrasses, in order to develop management plans. Even small natural or anthropogenic disturbances can cause severe changes in the distributional pattern of seagrass meadows. Satellite imageries provide a suitable means to detect and assess such changes in space and time in remote and inaccessible areas. Present study aims to understand the distribution pattern of seagrasses after the Indian Ocean Tsunami in 2004 with the help of Indian Remote Sensing satellite data and in situ ground surveys with hand held GPS. As no geospatial data bases were available for the pre-tsunami period, the changes in seagrass cover were compared with the ground estimates available in the literature and also using pre-tsunami satellite data sets. The study found severe loss of seagrasses in the northern Andaman particularly in the Interview and North reef islands and in the Nicobar group of islands including Great Nicobar and Trinket islands. The investigation revealed the presence of 2,943.38 ha of seagrass covering the entire Andaman and Nicobar islands, and that 1,619.41 ha of seagrasses had been denuded during this period. The earthquake and subsequent tsunami in 2004 was the major reason for the loss of seagrasses in these islands. The seagrass spatial map generated in the present study can be used for the development of conservation and management plans and also to restore the denuded seagrasses of this region.

  19. [Hard and soft classification method of multi-spectral remote sensing image based on adaptive thresholds].

    Science.gov (United States)

    Hu, Tan-Gao; Xu, Jun-Feng; Zhang, Deng-Rong; Wang, Jie; Zhang, Yu-Zhou

    2013-04-01

    Hard and soft classification techniques are the conventional methods of image classification for satellite data, but they have their own advantages and drawbacks. In order to obtain accurate classification results, we took advantages of both traditional hard classification methods (HCM) and soft classification models (SCM), and developed a new method called the hard and soft classification model (HSCM) based on adaptive threshold calculation. The authors tested the new method in land cover mapping applications. According to the results of confusion matrix, the overall accuracy of HCM, SCM, and HSCM is 71.06%, 67.86%, and 71.10%, respectively. And the kappa coefficient is 60.03%, 56.12%, and 60.07%, respectively. Therefore, the HSCM is better than HCM and SCM. Experimental results proved that the new method can obviously improve the land cover and land use classification accuracy.

  20. Satellite-based Tropical Cyclone Monitoring Capabilities

    Science.gov (United States)

    Hawkins, J.; Richardson, K.; Surratt, M.; Yang, S.; Lee, T. F.; Sampson, C. R.; Solbrig, J.; Kuciauskas, A. P.; Miller, S. D.; Kent, J.

    2012-12-01

    Satellite remote sensing capabilities to monitor tropical cyclone (TC) location, structure, and intensity have evolved by utilizing a combination of operational and research and development (R&D) sensors. The microwave imagers from the operational Defense Meteorological Satellite Program [Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS)] form the "base" for structure observations due to their ability to view through upper-level clouds, modest size swaths and ability to capture most storm structure features. The NASA TRMM microwave imager and precipitation radar continue their 15+ yearlong missions in serving the TC warning and research communities. The cessation of NASA's QuikSCAT satellite after more than a decade of service is sorely missed, but India's OceanSat-2 scatterometer is now providing crucial ocean surface wind vectors in addition to the Navy's WindSat ocean surface wind vector retrievals. Another Advanced Scatterometer (ASCAT) onboard EUMETSAT's MetOp-2 satellite is slated for launch soon. Passive microwave imagery has received a much needed boost with the launch of the French/Indian Megha Tropiques imager in September 2011, basically greatly supplementing the very successful NASA TRMM pathfinder with a larger swath and more frequent temporal sampling. While initial data issues have delayed data utilization, current news indicates this data will be available in 2013. Future NASA Global Precipitation Mission (GPM) sensors starting in 2014 will provide enhanced capabilities. Also, the inclusion of the new microwave sounder data from the NPP ATMS (Oct 2011) will assist in mapping TC convective structures. The National Polar orbiting Partnership (NPP) program's VIIRS sensor includes a day night band (DNB) with the capability to view TC cloud structure at night when sufficient lunar illumination exits. Examples highlighting this new capability will be discussed in concert with additional data fusion efforts.

  1. 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

  2. Spatio-temporal monitoring of cotton cultivation using ground-based and airborne multispectral sensors in GIS environment.

    Science.gov (United States)

    Papadopoulos, Antonis; Kalivas, Dionissios; Theocharopoulos, Sid

    2017-07-01

    Multispectral sensor capability of capturing reflectance data at several spectral channels, together with the inherent reflectance responses of various soils and especially plant surfaces, has gained major interest in crop production. In present study, two multispectral sensing systems, a ground-based and an aerial-based, were applied for the multispatial and temporal monitoring of two cotton fields in central Greece. The ground-based system was Crop Circle ACS-430, while the aerial consisted of a consumer-level quadcopter (Phantom 2) and a modified Hero3+ Black digital camera. The purpose of the research was to monitor crop growth with the two systems and investigate possible interrelations between the derived well-known normalized difference vegetation index (NDVI). Five data collection campaigns were conducted during the cultivation period and concerned scanning soil and plants with the ground-based sensor and taking aerial photographs of the fields with the unmanned aerial system. According to the results, both systems successfully monitored cotton growth stages in terms of space and time. The mean values of NDVI changes through time as retrieved by the ground-based system were satisfactorily modelled by a second-order polynomial equation (R (2) 0.96 in Field 1 and 0.99 in Field 2). Further, they were highly correlated (r 0.90 in Field 1 and 0.74 in Field 2) with the according values calculated via the aerial-based system. The unmanned aerial system (UAS) can potentially substitute crop scouting as it concerns a time-effective, non-destructive and reliable way of soil and plant monitoring.

  3. Digital preprocessing and classification of multispectral earth observation data

    Science.gov (United States)

    Anuta, P. E.

    1976-01-01

    The development of airborne and satellite multispectral image scanning sensors has generated wide-spread interest in application of these sensors to earth resource mapping. These point scanning sensors permit scenes to be imaged in a large number of electromagnetic energy bands between .3 and 15 micrometers. The energy sensed in each band can be used as a feature in a computer based multi-dimensional pattern recognition process to aid in interpreting the nature of elements in the scene. Images from each band can also be interpreted visually. Visual interpretation of five or ten multispectral images simultaneously becomes impractical especially as area studied increases; hence, great emphasis has been placed on machine (computer) techniques for aiding in the interpretation process. This paper describes a computer software system concept called LARSYS for analysis of multivariate image data and presents some examples of its application.

  4. Improved tunable filter-based multispectral imaging system for detection of blood stains on construction material substrates

    Science.gov (United States)

    Janchaysang, Suwatwong; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

    2013-06-01

    We present the improved tunable filter based multispectral imaging system for detecting blood stains on construction materials. Based upon the reflectance and Kubelka Munk absorbance spectra stocked from our previous work, we modify the blood discrimination criteria to make the system more efficient by replacing the old criteria which make use of polynomial fitting with new criteria associated with a few wavelengths images. The newly established criteria are tested to be able to detect blood against other stains almost as efficient as the old criteria, while the number of spectral images required for detecting blood stains are reduced significantly from 64 to 9 spectral images. The reduction of required spectral images will reduce the time needed for image capturing and blood detection criteria application with little sacrificing of the specificity and sensitivity of the system.

  5. Mapping shrublands and forests with multispectral satellite images based on spectral unmixing of scene components

    Science.gov (United States)

    Caetano, Mario R.; Oliveira, Tiago; Paul, Jose U.; Vasconcelos, Maria J.; Cardoso Pereira, Jose M.

    1997-12-01

    Linear spectral mixture models (SMM) with image endmembers (IEM) and with reference endmembers (REM) were tested for discriminating maritime pine stands and shrublands in a Landsat-TM image of Central Portugal. For both types of EM, IEM and REM, two types of SMM were tried: SMM with three EM (SMM-3), i.e., green vegetation, soil and shade, and SMM with five EM (SMM-5), where the EM were the components of the landscapes that we were interested on, i.e., pine canopy, shrub, soil, forest litter and shade. Results showed that in the SMM-5, REM need to be used, since IEM were not pure enough. We verified that in the SMM-5, there was not a single set of EM that could be applied to the whole study area, because the shrubs that exist underneath the pine canopy and in the shrublands could not be modeled just by using a shrub EM. Therefore, SMM-5 require a multi-endmember approach, where the set of EM may change from pixel to pixel. In the SMM-3, an accurate discrimination of shrublands and pine stands (90% accuracy) was achieved by thresholding the shade fraction. In these simpler SMM, IEM and REM produced similar results.

  6. Monitoring objects orbiting earth using satellite-based telescopes

    Energy Technology Data Exchange (ETDEWEB)

    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.

  7. Recent Developments for Satellite-Based Fire Monitoring in Canada

    Science.gov (United States)

    Abuelgasim, A.; Fraser, R.

    2002-05-01

    Wildfires in Canadian forests are a major source of natural disturbance. These fires have a tremendous impact on the local environment, humans and wildlife, ecosystem function, weather, and climate. Approximately 9000 fires burn 3 million hectares per year in Canada (based on a 10-year average). While only 2 to 3 percent of these wildfires grow larger than 200 hectares in size, they account for almost 97 percent of the annual area burned. This provides an excellent opportunity to monitor active fires using a combination of low and high resolution sensors for the purpose of determining fire location and burned areas. Given the size of Canada, the use of remote sensing data is a cost-effective way to achieve a synoptic overview of large forest fire activity in near-real time. In 1998 the Canada Centre for Remote Sensing (CCRS) and the Canadian Forest Service (CFS) developed a system for Fire Monitoring, Mapping and Modelling (Fire M3;http://fms.nofc.cfs.nrcan.gc.ca/FireM3/). Fire M3 automatically identifies, monitors, and maps large forest fires on a daily basis using NOAA AVHRR data. These data are processed daily using the GEOCOMP-N satellite image processing system. This presentation will describe recent developments to Fire M3, included the addition of a set of algorithms tailored for NOAA-16 (N-16) data. The two fire detection algorithms are developed for N-16 day and night-time daily data collection. The algorithms exploit both the multi-spectral and thermal information from the AVHRR daily images. The set of N-16 day and night algorithms was used to generate daily active fire maps across North America for the 2001 fire season. Such a combined approach for fire detection leads to an improved detection rate, although day-time detection based on the new 1.6 um channel was much less effective (note - given the low detection rate with day time imagery, I don't think we can make the statement about capturing the diurnal cycle). Selected validation sites in western

  8. Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island

    Science.gov (United States)

    Heleno, Sandra; Matias, Magda; Pina, Pedro; Sousa, António Jorge

    2016-04-01

    A method for semiautomated landslide detection and mapping, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a support vector machine classifier and is tested using a GeoEye-1 multispectral image, sensed 3 days after a major damaging landslide event that occurred on Madeira Island (20 February 2010), and a pre-event lidar digital terrain model. The testing is developed in a 15 km2 wide study area, where 95 % of the number of landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area, with commission errors below 26 % and omission errors below 24 %. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier, east-facing slopes.

  9. Automated object-based classification of rain-induced landslides with VHR multispectral images in Madeira Island

    Science.gov (United States)

    Heleno, S.; Matias, M.; Pina, P.; Sousa, A. J.

    2015-09-01

    A method for semi-automatic landslide detection, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a Support Vector Machine classifier on a GeoEye-1 multispectral image, sensed 3 days after the major damaging landslide event that occurred in Madeira island (20 February 2010), with a pre-event LIDAR Digital Elevation Model. The testing is developed in a 15 km2-wide study area, where 95 % of the landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier east facing-slopes.

  10. Utilizing SAR and Multispectral Integrated Data for Emergency Response

    Science.gov (United States)

    Havivi, S.; Schvartzman, I.; Maman, S.; Marinoni, A.; Gamba, P.; Rotman, S. R.; Blumberg, D. G.

    2016-06-01

    Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar) these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD) for SAR data and Covariance Equalization (CE) for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX) and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a complete scene for

  11. UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

    Directory of Open Access Journals (Sweden)

    S. Havivi

    2016-06-01

    Full Text Available Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD for SAR data and Covariance Equalization (CE for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a

  12. Earth Observation Satellites Scheduling Based on Decomposition Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Feng Yao

    2010-11-01

    Full Text Available A decomposition-based optimization algorithm was proposed for solving Earth Observation Satellites scheduling problem. The problem was decomposed into task assignment main problem and single satellite scheduling sub-problem. In task assignment phase, the tasks were allocated to the satellites, and each satellite would schedule the task respectively in single satellite scheduling phase. We adopted an adaptive ant colony optimization algorithm to search the optimal task assignment scheme. Adaptive parameter adjusting strategy and pheromone trail smoothing strategy were introduced to balance the exploration and the exploitation of search process. A heuristic algorithm and a very fast simulated annealing algorithm were proposed to solve the single satellite scheduling problem. The task assignment scheme was valued by integrating the observation scheduling result of multiple satellites. The result was responded to the ant colony optimization algorithm, which can guide the search process of ant colony optimization. Computation results showed that the approach was effective to the satellites observation scheduling problem.

  13. SAW based systems for mobile communications satellites

    Science.gov (United States)

    Peach, R. C.; Miller, N.; Lee, M.

    1993-01-01

    Modern mobile communications satellites, such as INMARSAT 3, EMS, and ARTEMIS, use advanced onboard processing to make efficient use of the available L-band spectrum. In all of these cases, high performance surface acoustic wave (SAW) devices are used. SAW filters can provide high selectivity (100-200 kHz transition widths), combined with flat amplitude and linear phase characteristics; their simple construction and radiation hardness also makes them especially suitable for space applications. An overview of the architectures used in the above systems, describing the technologies employed, and the use of bandwidth switchable SAW filtering (BSSF) is given. The tradeoffs to be considered when specifying a SAW based system are analyzed, using both theoretical and experimental data. Empirical rules for estimating SAW filter performance are given. Achievable performance is illustrated using data from the INMARSAT 3 engineering model (EM) processors.

  14. Global Ocean Surveillance With Electronic Intelligence Based Satellite System

    Science.gov (United States)

    Venkatramanan, Haritha

    2016-07-01

    The objective of this proposal is to design our own ELINT based satellite system to detect and locate the target by using satellite Trilateration Principle. The target position can be found by measuring the radio signals arrived at three satellites using Time Difference of Arrival(TDOA) technique. To locate a target it is necessary to determine the satellite position. The satellite motion and its position is obtained by using Simplified General Perturbation Model(SGP4) in MATLAB. This SGP4 accepts satellite Two Line Element(TLE) data and returns the position in the form of state vectors. These state vectors are then converted into observable parameters and then propagated in space. This calculations can be done for satellite constellation and non - visibility periods can be calculated. Satellite Trilateration consists of three satellites flying in formation with each other. The satellite constellation design consists of three satellites with an inclination of 61.3° maintained at equal distances between each other. The design is performed using MATLAB and simulated to obtain the necessary results. The target's position can be obtained using the three satellites ECEF Coordinate system and its position and velocity can be calculated in terms of Latitude and Longitude. The target's motion is simulated to obtain the Speed and Direction of Travel.

  15. 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.

  16. Age determinations and Earth-based multispectral observations of lunar light plains

    Science.gov (United States)

    Koehler, U.; Jaumann, R.; Neukum, G.

    1993-01-01

    The history of light plains still remains doubtful, but there are good arguments - mainly obtained by age determinations and supported by multispectral observations - for an endogenic (magmatic) instead of an (exclusively) impact related origin. Light plains are characterized by smooth areas with an albedo lower than the surrounding highlands (12 - 13 percent), but significantly higher than maria (5 - 6 percent). Before Apollo 16 a volcanic source has been supposed, but analysis of returned samples (highly brecciated and metamorphosed rocks) favored an impact ejecta related origin. Among the currently discussed models are formation by ejecta sedimentation from multi-ringed basins, formation by secondary and tertiary cratering action of ballistically ejected material during the formation of multi-ringed basins, in situ formation by impact melt of large events, and premare (crypto-) volcanism basalts covered by a thin ejecta cover; younger impacts penetrated the ejecta surface to create the dark haloed craters. To find arguments in favor or against these ideas the chronology of light plains is of major importance. Obviously a genetic relationship between the evolution of light plains and the basin forming impacts can be possible only if the events of emplacement features happened simultaneously.

  17. Adaptive on-line classification of multi-spectral scanner data

    Science.gov (United States)

    Fromm, F. R.; Northouse, R. A.

    1973-01-01

    A possible solution to the analysis of the massive amounts of multi-spectral scanner data from the Earth Resource Technical Satellite (ERTS) program is proposed. This solution is offered as an adaptive on-line classification scheme. The classifier is described as well as its controller which is based on ground truth data. Cluster analysis is presented as an alternative approach to the ground truth data. Adaptive feature selection is discussed and possible mini-computer implementations are offered.

  18. Satellite Based Analysis of Carbon Monoxide Levels Over Alberta Oil Sand

    Science.gov (United States)

    Marey, H. S.; Hashisho, Z.; Fu, L.; Gille, J. C.

    2014-12-01

    The rapid expansion of oil sands activities and massive energy requirements to extract and upgrade the bitumen require a comprehensive understanding of their potential environmental impacts, particularly on air quality. In this study, satellite-based analysis of carbon monoxide (CO) levels was used to assess the magnitude and distribution of this pollutant throughout Alberta oil sands region. Measurements of Pollution in the Troposphere (MOPITT) V5 multispectral product that uses both near-infrared and the thermal-infrared radiances for CO retrieval were used. MOPITT-based climatology and inter-annual variations were examined for 12 years (2002-2013) on spatial and temporal scales. Seasonal climatological maps for CO total columns indicated conspicuous spatial variations in all seasons except in winter where the CO spatial variations are less prominent. High CO loadings are observed to extend from the North East to North West regions of Alberta, with highest values in spring. The CO mixing ratios at the surface level in winter and spring seasons exhibited dissimilar spatial distribution pattern where the enhancements are detected in south eastern rather than northern Alberta. Analyzing spatial distributions of Omega at 850 mb pressure level for four seasons implied that, conditions in northeastern Alberta are more favorable for up lofting while in southern Alberta, subsidence of CO emissions are more likely. Time altitude CO profile climatology as well as the inter-annual variability were investigated for the oil sands and main urban regions in Alberta to assess the impact of various sources on CO loading. Monthly variations over urban regions are consistent with the general seasonal cycle of CO in Northern Hemisphere which exhibits significant enhancement in winter and spring, and minimum mixing ratios in summer. The typical seasonal CO variations over the oil sands region are less prominent. This study has demonstrated the potential use of multispectral CO

  19. A NEW OBJECT-BASED FRAMEWORK TO DETECT SHODOWS IN HIGH-RESOLUTION SATELLITE IMAGERY OVER URBAN AREAS

    Directory of Open Access Journals (Sweden)

    N. Tatar

    2015-12-01

    Full Text Available In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

  20. Satellite-Based EMI Detection, Identification, and Mitigation

    Science.gov (United States)

    Stottler, R.; Bowman, C.

    2016-09-01

    Commanding, controlling, and maintaining the health of satellites requires a clear operating spectrum for communications. Electro Magnetic Interference (EMI) from other satellites can interfere with these communications. Determining which satellite is at fault improves space situational awareness and can be used to avoid the problem in the future. The Rfi detection And Prediction Tool, Optimizing Resources (RAPTOR) monitors the satellite communication antenna signals to detect EMI (also called RFI for Radio Frequency Interference) using a neural network trained on past cases of both normal communications and EMI events. RAPTOR maintains a database of satellites that have violated the reserved spectrum in the past. When satellite-based EMI is detected, RAPTOR first checks this list to determine if any are angularly close to the satellite being communicated with. Additionally, RAPTOR checks the Space Catalog to see if any of its active satellites are angularly close. RAPTOR also consults on-line databases to determine if the described operating frequencies of the satellites match the detected EMI and recommends candidates to be added to the known offenders database, accordingly. Based on detected EMI and predicted orbits and frequencies, RAPTOR automatically reschedules satellite communications to avoid current and future satellite-based EMI. It also includes an intuitive display for a global network of satellite communications antennas and their statuses including the status of their EM spectrum. RAPTOR has been prototyped and tested with real data (amplitudes versus frequency over time) for both satellite communication signals and is currently undergoing full-scale development. This paper describes the RAPTOR technologies and results of testing.

  1. 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.

  2. A Gravitational Edge Detection for Multispectral Images

    Directory of Open Access Journals (Sweden)

    Genyun Sun

    2013-07-01

    Full Text Available Gravitational edge detection is one of the new edge detection algorithms that is based on the law of gravity. This algorithm assumes that each image pixel is a celestial body with a mass represented by its grayscale intensity and their interactions are based on the Newtonian laws of gravity. In this article, a multispectral version of the algorithm is introduced. The method uses gravitational techniques in combination with metric tensor to detect edges of multispectral images including color images. To evaluate the performances of the proposed algorithm, several experiments are performed. The experimental results confirm the efficiency of the multispectral gravitational edge detection.  

  3. Fusion of LIDAR Data and Multispectral Imagery for Effective Building Detection Based on Graph and Connected Component Analysis

    Science.gov (United States)

    Gilani, S. A. N.; Awrangjeb, M.; Lu, G.

    2015-03-01

    Building detection in complex scenes is a non-trivial exercise due to building shape variability, irregular terrain, shadows, and occlusion by highly dense vegetation. In this research, we present a graph based algorithm, which combines multispectral imagery and airborne LiDAR information to completely delineate the building boundaries in urban and densely vegetated area. In the first phase, LiDAR data is divided into two groups: ground and non-ground data, using ground height from a bare-earth DEM. A mask, known as the primary building mask, is generated from the non-ground LiDAR points where the black region represents the elevated area (buildings and trees), while the white region describes the ground (earth). The second phase begins with the process of Connected Component Analysis (CCA) where the number of objects present in the test scene are identified followed by initial boundary detection and labelling. Additionally, a graph from the connected components is generated, where each black pixel corresponds to a node. An edge of a unit distance is defined between a black pixel and a neighbouring black pixel, if any. An edge does not exist from a black pixel to a neighbouring white pixel, if any. This phenomenon produces a disconnected components graph, where each component represents a prospective building or a dense vegetation (a contiguous block of black pixels from the primary mask). In the third phase, a clustering process clusters the segmented lines, extracted from multispectral imagery, around the graph components, if possible. In the fourth step, NDVI, image entropy, and LiDAR data are utilised to discriminate between vegetation, buildings, and isolated building's occluded parts. Finally, the initially extracted building boundary is extended pixel-wise using NDVI, entropy, and LiDAR data to completely delineate the building and to maximise the boundary reach towards building edges. The proposed technique is evaluated using two Australian data sets

  4. Prostate Cancer Segmentation Using Multispectral Random Walks

    Science.gov (United States)

    Artan, Yusuf; Haider, Masoom A.; Yetik, Imam Samil

    Several studies have shown the advantages of multispectral magnetic resonance imaging (MRI) as a noninvasive imaging technique for prostate cancer localization. However, a large proportion of these studies are with human readers. There is a significant inter and intra-observer variability for human readers, and it is substantially difficult for humans to analyze the large dataset of multispectral MRI. To solve these problems a few studies were proposed for fully automated cancer localization in the past. However, fully automated methods are highly sensitive to parameter selection and often may not produce desirable segmentation results. In this paper, we present a semi-supervised segmentation algorithm by extending a graph based semi-supervised random walker algorithm to perform prostate cancer segmentation with multispectral MRI. Unlike classical random walker which can be applied only to dataset of single type of MRI, we develop a new method that can be applied to multispectral images. We prove the effectiveness of the proposed method by presenting the qualitative and quantitative results of multispectral MRI datasets acquired from 10 biopsy-confirmed cancer patients. Our results demonstrate that the multispectral MRI noticeably increases the sensitivity and jakkard measures of prostate cancer localization compared to single MR images; 0.71 sensitivity and 0.56 jakkard for multispectral images compared to 0.51 sensitivity and 0.44 jakkard for single MR image based segmentation.

  5. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  6. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  7. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multipectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  8. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  9. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  10. Mosaic of 2m bathymetry derived from multispectral IKONOS World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  11. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  12. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  13. Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  14. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of the Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  15. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  16. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Rota Island, Territory of Mariana, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  17. UAS-based soil carbon mapping using VIS-NIR (480–1000 nm) multi-spectral imaging: Potential and limitations

    DEFF Research Database (Denmark)

    Aldana Jague, Emilien; Heckrath, Goswin; Macdonald, Andy

    2016-01-01

    Traditional methods to assess the soil organic carbon (SOC) content based on soil sampling and analysis are time consuming and expensive, and the results are influenced by the sampling design. The aim of this study was to investigate the potential of UAS (Unmanned Aerial Systems) multi-spectral i......Traditional methods to assess the soil organic carbon (SOC) content based on soil sampling and analysis are time consuming and expensive, and the results are influenced by the sampling design. The aim of this study was to investigate the potential of UAS (Unmanned Aerial Systems) multi...... practices, provide a valuable resource to evaluate this approach. We acquired images (wavelength: 480–550–670–780–880–1000 nm) at an altitude of 120 m over an area of 2 ha using a multi-spectral camera mounted on an UAS. The high-resolution images captured smallscale variations at the soil surface (e...

  18. Spectrally Enhanced Cloud Objects—A generalized framework for automated detection of volcanic ash and dust clouds using passive satellite measurements: 1. Multispectral analysis

    Science.gov (United States)

    Pavolonis, Michael J.; Sieglaff, Justin; Cintineo, John

    2015-08-01

    While satellites are a proven resource for detecting and tracking volcanic ash and dust clouds, existing algorithms for automatically detecting volcanic ash and dust either exhibit poor overall skill or can only be applied to a limited number of sensors and/or geographic regions. As such, existing techniques are not optimized for use in real-time applications like volcanic eruption alerting and data assimilation. In an effort to significantly improve upon existing capabilities, the Spectrally Enhanced Cloud Objects (SECO) algorithm was developed. The SECO algorithm utilizes a combination of radiative transfer theory, a statistical model, and image processing techniques to identify volcanic ash and dust clouds in satellite imagery with a very low false alarm rate. This fully automated technique is globally applicable (day and night) and can be adapted to a wide range of low earth orbit and geostationary satellite sensors or even combinations of satellite sensors. The SECO algorithm consists of four primary components: conversion of satellite measurements into robust spectral metrics, application of a Bayesian method to estimate the probability that a given satellite pixel contains volcanic ash and/or dust, construction of cloud objects, and the selection of cloud objects deemed to have the physical attributes consistent with volcanic ash and/or dust clouds. The first two components of the SECO algorithm are described in this paper, while the final two components are described in a companion paper.

  19. System refinement for content based satellite image retrieval

    Directory of Open Access Journals (Sweden)

    NourElDin Laban

    2012-06-01

    Full Text Available We are witnessing a large increase in satellite generated data especially in the form of images. Hence intelligent processing of the huge amount of data received by dozens of earth observing satellites, with specific satellite image oriented approaches, presents itself as a pressing need. Content based satellite image retrieval (CBSIR approaches have mainly been driven so far by approaches dealing with traditional images. In this paper we introduce a novel approach that refines image retrieval process using the unique properties to satellite images. Our approach uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tiling sizes. Accordingly the system uses these multilevel features within a multilevel retrieval system that refines the retrieval process. Our multilevel refinement approach has been experimentally validated against the conventional one yielding enhanced precision and recall rates.

  20. An automated fog monitoring system for the Indo-Gangetic Plains based on satellite measurements

    Science.gov (United States)

    Patil, Dinesh; Chourey, Reema; Rizvi, Sarwar; Singh, Manoj; Gautam, Ritesh

    2016-05-01

    Fog is a meteorological phenomenon that causes reduction in regional visibility and affects air quality, thus leading to various societal and economic implications, especially disrupting air and rail transportation. The persistent and widespread winter fog impacts the entire the Indo-Gangetic Plains (IGP), as frequently observed in satellite imagery. The IGP is a densely populated region in south Asia, inhabiting about 1/6th of the world's population, with a strong upward pollution trend. In this study, we have used multi-spectral radiances and aerosol/cloud retrievals from Terra/Aqua MODIS data for developing an automated web-based fog monitoring system over the IGP. Using our previous and existing methodologies, and ongoing algorithm development for the detection of fog and retrieval of associated microphysical properties (e.g. fog droplet effective radius), we characterize the widespread fog detection during both daytime and nighttime. Specifically, for the night time fog detection, the algorithm employs a satellite-based bi-spectral brightness temperature difference technique between two spectral channels: MODIS band-22 (3.9μm) and band-31 (10.75μm). Further, we are extending our algorithm development to geostationary satellites, for providing continuous monitoring of the spatial-temporal variation of fog. We anticipate that the ongoing and future development of a fog monitoring system would be of assistance to air, rail and vehicular transportation management, as well as for dissemination of fog information to government agencies and general public. The outputs of fog detection algorithm and related aerosol/cloud parameters are operationally disseminated via http://fogsouthasia.com/.

  1. Radio occultation based on BeiDou satellite navigation

    Science.gov (United States)

    Jiang, Hu; Hu, Haiying; Shen, Xue-min; Gong, Wenbin; Zhang, Yonghe

    2014-11-01

    With the development of GNSS systems, it has become a tendency that radio occultation is used to sense the Earth's atmosphere. By this means, the moisture, temperature, pressure, and total electron content can be derived. Based on the sensing results, more complicated models for atmosphere might come into being. Meteorology well benefits from this technology. As scheduled, the BD satellite navigation system will have a worldwide coverage by the end of 2020. Radio occultation studies in China have been highlighted in the recent decade. More and more feasibilities reports have been published in either domestic or international journals. Herein, some scenarios are proposed to assess the coverage of radio occultation based on two different phases of BD satellite navigation system. Phase one for BD is composed of GEO,IGSO and several MEO satellites. Phase two for BD consists mostly of 24 MEO satellites, some GEO and IGSO satellites. The characteristics of radio occultation based on these two phases are presented respectively.

  2. 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...

  3. A novel method for non-destructive determination of hair photo-induced damage based on multispectral imaging technology.

    Science.gov (United States)

    Cao, Yue; Qu, Hao; Xiong, Can; Liu, Changhong; Zheng, Lei

    2017-03-31

    Extended exposure to sunlight may give rise to chemical and physical damages of human hairs. In this work, we report a novel method for non-destructive quantification of hair photodamage via multispectral imaging (MSI) technology. We show that the multispectral reflectance value in near-infrared region has a strong correlation with hair photodamage. More specifically, the hair segments with longer growing time and the same hair root segment after continuous ultraviolet (UV) irradiation displaying more severe photodamage observed via scanning electron microscopy (SEM) micrographs showed significantly higher multispectral reflectance value. Besides, the multispectral reflectance value of hair segments with different growing time was precisely reproduced by exposing the same hair root segment to specific durations of UV irradiation, suggesting that MSI can be adequately applied to determine the sunlight exposure time of the hair. The loss of cystine content of photodamaged hairs was identified to be the main factor that physiologically contributed to the morphological changes of hair surface fibers and hence the variation of their multispectral reflectance spectra. Considering the environmental information recording nature of hairs, we believe that MSI for non-destructive evaluation of hair photodamage would prove valuable for assessing sunlight exposure time of a subject in the biomedical fields.

  4. Technique based on LED multispectral imaging and multivariate analysis for monitoring the conservation state of the Dead Sea Scrolls.

    Science.gov (United States)

    Marengo, Emilio; Manfredi, Marcello; Zerbinati, Orfeo; Robotti, Elisa; Mazzucco, Eleonora; Gosetti, Fabio; Bearman, Greg; France, Fenella; Shor, Pnina

    2011-09-01

    The aim of this project is the development of a noninvasive technique based on LED multispectral imaging (MSI) for monitoring the conservation state of the Dead Sea Scrolls (DSS) collection. It is well-known that changes in the parchment reflectance drive the transition of the scrolls from legible to illegible. Capitalizing on this fact, we will use spectral imaging to detect changes in the reflectance before they become visible to the human eye. The technique uses multivariate analysis and statistical process control theory. The present study was carried out on a "sample" parchment of calfskin. The monitoring of the surface of a commercial modern parchment aged consecutively for 2 h and 6 h at 80 °C and 50% relative humidity (ASTM) was performed at the Imaging Lab of the Library of Congress (Washington, DC, U.S.A.). MSI is here carried out in the vis-NIR range limited to 1 μm, with a number of bands of 13 and bandwidths that range from about 10 nm in UV to 40 nm in IR. Results showed that we could detect and locate changing pixels, on the basis of reflectance changes, after only a few "hours" of aging.

  5. In vivo wide-field multispectral dosimeter for use in ALA-PpIX based photodynamic therapy of skin

    Science.gov (United States)

    LaRochelle, Ethan P. M.; Davis, Scott C.; de Souza, Ana Luiza Ribeiro; Pogue, Brian W.

    2017-02-01

    Photodynamic therapy (PDT) for Actinic Kertoses (AK) using aminoluvelinic acid (ALA) is an FDA-approved treatment, which is generally effective, yet response rates vary. The origin of the variability is not well characterized, but may be related to inter-patient variability in the production of protoporphyrin IX (PpIX). While fiber-based point probe systems provide a method for measuring PpIX production, these measurements have demonstrated large spatial and inter-operator variability. Thus, in an effort to improve patient-specific dosimetry and treatment it is important to develop a robust system that accounts for spatial variability and reduces the chance of operator errors. To address this need, a wide-field multispectral imaging system was developed that is capable of quantifying maps of PpIX in both liquid phantoms and in vivo experiments, focusing on high sensitivity light signals. The system uses both red and blue excitation to elicit a fluorescent response at varying skin depths. A ten-position filter wheel with bandpass filters ranging from 635nm to 710nm are used to capture images along the emission band. A linear least-square spectral fitting algorithm provides the ability to decouple background autofluorescence from PpIX fluorescence, which has improved the system sensitivity by an order of magnitude, detecting nanomolar PpIX concentrations in liquid phantoms in the presence of 2% whole blood and 2% intralipid.

  6. Identification and mapping of soil erosion areas in the Blue Nile-Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model

    Directory of Open Access Journals (Sweden)

    M. El Haj Tahir

    2010-01-01

    Full Text Available This paper is part of a set of studies to evaluate the spatial and temporal variability of soil water in terms of natural as well as land-use changes as fundamental factors for vegetation regeneration in arid ecosystems in the Blue Nile-Sudan. The specific aim is to indicate the spatial distribution of soil erosion caused by the rains of 2006. The current study is conducted to determine whether automatic classification of multispectral Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER imagery could accurately discriminate erosion gullies. Shuttle Radar Topography Mission (SRTM is used to orthoproject ASTER data. A maximum likelihood classifier is trained with four classes, Gullies, Flat_Land, Mountains and Water and applied to images from March and December 2006. Validation is done with field data from December and January 2006/2007, and using drainage network analysis of SRTM digital elevation model. The results allow the identification of erosion gullies and subsequent estimation of eroded area. Consequently the results were up-scaled using Moderate Resolution Imaging Spectroradiometer (MODIS images of the same dates. Because the selected study site is representative of the wider Blue Nile province, it is expected that the approach presented could be applied to larger areas.

  7. Identification and mapping of soil erosion areas in the Blue Nile-Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model

    Science.gov (United States)

    El Haj Tahir, M.; Kääb, A.; Xu, C.-Y.

    2010-01-01

    This paper is part of a set of studies to evaluate the spatial and temporal variability of soil water in terms of natural as well as land-use changes as fundamental factors for vegetation regeneration in arid ecosystems in the Blue Nile-Sudan. The specific aim is to indicate the spatial distribution of soil erosion caused by the rains of 2006. The current study is conducted to determine whether automatic classification of multispectral Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) imagery could accurately discriminate erosion gullies. Shuttle Radar Topography Mission (SRTM) is used to orthoproject ASTER data. A maximum likelihood classifier is trained with four classes, Gullies, Flat_Land, Mountains and Water and applied to images from March and December 2006. Validation is done with field data from December and January 2006/2007, and using drainage network analysis of SRTM digital elevation model. The results allow the identification of erosion gullies and subsequent estimation of eroded area. Consequently the results were up-scaled using Moderate Resolution Imaging Spectroradiometer (MODIS) images of the same dates. Because the selected study site is representative of the wider Blue Nile province, it is expected that the approach presented could be applied to larger areas.

  8. 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.

  9. 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

    2016-01-01

    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.

  10. 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.

  11. A method for comparison of growth media in objective identification of Penicillium based on multi-spectral imaging

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Hansen, Michael Adsetts Edberg; Frisvad, Jens Christian

    2007-01-01

    We consider the problems of using excessive growth media for identification and performing objective identification of fungi at the species level. We propose a method for choosing the subset of growth media, which provides the best discrimination between several fungal species. Furthermore, we pr...... to macro-morphological features. The species have been classified using only 3–4 of the spectral bands with a 100% correct classification rate using both leave-one-out cross-validation and test set validation....... propose the use of multi-spectral imaging as a means of objective identification. Three species of the fungal genus Penicillium are subject to classification. To obtain an objective classification we use multi-spectral images. Previously, RGB images have proven useful for the purpose. We use multi-spectral...

  12. Validation of a fiber-based confocal microscope for interventional image-guided procedures: correlation with multispectral optical imaging

    Science.gov (United States)

    Herzka, Daniel; Quijano, Jade; Xie, Jianwu; Krueger, Sascha; Weiss, Steffen; Abrat, Benjamin; Osdoit, Anne; Cavé, Charlotte; Burnett, Christopher; Danthi, S. Narasimhan; Li, King

    2006-03-01

    The concept of the biopsy is ubiquitous in current medical diagnosis of cancer and other diseases. The standard biopsy consists of removing a sample of tissue for evaluation and diagnosis, primarily to ascertain the presence of cancer cells by (histo)pathological analyses. However, the advent of new optical imaging modalities and targeted or "smart" agents, that have affinity for a select target, suggests the possibility of performing in vivo tissue characterization without the need for sample removal or the wait for histopathologic processing. Here we present work testing and validating a fiber-based confocal fluorescence microscopic imaging system intended for combination with a larger scale imaging modality (i.e. MRI or CT) to be used in image-guided in vivo tissue characterization. Fiber-based confocal fluorescence microscopic imaging experiments were performed (Cellvizio, Mauna Kea Technologies, Paris, France) in vivo in two mouse models including: 1) EGFP-expressing mouse melanoma model and 2) M21 mouse melanoma model. Both models are known to express integrin α νβ 3, a cell-surface receptor protein. We also performed an experiment in ex vivo chicken muscle tissue labelled with a fluorescein isothiocyanate-lectin targeted compound. In the mouse models, contrast agents that targeted the integrin were injected and the contrast agent localization in tumor was verified by a whole-body multispectral imager. The fiber-based tool was sensitive enough to detect and image the tissue of interest in all different experiments, and was found appropriate for use in interventional catheter-based procedures.

  13. 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.

  14. 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...

  15. Delivery of satellite based broadband services

    Science.gov (United States)

    Chandrasekhar, M. G.; Venugopal, D.

    2007-06-01

    Availability of speedy communication links to individuals and organizations is essential to keep pace with the business and social requirements of this modern age. While the PCs have been continuously growing in processing speed and memory capabilities, the availability of broadband communication links still has not been satisfactory in many parts of the world. Recognizing the need to give fillip to the growth of broadband services and improve the broadband penetration, the telecom policies of different counties have placed special emphasis on the same. While emphasis is on the use of fiber optic and copper in local loop, satellite communications systems will play an important role in quickly establishing these services in areas where fiber and other communication systems are not available and are not likely to be available for a long time to come. To make satellite communication systems attractive for the wide spread of these services in a cost effective way special emphasis has to be given on factors affecting the cost of the bandwidth and the equipment. As broadband services are bandwidth demanding, use of bandwidth efficient modulation technique and suitable system architecture are some of the important aspects that need to be examined. Further there is a need to re-look on how information services are provided keeping in view the user requirements and broadcast capability of satellite systems over wide areas. This paper addresses some of the aspects of delivering broadband services via satellite taking Indian requirement as an example.

  16. Satellite data compression

    CERN Document Server

    Huang, Bormin

    2011-01-01

    Satellite Data Compression covers recent progress in compression techniques for multispectral, hyperspectral and ultra spectral data. A survey of recent advances in the fields of satellite communications, remote sensing and geographical information systems is included. Satellite Data Compression, contributed by leaders in this field, is the first book available on satellite data compression. It covers onboard compression methodology and hardware developments in several space agencies. Case studies are presented on recent advances in satellite data compression techniques via various prediction-

  17. 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

    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...... by the resolution of the radar data. Subsequently, a supervised classifier was developed based on training data selected by a weather radar expert. Results of classification of data from several different meteorological events are shown. Cases of widespread sea clutter caused by anomalous propagation are especially...

  18. Co-Channel Interference Mitigation Using Satellite Based Receivers

    Science.gov (United States)

    2014-12-01

    While there is some phase noise present in the continuous time-shifted signal, it is important to recognize that this signal is plotted over the [−π...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS CO-CHANNEL INTERFERENCE MITIGATION USING SATELLITE BASED RECEIVERS by John E. Patterson...07-02-2012 to 12-19-2014 4. TITLE AND SUBTITLE CO-CHANNEL INTERFERENCE MITIGATION USING SATELLITE BASED RE- CEIVERS 5. FUNDING NUMBERS 6. AUTHOR(S

  19. Multispectral Microimager for Astrobiology

    Science.gov (United States)

    Sellar, R. Glenn; Farmer, Jack D.; Kieta, Andrew; Huang, Julie

    2006-01-01

    A primary goal of the astrobiology program is the search for fossil records. The astrobiology exploration strategy calls for the location and return of samples indicative of environments conducive to life, and that best capture and preserve biomarkers. Successfully returning samples from environments conducive to life requires two primary capabilities: (1) in situ mapping of the mineralogy in order to determine whether the desired minerals are present; and (2) nondestructive screening of samples for additional in-situ testing and/or selection for return to laboratories for more in-depth examination. Two of the most powerful identification techniques are micro-imaging and visible/infrared spectroscopy. The design and test results are presented from a compact rugged instrument that combines micro-imaging and spectroscopic capability to provide in-situ analysis, mapping, and sample screening capabilities. Accurate reflectance spectra should be a measure of reflectance as a function of wavelength only. Other compact multispectral microimagers use separate LEDs (light-emitting diodes) for each wavelength and therefore vary the angles of illumination when changing wavelengths. When observing a specularly-reflecting sample, this produces grossly inaccurate spectra due to the variation in the angle of illumination. An advanced design and test results are presented for a multispectral microimager which demonstrates two key advances relative to previous LED-based microimagers: (i) acquisition of actual reflectance spectra in which the flux is a function of wavelength only, rather than a function of both wavelength and illumination geometry; and (ii) increase in the number of spectral bands to eight bands covering a spectral range of 468 to 975 nm.

  20. Efficient chaotic based satellite power supply subsystem

    Energy Technology Data Exchange (ETDEWEB)

    Ramos Turci, Luiz Felipe [Technological Institute of Aeronautics (ITA), Sao Jose dos Campos, SP (Brazil)], E-mail: felipeturci@yahoo.com.br; Macau, Elbert E.N. [National Institute of Space Research (Inpe), Sao Jose dos Campos, SP (Brazil)], E-mail: elbert@lac.inpe.br; Yoneyama, Takashi [Technological Institute of Aeronautics (ITA), Sao Jose dos Campos, SP (Brazil)], E-mail: takashi@ita.br

    2009-10-15

    In this work, we investigate the use of the Dynamical System Theory to increase the efficiency of the satellite power supply subsystems. The core of a satellite power subsystem relies on its DC/DC converter. This is a very nonlinear system that presents a multitude of phenomena ranging from bifurcations, quasi-periodicity, chaos, coexistence of attractors, among others. The traditional power subsystem design techniques try to avoid these nonlinear phenomena so that it is possible to use linear system theory in small regions about the equilibrium points. Here, we show that more efficiency can be drawn from a power supply subsystem if the DC/DC converter operates in regions of high nonlinearity. In special, if it operates in a chaotic regime, is has an intrinsic sensitivity that can be exploited to efficiently drive the power subsystem over high ranges of power requests by using control of chaos techniques.

  1. Multispectral biometrics systems and applications

    CERN Document Server

    Zhang, David; Gong, Yazhuo

    2016-01-01

    Describing several new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris recognition technologies, this book analyzes a number of efficient feature extraction, matching and fusion algorithms and how potential systems have been developed. Focusing on how to develop new biometric technologies based on the requirements of applications, and how to design efficient algorithms to deliver better performance, the work is based on the author’s research with experimental results under different challenging conditions described in the text. The book offers a valuable resource for researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, biometrics, and security applications, amongst others.

  2. Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery

    Science.gov (United States)

    Zhou, X.; Zheng, H. B.; Xu, X. Q.; He, J. Y.; Ge, X. K.; Yao, X.; Cheng, T.; Zhu, Y.; Cao, W. X.; Tian, Y. C.

    2017-08-01

    Timely and non-destructive assessment of crop yield is an essential part of agricultural remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a novel approach for RS, and makes it possible to acquire high spatio-temporal resolution imagery on a regional scale. In this study, the rice grain yield was predicted with single stage vegetation indices (VIs) and multi-temporal VIs derived from the multispectral (MS) and digital images. The results showed that the booting stage was identified as the optimal stage for grain yield prediction with VIs at a single stage for both digital image and MS image. And corresponding optimal color index was VARI with R2 value of 0.71 (Log relationship). While the optimal vegetation index NDVI[800,720] based on MS images showed a linear relationship with the grain yield and gained a higher R2 value (0.75) than color index did. The multi-temporal VIs showed a higher correlation with grain yield than the single stage VIs did. And the VIs at two random growth stage with the multiple linear regression function [MLR(VI)] performed best. The highest correlation coefficient were 0.76 with MLR(NDVI[800,720]) at the booting and heading stages (for the MS image) and 0.73 with MLR(VARI) at the jointing and booting stages (for the digital image). In addition, the VIs that showed a high correlation with LAI performed well for yield prediction, and the VIs composed of red edge band (720 nm) and near infrared band (800 nm) were found to be more effective in predicting yield and LAI at high level. In conclusion, this study has demonstrated that both MS and digital sensors mounted on the UAV are reliable platforms for rice growth and grain yield estimation, and determined the best period and optimal VIs for rice grain yield prediction.

  3. 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.

  4. 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.

  5. Multispectral Palmprint Recognition Using a Quaternion Matrix

    Directory of Open Access Journals (Sweden)

    Yafeng Li

    2012-04-01

    Full Text Available Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR illuminations were represented by a quaternion matrix, then principal component analysis (PCA and discrete wavelet transform (DWT were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

  6. 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.

  7. A comparative study of satellite and ground-based phenology.

    Science.gov (United States)

    Studer, S; Stöckli, R; Appenzeller, C; Vidale, P L

    2007-05-01

    Long time series of ground-based plant phenology, as well as more than two decades of satellite-derived phenological metrics, are currently available to assess the impacts of climate variability and trends on terrestrial vegetation. Traditional plant phenology provides very accurate information on individual plant species, but with limited spatial coverage. Satellite phenology allows monitoring of terrestrial vegetation on a global scale and provides an integrative view at the landscape level. Linking the strengths of both methodologies has high potential value for climate impact studies. We compared a multispecies index from ground-observed spring phases with two types (maximum slope and threshold approach) of satellite-derived start-of-season (SOS) metrics. We focus on Switzerland from 1982 to 2001 and show that temporal and spatial variability of the multispecies index correspond well with the satellite-derived metrics. All phenological metrics correlate with temperature anomalies as expected. The slope approach proved to deviate strongly from the temporal development of the ground observations as well as from the threshold-defined SOS satellite measure. The slope spring indicator is considered to indicate a different stage in vegetation development and is therefore less suited as a SOS parameter for comparative studies in relation to ground-observed phenology. Satellite-derived metrics are, however, very susceptible to snow cover, and it is suggested that this snow cover should be better accounted for by the use of newer satellite sensors.

  8. 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.

  9. Technology status of HNF-based monopropellants for satellite propulsion

    NARCIS (Netherlands)

    Marée, A.G.M.; Moerel, J.L.P.A.; Weiland-Veltmans, W.H.M.; Wierkx, F.J.M.; Zevenbergen, J.

    2004-01-01

    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 o

  10. Technology status of HNF-based monopropellants for satellite propulsion

    NARCIS (Netherlands)

    Marée, A.G.M.; Moerel, J.L.P.A.; Weiland-Veltmans, W.H.M.; Wierkx, F.J.M.; Zevenbergen, J.

    2004-01-01

    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 o

  11. Multi-spectral remote sensing image true color synthesis technique based on artificial target%基于人工靶标的多光谱遥感图像真彩色合成

    Institute of Scientific and Technical Information of China (English)

    黄红莲; 易维宁; 杜丽丽; 崔文煜; 曾献芳

    2016-01-01

    Multi-spectral true color synthesized images have the prospects of broad application in the interpretation of remote sensing image, target recognition and information processing etc. The technique of true color synthesis depends on the accuracy of the obtained tristimulus values CIE-XYZ, which is used to establish the right relationship between the system of camera′s RGB and human being′s visual color. So, a method of true color image synthesis based on the information of artificial target was proposed by laying the man-made targets when the satellite passes. And, the transformation matrix between camera′s RGB trichromatic system and human being′s visual color system was estimated from the reflectance spectrum of man-made targets. Eventually, the suitable true color correction model was established in the certain atmospheric conditions. Experiment of true color correction was conducted on the multi-spectral images of GF-1 satellite, and the results show that good color correction effects has been exhibited on even every image with different degrees of color′s richness.%多光谱真彩色合成图像在遥感图像解译判读、 目标识别和信息处理等领域具有广阔的应用前景.真彩色合成技术取决于获得准确的X、Y、Z三刺激值,以建立相机RGB三基色体系与人眼视觉颜色体系之间的关系.为此,提出了基于彩色目标光谱信息的多光谱图像真彩色合成方法,通过在卫星过顶时铺设人工靶标,利用实测的靶标反射率光谱,计算相机三基色体系RGB与人眼视觉颜色体系CIE-XYZ之间的转换矩阵,构建适用于一定大气条件下的真彩色校正模型.利用高分一号卫星多光谱图像进行真彩色校正实验的结果表明,该方法对色彩丰富度不同的图像均具有较好的颜色校正效果.

  12. Implementation of multispectral image fusion system based on SoPC

    Science.gov (United States)

    Meng, Lingfei; Wang, Zhihui

    2013-10-01

    Combining the theory of wavelet transform based image fusion and SOPC design method, the authors uses SOPC as the core device to design and implement a image fusion system. The fusion system adopts the Verilog hardware description language, Dsp builder and Quartus II development platform together with macro module to complete the logic design and timing control of each module. In the fusion system, we can achieve simple pixel-level image fusion of two registered images. This design not only builds up an image fusion system based on SOPC in accident, but also provides a hardware design principle in SoPC for the future design and Implementation of more comprehensive function of image processing.

  13. Bio-Inspired Dynamically Tunable Polymer-Based Filters for Multi-Spectral Infrared Imaging

    Science.gov (United States)

    2010-05-01

    Morse. Plastic Transmissive Infrared Electrochromic Devices , Macromolecular Chemistry and Physics, (07 2010): 0. doi: 10.1002/macp.201000096 2011/10/10...Publication: Holt, A.L., J. G. A. Wehner, A. Hammp and D. E. Morse. 2010. Plastic transmissive infrared electrochromic devices ...Level Device Design ( Electrochromic -Based IR Shutter): The first initiative in the device design work consisted of determining a standard device

  14. A Color-texture Approach Based on Mutual Information for Multispectral Image Classification

    Directory of Open Access Journals (Sweden)

    Hassan El Maia

    2010-10-01

    Full Text Available In this work we propose an approach to improve the results of color texture image classification. We construct a new space called hybrid color-texture space by selecting the most discriminating attributes for the textures. Attributes are calculating from the co-occurrence matrix. The selection is done by the algorithm MRMR based on the mutual information. The Support Vectors Machine classifier (SVMis used. A comparison with an iterative selection is also performed. The effectiveness of the proposed approach is evaluated on the VisTex database and on a SPOT HRV (XS image representing two forest areas in the region of Rabat.

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

    Directory of Open Access Journals (Sweden)

    Xiangjun Wang

    2015-05-01

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

  16. A satellite based telemetry link for a UAV application

    Science.gov (United States)

    Bloise, Anthony

    1995-01-01

    The requirements for a satellite based communication facility to service the needs of the Geographical Information System (GIS) data collection community are addressed in this paper. GIS data is supplied in the form of video imagery at sub-television rates in one or more spectral bands / polarizations laced with a position correlated data stream. The limitations and vicissitudes of using a terrestrial based telecommunications link to collect GIS data are illustrated from actual mission scenarios. The expectations from a satellite based communications link by the geophysical data collection community concerning satellite architecture, operating bands, bandwidth, footprint agility, up link and down link hardware configurations on the UAV, the Mobile Control Vehicle and at the Central Command and Data Collection Facility comprise the principle issues discussed in the first section of this paper. The final section of the paper discusses satellite based communication links would have an increased volume and scope of services the GIS data collection community could make available to the GIS user community, and the price the data collection community could afford to pay for access to the communication satellite described in the paper.

  17. [The inversion processing of vegetation biomass along Yongding River based on multispectral information].

    Science.gov (United States)

    He, Cheng; Feng, Zhong-Ke; Han, Xu; Sun, Meng-Ying; Gong, Yin-Xi; Gao, Yuan; Dong, Bin

    2012-12-01

    Researching on vegetation biomass using the traditional measurement method is time-consuming and hard sledding, and prediction precision of biomass is always not good because of uncertain influencing factors. The present article aims at the current situation of Hebei-Beijing reach along Yongding River, using the Thematic Mapper data in this place on 20th July 2009 as source data, with the 30 meters Digital Elevation Model data in Beijing and other auxiliary information, meanwhile through field observation data, to find out the possible functional relationship along vegetation biomass and remote sensing image factor. The authros sorted out the vegetation biomass and remote sensing image factor on the sample plot, then set up an inverse model through multiple linear regression analysis, and analyzed the precision of inverse model. After calculating the measured value and predicted value, the authors got the global relative error is -0.025%, the average relative error is -0.016%, and the general predictive precision is 84.56%. The establishment of this model is able to investigate eco-environmental factors on large range timely, quickly and accurately, also can provide the experimental base for the eco-environmental survey on river basin, and make the foundation for the problem diagnosis of ecological environment and the research on ecosystem degradation mechanism of Yongding River.

  18. Potential of Uav-Based Laser Scanner and Multispectral Camera Data in Building Inspection

    Science.gov (United States)

    Mader, D.; Blaskow, R.; Westfeld, P.; Weller, C.

    2016-06-01

    Conventional building inspection of bridges, dams or large constructions in general is rather time consuming and often cost expensive due to traffic closures and the need of special heavy vehicles such as under-bridge inspection units or other large lifting platforms. In consideration that, an unmanned aerial vehicle (UAV) will be more reliable and efficient as well as less expensive and simpler to operate. The utilisation of UAVs as an assisting tool in building inspections is obviously. Furthermore, light-weight special sensors such as infrared and thermal cameras as well as laser scanner are available and predestined for usage on unmanned aircraft systems. Such a flexible low-cost system is realized in the ADFEX project with the goal of time-efficient object exploration, monitoring and damage detection. For this purpose, a fleet of UAVs, equipped with several sensors for navigation, obstacle avoidance and 3D object-data acquisition, has been developed and constructed. This contribution deals with the potential of UAV-based data in building inspection. Therefore, an overview of the ADFEX project, sensor specifications and requirements of building inspections in general are given. On the basis of results achieved in practical studies, the applicability and potential of the UAV system in building inspection will be presented and discussed.

  19. An interdisciplinary analysis of multispectral satellite data for selected cover types in the Colorado Mountains, using automatic data processing techniques. [geological lineaments and mineral exploration

    Science.gov (United States)

    Hoffer, R. M. (Principal Investigator)

    1974-01-01

    The author has identified the following significant results. One capability which has been recognized by many geologists working with space photography is the ability to see linear features and alinements which were previously not apparent. To the exploration geologist, major lineaments seen on satellite images are of particular interest. A portion of ERTS-1 frame 1407-17193 (3 Sept. 1973) was used for mapping lineaments and producing an iso-lineament intersection map. Skylab photography over the area of prime area was not useable due to snow cover. Once the lineaments were mapped, a grid with 2.5 km spacing was overlayed on the map and the lineament intersections occurring within each grid square were counted and the number plotted in the center of the grid square. These numbers were then contoured producing a contour map of equal lineament intersection. It is believed that the areas of high intersection concentration would be the most favorable area for ore mineralization if favorable host rocks are also present. These highly fractured areas would act as conduits for carrying the ore forming solutions to the site of deposition in a favorable host rock. Two of the six areas of high intersection concentration are over areas of present or past mining camps and small claims are known to exist near the others. These would be prime target areas for future mineral exploration.

  20. Multispectral Fluorescence Imaging During Robot-assisted Laparoscopic Sentinel Node Biopsy: A First Step Towards a Fluorescence-based Anatomic Roadmap.

    Science.gov (United States)

    van den Berg, Nynke S; Buckle, Tessa; KleinJan, Gijs H; van der Poel, Henk G; van Leeuwen, Fijs W B

    2017-07-01

    During (robot-assisted) sentinel node (SN) biopsy procedures, intraoperative fluorescence imaging can be used to enhance radioguided SN excision. For this combined pre- and intraoperative SN identification was realized using the hybrid SN tracer, indocyanine green-(99m)Tc-nanocolloid. Combining this dedicated SN tracer with a lymphangiographic tracer such as fluorescein may further enhance the accuracy of SN biopsy. Clinical evaluation of a multispectral fluorescence guided surgery approach using the dedicated SN tracer ICG-(99m)Tc-nanocolloid, the lymphangiographic tracer fluorescein, and a commercially available fluorescence laparoscope. Pilot study in ten patients with prostate cancer. Following ICG-(99m)Tc-nanocolloid administration and preoperative lymphoscintigraphy and single-photon emission computed tomograpy imaging, the number and location of SNs were determined. Fluorescein was injected intraprostatically immediately after the patient was anesthetized. A multispectral fluorescence laparoscope was used intraoperatively to identify both fluorescent signatures. Multispectral fluorescence imaging during robot-assisted radical prostatectomy with extended pelvic lymph node dissection and SN biopsy. (1) Number and location of preoperatively identified SNs. (2) Number and location of SNs intraoperatively identified via ICG-(99m)Tc-nanocolloid imaging. (3) Rate of intraoperative lymphatic duct identification via fluorescein imaging. (4) Tumor status of excised (sentinel) lymph node(s). (5) Postoperative complications and follow-up. Near-infrared fluorescence imaging of ICG-(99m)Tc-nanocolloid visualized 85.3% of the SNs. In 8/10 patients, fluorescein imaging allowed bright and accurate identification of lymphatic ducts, although higher background staining and tracer washout were observed. The main limitation is the small patient population. Our findings indicate that a lymphangiographic tracer can provide additional information during SN biopsy based on ICG-(99m

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  2. Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data

    Science.gov (United States)

    Lisenko, S. A.

    2017-05-01

    An algorithm is proposed for making charts of the distribution of water vapor in the atmosphere based on multispectral images of the earth by the Ocean and Land Color Instrument (OLCI) on board of the European research satellite Sentinel-3. The algorithm is based on multiple regression fits of the spectral brightness coefficients at the upper boundary of the atmosphere, the geometric parameters of the satellite location (solar and viewing angles), and the total water vapor content in the atmosphere. A regression equation is derived from experimental data on the variation in the optical characteristics of the atmosphere and underlying surface, together with Monte-Carlo calculations of the radiative transfer characteristics. The equation includes the brightness coefficients in the near IR channels of the OLCI for the absorption bands of water vapor and oxygen, as well as for the transparency windows of the atmosphere. Together these make it possible to eliminate the effect of the reflection spectrum of the underlying surface and air pressure on the accuracy of the measurements. The algorithm is tested using data from a prototype OLCI, the medium resolution imaging spectrometer (MERIS). A sample chart of the distribution of water vapor in the atmosphere over Eastern Europe is constructed without using subsatellite data and digital models of the surface relief. The water vapor contents in the atmosphere determined using MERIS images and data provided by earthbound measurements with the aerosol robotic network (AERONET) are compared with a mean square deviation of 1.24 kg/m2.

  3. 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.

  4. Validation of an Innovative Satellite-Based UV Dosimeter

    Science.gov (United States)

    Morelli, Marco; Masini, Andrea; Simeone, Emilio; Khazova, Marina

    2016-08-01

    We present an innovative satellite-based UV (ultraviolet) radiation dosimeter with a mobile app interface that has been validated by exploiting both ground-based measurements and an in-vivo assessment of the erythemal effects on some volunteers having a controlled exposure to solar radiation.Both validations showed that the satellite-based UV dosimeter has a good accuracy and reliability needed for health-related applications.The app with this satellite-based UV dosimeter also includes other related functionalities such as the provision of safe sun exposure time updated in real-time and end exposure visual/sound alert. This app will be launched on the global market by siHealth Ltd in May 2016 under the name of "HappySun" and available both for Android and for iOS devices (more info on http://www.happysun.co.uk).Extensive R&D activities are on-going for further improvement of the satellite-based UV dosimeter's accuracy.

  5. 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...

  6. A Satellite Based Fog Study of the Korean Peninsula

    Science.gov (United States)

    2007-06-01

    total number of fog and fog likely days detected from the two MODIS satellites, Aqua and Tera , respectively. Results from all nine areas of...trends in fog detection based on the satellite differences. 46 0 20 40 60 80 100 120 N um be r o f D ay s 1 2 3 4 5 6 7 8 9 Areas Four Month Tera vs...Aqua Fog Totals Tera Fog Tera Fog Likely Aqua Fog Aqua Fog Likely Figure 29. Comparisons of the four month total number of fog and fog likely days

  7. Satellite Type Estination from Ground-based Photometric Observation

    Science.gov (United States)

    Endo, T.; Ono, H.; Suzuki, J.; Ando, T.; Takanezawa, T.

    2016-09-01

    The optical photometric observation is potentially a powerful tool for understanding of the Geostationary Earth Orbit (GEO) objects. At first, we measured in laboratory the surface reflectance of common satellite materials, for example, Multi-layer Insulation (MLI), mono-crystalline silicon cells, and Carbon Fiber Reinforced Plastic (CFRP). Next, we calculated visual magnitude of a satellite by simplified shape and albedo. In this calculation model, solar panels have dimensions of 2 by 8 meters, and the bus area is 2 meters squared with measured optical properties described above. Under these conditions, it clarified the brightness can change the range between 3 and 4 magnitudes in one night, but color index changes only from 1 to 2 magnitudes. Finally, we observed the color photometric data of several GEO satellites visible from Japan multiple times in August and September 2014. We obtained that light curves of GEO satellites recorded in the B and V bands (using Johnson filters) by a ground-base optical telescope. As a result, color index changed approximately from 0.5 to 1 magnitude in one night, and the order of magnitude was not changed in all cases. In this paper, we briefly discuss about satellite type estimation using the relation between brightness and color index obtained from the photometric observation.

  8. Trellis-coded CPM for satellite-based mobile communications

    Science.gov (United States)

    Abrishamkar, Farrokh; Biglieri, Ezio

    1988-01-01

    Digital transmission for satellite-based land mobile communications is discussed. To satisfy the power and bandwidth limitations imposed on such systems, a combination of trellis coding and continuous-phase modulated signals are considered. Some schemes based on this idea are presented, and their performance is analyzed by computer simulation. The results obtained show that a scheme based on directional detection and Viterbi decoding appears promising for practical applications.

  9. Multispectral Airborne Laser Scanning for Automated Map Updating

    Science.gov (United States)

    Matikainen, Leena; Hyyppä, Juha; Litkey, Paula

    2016-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with multispectral information from aerial images, has shown its high feasibility for automated mapping processes. Recently, the first multispectral airborne laser scanners have been launched, and multispectral information is for the first time directly available for 3D ALS point clouds. This article discusses the potential of this new single-sensor technology in map updating, especially in automated object detection and change detection. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from a random forests analysis suggest that the multispectral intensity information is useful for land cover classification, also when considering ground surface objects and classes, such as roads. An out-of-bag estimate for classification error was about 3% for separating classes asphalt, gravel, rocky areas and low vegetation from each other. For buildings and trees, it was under 1%. According to feature importance analyses, multispectral features based on several channels were more useful that those based on one channel. Automatic change detection utilizing the new multispectral ALS data, an old digital surface model (DSM) and old building vectors was also demonstrated. Overall, our first analyses suggest that the new data are very promising for further increasing the automation level in mapping. The multispectral ALS technology is independent of external illumination conditions, and intensity images produced from the data do not include shadows. These are significant advantages when the development of automated classification and change detection procedures is considered.

  10. Multispectral Image Processing for Plants

    Science.gov (United States)

    Miles, Gaines E.

    1991-01-01

    The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

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

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    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 measur- ing 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

  12. Possible satellite-based observations of the 1997 Leonid meteoroids

    Energy Technology Data Exchange (ETDEWEB)

    Pongratz, M.B.; Carlos, R.C.; Cayton, T.

    1998-12-01

    The Block IIA GPS satellites are equipped with a sensor designed to detect electromagnetic transients. Several phenomena will produce triggers in this sensor. They include earth-based electromagnetic transients such as lightning and two space-based phenomena--deep dielectric discharge and meteoroid or hyper-velocity micro-gram particle impact (HMPI). Energetic electrons in the GPS environment cause the deep dielectric charging. HMPIs cause triggers through the transient electric fields generated by the ejecta plasma. During the 1997 Leonid passage the energetic particle fluxes were very low. In the presence of such low fluxes the typical median trigger rate is 20 per minute with a standard deviation of about 20 per minute. Between 0800 UT and 1200 UT on November 17, 1997, the sensor on a specially configured satellite observed trigger rates more than 10 sigma above the nominal median rate. Sensors on other Block IIA GPS satellites also observed excess triggers during November. Detection is enhanced when the sensor antenna is oriented into the Leonid radiant. While many questions persist the authors feel that it is likely that the excess events during the November interval were caused by the close approach of the satellites to the Leonid meteoroid path.

  13. An Ontology Based Methodology for Satellite Data Semantic Interoperability

    Directory of Open Access Journals (Sweden)

    ABBURU, S.

    2015-08-01

    Full Text Available Satellites and ocean based observing system consists of various sensors and configurations. These observing systems transmit data in heterogeneous file formats and heterogeneous vocabulary from various data centers. These data centers maintain a centralized data management system that disseminates the observations to various research communities. Currently, different data naming conventions are being used by existing observing systems, thus leading to semantic heterogeneity. In this work, sensor data interoperability and semantics of the data are being addressed through ontologies. The present work provides an effective technical solution to address semantic heterogeneity through semantic technologies. These technologies provide interoperability, capability to build knowledge base, and framework for semantic information retrieval by developing an effective concept vocabulary through domain ontologies. The paper aims at a new methodology to interlink the multidisciplinary and heterogeneous sensor data products. A four phase methodology has been implemented to address satellite data semantic interoperability. The paper concludes with the evaluation of the methodology by linking and interfacing multiple ontologies to arrive at ontology vocabulary for sensor observations. Data from Indian Meteorological satellite INSAT-3D satellite have been used as a typical example to illustrate the concepts. This work on similar lines can also be extended to other sensor observations.

  14. Satellite Based Extrusion Rates for the 2006 Augustine Eruption

    Science.gov (United States)

    Dehn, J.; Bailey, J. E.; Dean, K. G.; Skoog, R.; Valcic, L.

    2006-12-01

    Extrusion rates were calculated from polar orbiting infrared satellite data for the 2006 eruption of Augustine Volcano, Alaska. The pixel integrated brightness temperatures from the satellite data were converted to estimates of ground temperature by making assumptions and using first hand observations about the geometry of the hot area (lava dome, flows and pyroclastic flow deposits) relative to the cold area in the kilometer scale pixels. Extrusion rate is calculated by assuming that at a given temperature, a lava emits an amount of radiation proportional to its volume. On ten occasions during the activity, helicopter based infrared imagers were used to validate the satellite observations. The pre-January 11 thermal activity was not significantly above background in satellite data. The first strong thermal anomalies were recorded during the first explosive phase on January 11. During successive explosive phases in January, bright thermal signals were observed, often saturating the sensors. Large areas (many km2) were observed to be warm in the satellite data, indicative of pyroclastic flows. Sometime during or after January 29, during a phase of sustained ash emission, the thermal signal became persistent, suggesting the beginning of lava effusion. The extrusion rates derived from satellite data varied from 0 to nearly 7 m3/s, giving an eruption rate of 2.7 m3/s. The extrusion event produced two blocky lava flows which moved down the north flank of the volcano. Extrusion occurred through at least March 15 (day 76) when a sharp drop in extrusion rate and thermal signal is observed. Based on the derived extrusion rates, it is estimated that 18 million m3 of lava was extruded during the course of the eruption. This value agreed well with photogrammetric measurements, but does not agree with volumes derived through subtraction of digital elevation models post- and pre- eruption. It should be noted that the thermal approach only works for hot lavas, and does not

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

    KAUST Repository

    Lopez Valencia, Oliver M.

    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. The principle of the positioning system based on communication satellites

    Institute of Scientific and Technical Information of China (English)

    AI GuoXiang; SHI HuLi; WU HaiTao; LI ZhiGang; GUO Ji

    2009-01-01

    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 satelIites,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 ignal 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 re 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 measurement,transmission and receiving

  17. Land use change detection based on multi-date imagery from different satellite sensor systems

    Science.gov (United States)

    Stow, Douglas A.; Collins, Doretta; Mckinsey, David

    1990-01-01

    An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

  18. Development of a technique based on multi-spectral imaging for monitoring the conservation of cultural heritage objects.

    Science.gov (United States)

    Marengo, Emilio; Manfredi, Marcello; Zerbinati, Orfeo; Robotti, Elisa; Mazzucco, Eleonora; Gosetti, Fabio; Bearman, Greg; France, Fenella; Shor, Pnina

    2011-11-14

    A new approach for monitoring the state of conservation of cultural heritage objects surfaces is being developed. The technique utilizes multi-spectral imaging, multivariate analysis and statistical process control theory for the automatic detection of a possible deterioration process, its localization and identification, and the wavelengths most sensitive to detecting this before the human eye can detect the damage or potential degradation changes occur. A series of virtual degradation analyses were performed on images of parchment in order to test the proposed algorithm in controlled conditions. The spectral image of a Dead Sea Scroll (DSS) parchment, IAA (Israel Antiquities Authority) inventory plate # 279, 4Q501 Apocryphal Lamentations B, taken during the 2008 Pilot of the DSS Digitization Project, was chosen for the simulation.

  19. 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.

  20. Multi-spectral pyrometry—a review

    Science.gov (United States)

    Araújo, António

    2017-08-01

    In pyrometry measurements, the unknown target emissivity is a critical source of uncertainty, especially when the emissivity is low. Aiming to overcome this problem, various multi-spectral pyrometry systems and processing techniques have been proposed in the literature. Basically, all multi-spectral systems are based on the same principle: the radiation emitted by the target is measured at different channels having different spectral characteristics, and the emissivity is modelled as a function of wavelength with adjustable parameters to be obtained empirically, resulting in a system of equations whose solution is the target temperature and the parameters of the emissivity function. The present work reviews the most important multi-spectral developments. Concerning the spectral width of the measurement channels, multi-spectral systems are divided into multi-wavelength (monochromatic channels) and multi-band (wide-band channels) systems. Regarding the number of unknowns and equations (one equation per channel), pyrometry systems can either be determined (same number of unknowns and equations, having a unique solution) or overdetermined (more equations than unknowns, to be solved by least-squares). Generally, higher-order multi-spectral systems are overdetermined, since the uncertainty of the solutions obtained from determined systems increases as the number of channels increases, so that determined systems normally have less than four channels. In terms of the spectral characteristics of the measurement channels, narrow bands, far apart from each other and shifted towards lower wavelengths, seem to provide more accurate solutions. Many processing techniques have been proposed, but they strongly rely on the relationship between emissivity and wavelength, which is, in turn, strongly dependent on the characteristics of a particular target. Several accurate temperature and/or emissivity results have been reported, but no universally accepted multi-spectral technique has

  1. Estimation of evapotranspiration over heterogeneous surfaces based on HJ1B satellite data in China

    Science.gov (United States)

    Xin, Xiaozhou; Jiao, Jingjun

    2014-05-01

    The HJ1B satellite of China is equipped with two CCD cameras with 30m resolution and one infrared multispectral camera with 300m resolution. And the revisit period of HJ1B satellite is 4 days. Compared to MODIS or TM, HJ1B data has the advantage of high spatial-temporal resolution. Methodology based on the one-source energy balance model was developed for net radiation (Rn), soil heat flux (G), sensible heat flux (H) and latent heat flux (LE) estimation from HI1B data. The core procedure is a scheme that was designed for correcting the spatial scale error over heterogeneous surfaces by taking advantage of the HJ1B data characteristics, i.e., high resolution CCD data (30m) along with thermal data (300m). First of all, a regression relationship between Ts and NDVI was built up at 300m resolution based on the data of Ts and NDVI of the selected "pure" pixels. And then the relationship function was applied at 30m resolution to derive Ts at high resolution, i.e., at the subpixel level. Furthermore, the 30m land class data was also used in the parameterization of surface energy balance and surface aerodynamic transfer, which is important since significant error may be resulted by using one land class type to represent the whole mixed pixel. By using high resolution NDVI and land class data, we are able to mitigate the spatial scale error of the mixed pixels at 300m resolution. At last, the 300m surface energy fluxes were obtained by aggregation of the 30m estimation. HJ1B data at Hai river basin in north China in 2010 were used to verify this method. The eddy-correlation system data were used as validation. The results of the method were compared with the results of a simple method that estimates the fluxes at 300m by aggregating all of the input parameters to 300m. It is shown that the method proposed in this study shows higher agreement with in-suit measurement, and the fluxes maps also show much more details of the spatial variation. By using this method, it can be

  2. Multispectral colormapping using penalized least square regression

    DEFF Research Database (Denmark)

    Dissing, Bjørn Skovlund; Carstensen, Jens Michael; Larsen, Rasmus

    2010-01-01

    based multispectral system with a total of 11 channels in the visible area. To obtain interpretable models, the method estimates the projection coefficients with regard to their neighbors as well as the target. This results in relatively smooth coefficient curves which are correlated with the CIE...

  3. 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.

  4. 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.

  5. Transition, Training, and Assessment of Multispectral Composite Imagery in Support of the NWS Aviation Forecast Mission

    Science.gov (United States)

    Fuell, Kevin; Jedlovec, Gary; Leroy, Anita; Schultz, Lori

    2015-01-01

    The NASA/Short-term Prediction, Research, and Transition (SPoRT) Program works closely with NOAA/NWS weather forecasters to transition unique satellite data and capabilities into operations in order to assist with nowcasting and short-term forecasting issues. Several multispectral composite imagery (i.e. RGB) products were introduced to users in the early 2000s to support hydrometeorology and aviation challenges as well as incident support. These activities lead to SPoRT collaboration with the GOES-R Proving Ground efforts where instruments such as MODIS (Aqua, Terra) and S-NPP/VIIRS imagers began to be used as near-realtime proxies to future capabilities of the Advanced Baseline Imager (ABI). One of the composite imagery products introduced to users was the Night-time Microphysics RGB, originally developed by EUMETSAT. SPoRT worked to transition this imagery to NWS users, provide region-specific training, and assess the impact of the imagery to aviation forecast needs. This presentation discusses the method used to interact with users to address specific aviation forecast challenges, including training activities undertaken to prepare for a product assessment. Users who assessed the multispectral imagery ranged from southern U.S. inland and coastal NWS weather forecast offices (WFOs), to those in the Rocky Mountain Front Range region and West Coast, as well as highlatitude forecasters of Alaska. These user-based assessments were documented and shared with the satellite community to support product developers and the broad users of new generation satellite data.

  6. Satellite Formation Design for Space Based Radar Applications

    Science.gov (United States)

    2007-07-30

    Practical Guidance Methodology for Relative Motion of LEO Spacecraft Based on the Clohessy-Wiltshire Equations,” AAS Paper 04-252, AAS/AIAA Space...Non- Circular Reference Orbit," AAS Paper 01-222, AAS/AIAA Space Flight Mechanics Meeting, Santa Barbara, CA, Feb 11-16, 2001. 11. D. Brouwer ...Small Eccentricities or Inclinations in the Brouwer Theory of the Artificial Satellite,” The Astronomical Journal, Vol. 68, October 1963, pp. 555

  7. Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV

    Directory of Open Access Journals (Sweden)

    Samuel Ortega-Farías

    2016-08-01

    Full Text Available A field experiment was carried out to implement a remote sensing energy balance (RSEB algorithm for estimating the incoming solar radiation (Rsi, net radiation (Rn, sensible heat flux (H, soil heat flux (G and latent heat flux (LE over a drip-irrigated olive (cv. Arbequina orchard located in the Pencahue Valley, Maule Region, Chile (35°25′S; 71°44′W; 90 m above sea level. For this study, a helicopter-based unmanned aerial vehicle (UAV was equipped with multispectral and infrared thermal cameras to obtain simultaneously the normalized difference vegetation index (NDVI and surface temperature (Tsurface at very high resolution (6 cm × 6 cm. Meteorological variables and surface energy balance components were measured at the time of the UAV overpass (near solar noon. The performance of the RSEB algorithm was evaluated using measurements of H and LE obtained from an eddy correlation system. In addition, estimated values of Rsi and Rn were compared with ground-truth measurements from a four-way net radiometer while those of G were compared with soil heat flux based on flux plates. Results indicated that RSEB algorithm estimated LE and H with errors of 7% and 5%, respectively. Values of the root mean squared error (RMSE and mean absolute error (MAE for LE were 50 and 43 W m−2 while those for H were 56 and 46 W m−2, respectively. Finally, the RSEB algorithm computed Rsi, Rn and G with error less than 5% and with values of RMSE and MAE less than 38 W m−2. Results demonstrated that multispectral and thermal cameras placed on an UAV could provide an excellent tool to evaluate the intra-orchard spatial variability of Rn, G, H, LE, NDVI and Tsurface over the tree canopy and soil surface between rows.

  8. Hyperspectral and multispectral ocean color inversions to detect Phaeocystis globosa blooms in coastal waters

    Science.gov (United States)

    Lubac, Bertrand; Loisel, Hubert; Guiselin, Natacha; Astoreca, Rosa; Felipe Artigas, L.; MéRiaux, Xavier

    2008-06-01

    Identification of phytoplankton groups from space is essential to map and monitor algal blooms in coastal waters, but remains a challenge due to the presence of suspended sediments and dissolved organic matter which interfere with phytoplankton signal. On the basis of field measurements of remote sensing reflectance (Rrs(λ)), bio-optical parameters, and phytoplankton cells enumerations, we assess the feasibility of using multispectral and hyperspectral approaches for detecting spring blooms of Phaeocystis globosa (P. globosa). The two reflectance ratios (Rrs(490)/Rrs(510) and Rrs(442.5)/Rrs(490)), used in the multispectral inversion, suggest that detection of P. globosa blooms are possible from current ocean color sensors. The effects of chlorophyll concentration, colored dissolved organic matter (CDOM), and particulate matter composition on the performance of this multispectral approach are investigated via sensitivity analysis. This analysis indicates that the development of a remote sensing algorithm, based on the values of these two ratios, should include information about CDOM concentration. The hyperspectral inversion is based on the analysis of the second derivative of Rrs(λ) (dλ2Rrs). Two criteria, based on the position of the maxima and minima of dλ2Rrs, are established to discriminate the P. globosa blooms from diatoms blooms. We show that the position of these extremes is related to the specific absorption spectrum of P. globosa and is significantly correlated with the relative biomass of P. globosa. This result confirms the advantage of a hyperspectral over multispectral inversion for species identification and enumeration from satellite observations of ocean color.

  9. Efficient enhancing scheme for TCP performance over satellite-based internet

    Institute of Scientific and Technical Information of China (English)

    Wang Lina; Gu Xuemai

    2007-01-01

    Satellite link characteristics drastically degrade transport control protocol (TCP) performance. An efficient performance enhancing scheme is proposed. The improvement of TCP performance over satellite-based Intemet is accomplished by protocol transition gateways at each end ora satellite link. The protocol which runs over a satellite link executes the receiver-driven flow control and acknowledgements- and timeouts-based error control strategies. The validity of this TCP performance enhancing scheme is verified by a series of simulation experiments. Results show that the proposed scheme can efficiently enhance the TCP performance over satellite-based Intemet and ensure that the available bandwidth resources of the satellite link are fully utilized.

  10. Recent development of feature extraction and classification multispectral/hyperspectral images: a systematic literature review

    Science.gov (United States)

    Setiyoko, A.; Dharma, I. G. W. S.; Haryanto, T.

    2017-01-01

    Multispectral data and hyperspectral data acquired from satellite sensor have the ability in detecting various objects on the earth ranging from low scale to high scale modeling. These data are increasingly being used to produce geospatial information for rapid analysis by running feature extraction or classification process. Applying the most suited model for this data mining is still challenging because there are issues regarding accuracy and computational cost. This research aim is to develop a better understanding regarding object feature extraction and classification applied for satellite image by systematically reviewing related recent research projects. A method used in this research is based on PRISMA statement. After deriving important points from trusted sources, pixel based and texture-based feature extraction techniques are promising technique to be analyzed more in recent development of feature extraction and classification.

  11. Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

    Science.gov (United States)

    Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

    2014-10-01

    The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure

  12. 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).

  13. 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

  14. 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.

  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. 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

  17. 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.

  18. 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.

  19. Multispectral Panoramic Imaging System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — International Electronic Machines Corporation, a leader in the design of precision imaging systems, will develop an innovative multispectral, panoramic imaging...

  20. Interoperability of satellite-based augmentation systems for aircraft navigation

    Science.gov (United States)

    Dai, Donghai

    The Federal Aviation Administration (FAA) is pioneering a transformation of the national airspace system from its present ground based navigation and landing systems to a satellite based system using the Global Positioning System (GPS). To meet the critical safety-of-life aviation positioning requirements, a Satellite-Based Augmentation System (SBAS), the Wide Area Augmentation System (WAAS), is being implemented to support navigation for all phases of flight, including Category I precision approach. The system is designed to be used as a primary means of navigation, capable of meeting the Required Navigation Performance (RNP), and therefore must satisfy the accuracy, integrity, continuity and availability requirements. In recent years there has been international acceptance of Global Navigation Satellite Systems (GNSS), spurring widespread growth in the independent development of SBASs. Besides the FAA's WAAS, the European Geostationary Navigation Overlay Service System (EGNOS) and the Japan Civil Aviation Bureau's MTSAT-Satellite Augmentation System (MSAS) are also being actively developed. Although all of these SBASs can operate as stand-alone, regional systems, there is increasing interest in linking these SBASs together to reduce costs while improving service coverage. This research investigated the coverage and availability improvements due to cooperative efforts among regional SBAS networks. The primary goal was to identify the optimal interoperation strategies in terms of performance, complexity and practicality. The core algorithms associated with the most promising concepts were developed and demonstrated. Experimental verification of the most promising concepts was conducted using data collected from a joint international test between the National Satellite Test Bed (NSTB) and the EGNOS System Test Bed (ESTB). This research clearly shows that a simple switch between SBASs made by the airborne equipment is the most effective choice for achieving the

  1. SynSen PFT: Synergistic Retrieval of Phytoplankton Functional Types from Space From Hyper-and Multispectral Measurements

    Science.gov (United States)

    Soppa, Mariana A.; Loza, Svetlana N.; Dinter, Tilman; Wolanin, Aleksandra; Bricaud, Annick; Brewein, Robert; Rozanov, Vladimir; Barcher, Astrid

    2016-08-01

    To gain knowledge on the role of marine phytoplankton in the global marine ecosystem and biogeochemical cycles, information on the global distribution of major phytoplankton functional types is essential. The Synergistic Retrieval of Phytoplankton Functional Types from Space from Hyper- and Multispectral Measurements project (SynSenPFT) aims to improve the retrieval of phytoplankton types (PFTs) from space by exploring the synergistic use of low-spatial-hyper- spectral and high-spatial-multi-spectral satellite data. Three PFTs are investigated: diatoms, coccolithophores and cyanobacteria. The work involves the improvement/revision of existing PFT algorithms based on hyper- (PhytoDOAS, [1]) and multi-spectral (OC- PFT, [2]) datasets, development of synergistic PFT products combining the retrievals of these two algorithms and intercomparison of the synergistic PFT products with those derived from other methods [3,4,5].

  2. Novel wearable-type biometric devices based on skin tissue optics with multispectral LED–photodiode matrix

    Science.gov (United States)

    Jo, Young Chang; Kim, Hae Na; Kang, Jae Hwan; Hong, Hyuck Ki; Choi, Yeon Shik; Jung, Suk Won; Kim, Sung Phil

    2017-04-01

    In this study, we examined the possibility of using a multispectral skin photomatrix (MSP) module as a novel biometric device. The MSP device measures optical patterns of the wrist skin tissue. Optical patterns consist of 2 × 8 photocurrent intensities of photodiode arrays, which are generated by optical transmission and diffuse reflection of photons from LED light sources with variable wavelengths into the wrist skin tissue. Optical patterns detected by the MSP device provide information on both the surface and subsurface characteristics of the human skin tissue. We found that in the 21 subjects we studied, they showed their unique characteristics, as determined using several wavelengths of light. The experimental results show that the best personal identification accuracy can be acquired using a combination of infrared light and yellow light. This novel biometric device, the MSP module, exhibited an excellent false acceptance rate (FAR) of 0.3% and a false rejection rate (FRR) of 0.0%, which are better than those of commercialized biometric devices such as a fingerprint biometric system. From these experimental results, we found that people exhibit unique optical patterns of their inner-wrist skin tissue and this uniqueness could be used for developing novel high-accuracy personal identification devices.

  3. 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 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.

  4. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  5. Aerosol Remote Sensing Applications for Airborne Multiangle, Multispectral Shortwave Radiometers

    Science.gov (United States)

    von Bismarck, Jonas; Ruhtz, Thomas; Starace, Marco; Hollstein, André; Preusker, René; Fischer, Jürgen

    2010-05-01

    Aerosol particles have an important impact on the surface net radiation budget by direct scattering and absorption (direct aerosol effect) of solar radiation, and also by influencing cloud formation processes (semi-direct and indirect aerosol effects). To study the former, a number of multispectral sky- and sunphotometers have been developed at the Institute for Space Sciences of the Free University of Berlin in the past two decades. The latest operational developments were the multispectral aureole- and sunphotometer FUBISS-ASA2, the zenith radiometer FUBISS-ZENITH, and the nadir polarimeter AMSSP-EM, all designed for a flexible use on moving platforms like aircraft or ships. Currently the multiangle, multispectral radiometer URMS/AMSSP (Universal Radiation Measurement System/ Airborne Multispectral Sunphotometer and Polarimeter) is under construction for a Wing-Pod of the high altitude research aircraft HALO operated by DLR. The system is expected to have its first mission on HALO in 2011. The algorithms for the retrieval of aerosol and trace gas properties from the recorded multidirectional, multispectral radiation measurements allow more than deriving standard products, as for instance the aerosol optical depth and the Angstrom exponent. The radiation measured in the solar aureole contains information about the aerosol phasefunction and therefore allows conclusions about the particle type. Furthermore, airborne instrument operation allows vertically resolved measurements. An inversion algorithm, based on radiative transfer simulations and additionally including measured vertical zenith-radiance profiles, allows conclusions about the aerosol single scattering albedo and the relative soot fraction in aerosol layers. Ozone column retrieval is performed evaluating measurements from pixels in the Chappuis absorption band. A retrieval algorithm to derive the water-vapor column from the sunphotometer measurements is currently under development. Of the various airborne

  6. A Time and Space-based Dynamic IP Routing in Broadband Satellite Networks

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The topology architecture, characteristics and routing technologies of broadband satellite networks are studied in this paper. The authors propose the routing scheme of satellite networks and design a time and space-based distributed routing algorithm whose complexity is O(1). Simulation results aiming at satellite mobility show that the new algorithm can determine the minimum propagation delay paths effectively.

  7. Fast Lossless Compression of Multispectral-Image Data

    Science.gov (United States)

    Klimesh, Matthew

    2006-01-01

    An algorithm that effects fast lossless compression of multispectral-image data is based on low-complexity, proven adaptive-filtering algorithms. This algorithm is intended for use in compressing multispectral-image data aboard spacecraft for transmission to Earth stations. Variants of this algorithm could be useful for lossless compression of three-dimensional medical imagery and, perhaps, for compressing image data in general.

  8. Scheduler for monitoring objects orbiting earth using satellite-based telescopes

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-04-28

    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.

  9. Dialectical multispectral classification of diffusion-weighted magnetic resonance images as an alternative to apparent diffusion coefficients maps to perform anatomical analysis.

    Science.gov (United States)

    Santos, W P; Assis, F M; Souza, R E; Santos Filho, P B; Lima Neto, F B

    2009-09-01

    Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. A considerable number of current methods of analysis are based on parametric statistics. Alternatively, some methods in computational intelligence are inspired by biology and other sciences. Here we claim that philosophy can be also considered as a source of inspiration. This work proposes the objective dialectical method (ODM): a method for classification based on the philosophy of praxis. ODM is instrumental in assembling evolvable mathematical tools to analyze multispectral images. In the case study described in this paper, multispectral images are composed of diffusion-weighted (DW) magnetic resonance (MR) images. The results are compared to ground-truth images produced by polynomial networks using a morphological similarity index. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map. Such results proved that gray and white matter can be distinguished in DW-MR multispectral analysis and, consequently, DW-MR images can also be used to furnish anatomical information.

  10. Multispectral imaging system based on light-emitting diodes for the detection of melanomas and basal cell carcinomas: a pilot study

    Science.gov (United States)

    Delpueyo, Xana; Vilaseca, Meritxell; Royo, Santiago; Ares, Miguel; Rey-Barroso, Laura; Sanabria, Ferran; Puig, Susana; Pellacani, Giovanni; Noguero, Fernando; Solomita, Giuseppe; Bosch, Thierry

    2017-06-01

    This article proposes a multispectral system that uses the analysis of the spatial distribution of color and spectral features to improve the detection of skin cancer lesions, specifically melanomas and basal cell carcinomas. The system consists of a digital camera and light-emitting diodes of eight different wavelengths (414 to 995 nm). The parameters based on spectral features of the lesions such as reflectance and color, as well as others empirically computed using reflectance values, were calculated pixel-by-pixel from the images obtained. Statistical descriptors were calculated for every segmented lesion [mean (x˜), standard deviation (σ), minimum, and maximum]; descriptors based on the first-order statistics of the histogram [entropy (Ep), energy (En), and third central moment (μ3)] were also obtained. The study analyzed 429 pigmented and nonpigmented lesions: 290 nevi and 139 malignant (95 melanomas and 44 basal cell carcinomas), which were split into training and validation sets. Fifteen parameters were found to provide the best sensitivity (87.2% melanomas and 100% basal cell carcinomas) and specificity (54.5%). The results suggest that the extraction of textural information can contribute to the diagnosis of melanomas and basal cell carcinomas as a supporting tool to dermoscopy and confocal microscopy.

  11. Comparing robust and physics-based sea surface temperature retrievals for high resolution, multi-spectral thermal sensors using one or multiple looks

    Energy Technology Data Exchange (ETDEWEB)

    Borel, C.C.; Clodius, W.B.; Szymanski, J.J.; Theiler, J.P.

    1999-04-04

    With the advent of multi-spectral thermal imagers such as EOS's ASTER high spatial resolution thermal imagery of the Earth's surface will soon be a reality. Previous high resolution sensors such as Landsat 5 had only one spectral channel in the thermal infrared and its utility to determine absolute sea surface temperatures was limited to 6-8 K for water warmer than 25 deg C. This inaccuracy resulted from insufficient knowledge of the atmospheric temperature and water vapor, inaccurate sensor calibration, and cooling effects of thin high cirrus clouds. The authors will present two studies of algorithms and compare their performance. The first algorithm they call robust since it retrieves sea surface temperatures accurately over a fairly wide range of atmospheric conditions using linear combinations of nadir and off-nadir brightness temperatures. The second they call physics-based because it relies on physics-based models of the atmosphere. It attempts to come up with a unique sea surface temperature which fits one set of atmospheric parameters.

  12. 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.

  13. 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.

  14. Characteristics of the Landsat Multispectral Data System

    Science.gov (United States)

    Taranik, James V.

    1978-01-01

    Landsat satellites were launched into orbit in 1972 and 1975. Additional Landsat satellites are planned for launch in 1978 and 1981. The satellites orbit the Earth at an altitude of approximately 900 km and each can obtain repetitive coverage of cloud-free areas every 18 days. A sun-synchronous orbit is used to insure repeatable illumination conditions. Repetitive satellite coverage allows optimal cover conditions for geologic applications to be identified. Seasonal variations in solar illumination must be analyzed to select the best Landsat data for geologic applications. Landsat data may be viewed in stereo where there is sufficient sidelap and sufficient topographic relief. Landsat-1 ceased operation on January 10, 1978. Landsat-2 detects, only solar radiation that is reflected from the Earth's surface in visible and near-visible wavelengths. The third Landsat will also detect emitted thermal radiation. The multispectral scanner (MSS) was the only sensing instrument used on the first two satellites. The MSS on Landsats-1 and -2 detect radiation which is reflected from a 79 m by 79 m area, and the data are formatted as if the measurement was made from a 56 m by 79 m area. The MSS integrates spectral response from all cover types within the 79 m by 79 m area. The integrated spectral signature often does not resemble the spectral signature from individual cover types, and the integrated signature is also modified by the atmosphere. Landsat-1 and -2 data are converted to 70 mm film and computer compatible tapes (CCT's) at Goddard Space Flight Center (GSFC); these are shipped to the EROS Data Center (EDC) for duplication and distribution to users. Landsat-C data will be converted to 241 mm-wide film and CCT's at EDC. Landsat-D data will be relayed from the satellite directly to geosynchronous satellites and then to the United States from any location on Earth.

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

    Science.gov (United States)

    Salamonowicz, P.H.

    1986-01-01

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

  16. Multispectral Image Enhancement Through Adaptive Wavelet Fusion

    Science.gov (United States)

    2017-02-08

    Filtering. PeerJ Computer Science, 2, e72. doi: 10.7717/peerj-cs.72. https://peerj.com/articles/cs-72/ 6 Coloring multiband night vision images...decompose the source images into base and detail layers at multiple levels of resolution. Then, frequency-tuned filtering is used to compute saliency...obtains state-of-the-art performance for the fusion of multispectral night vision images. The method has a simple implementation and is computationally

  17. Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

    Directory of Open Access Journals (Sweden)

    Mohammad Zahidul H. Bhuiyan

    2010-01-01

    Full Text Available Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS, such as the Global Positioning System (GPS or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellite-receiver transit time offset of the Line-Of-Sight (LOS signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s, phase(s, and delay(s of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK- and Sine Binary Offset Carrier- (SinBOC- modulated signals is also analyzed in closed loop model with the new Composite

  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. Transferring results from NIR-hyperspectral to NIR-multispectral imaging systems: A filter-based simulation applied to the classification of Arabica and Robusta green coffee.

    Science.gov (United States)

    Calvini, Rosalba; Amigo, Jose Manuel; Ulrici, Alessandro

    2017-05-15

    Due to the differences in terms of both price and quality, the availability of effective instrumentation to discriminate between Arabica and Robusta coffee is extremely important. To this aim, the use of multispectral imaging systems could provide reliable and accurate real-time monitoring at relatively low costs. However, in practice the implementation of multispectral imaging systems is not straightforward: the present work investigates this issue, starting from the outcome of variable selection performed using a hyperspectral system. Multispectral data were simulated considering four commercially available filters matching the selected spectral regions, and used to calculate multivariate classification models with Partial Least Squares-Discriminant Analysis (PLS-DA) and sparse PLS-DA. Proper strategies for the definition of the training set and the selection of the most effective combinations of spectral channels led to satisfactory classification performances (100% classification efficiency in prediction of the test set). Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Application of multispectral systems for the diagnosis of plant diseases

    Science.gov (United States)

    Feng, Jie; Liao, Ningfang; Wang, Guolong; Luo, Yongdao; Liang, Minyong

    2008-03-01

    Multispectral imaging technique combines space imaging and spectral detecting. It can obtain the spectral information and image information of object at the same time. Base on this concept, A new method proposed multispectral camera system to demonstrated plant diseases. In this paper, multispectral camera was used as image capturing device. It consists of a monochrome CCD camera and 16 narrow-band filters. The multispectral images of Macbeth 24 color patches are captured under the illumination of incandescent lamp in this experiment The 64 spectral reflectances of each color patches are calculated using Spline interpolation from 400 to 700nm in the process. And the color of the object is reproduced from the estimated spectral reflectance. The result for reproduction is contrast with the color signal using X-rite PULSE spectrophotometer. The average and maximum ΔΕ * ab are 9.23 and 12.81. It is confirmed that the multispectral system realizes the color reproduction of plant diseases from narrow-band multispectral image.

  1. Multispectral device for help in diagnosis

    Science.gov (United States)

    Delporte, Céline; Ben Chouikha, Mohamed; Sautrot, Sylvie; Viénot, Françoise; Alquié, Georges

    2012-03-01

    In order to build biological tissues spectral characteristics database to be used in a multispectral imaging system a tissues optical characterization bench is developed and validated. Several biological tissue types have been characterized in vitro and ex vivo with our device such as beef, turkey and pork muscle and beef liver. Multispectral images obtained have been analyzed in order to study the dispersion of biological tissues spectral luminance factor. Tissue internal structure inhomogeneity was identified as a phenomenon contributing to the dispersion of spectral luminance factor. This dispersion of spectral luminance factor could be a characteristic of the tissue. A method based on envelope technique has been developed to identify and differentiate biological tissues in the same scene. This method applied to pork tissues containing muscle and fat gives detection rates of 59% for pork muscle and 14% for pork fat.

  2. Internet-Protocol-Based Satellite Bus Architecture Designed

    Science.gov (United States)

    Slywczak, Richard A.

    2004-01-01

    NASA is designing future complex satellite missions ranging from single satellites and constellations to space networks and sensor webs. These missions require more interoperability, autonomy, and coordination than previous missions; in addition, a desire exists to have scientists retrieve data directly from the satellite rather than a central distribution source. To meet these goals, NASA has been studying the possibility of extending the Transmission Control Protocol/Internet Protocol (TCP/IP) suite for spacebased applications.

  3. Satellite-based Flood Modeling Using TRMM-based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Greg Easson

    2007-12-01

    Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

  4. Dsm Based Orientation of Large Stereo Satellite Image Blocks

    Science.gov (United States)

    d'Angelo, P.; Reinartz, P.

    2012-07-01

    High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. Scene based method and a bundle block adjustment based correction are developed and evaluated for a test site covering the nothern part of Italy, for which 405 Cartosat-1 Stereopairs are available. Both methods are tested against independent ground truth. Checks against this ground truth indicate a lateral error of 10 meters.

  5. Fusion of multispectral and panchromatic images based on PCA and NSCT%基于PCA和NSCT的多光谱图像和全色图像的融合

    Institute of Scientific and Technical Information of China (English)

    时海亮; 魏涛; 辛向军; 裴云霞

    2012-01-01

    A novel fusion method is proposed for multispectral and panchromatic satellite images using Principal Component Analysis (PC A) and Nonsubsampled Contourlet Transform (NSCT). This method first performs PC A on MS, and NSCT on PAN and the first principal component(PC') to get corresponding low-frequency and high-frequency coefficients. Then fuses the approximation coefficients using PCA again for the tradeoff between the spectral and spatial information, and fuses the subbands coefficients based on Structural Similarity Index(SSIM) and local Sobel average gradient for the spatial detail information. A fused image is formed through inverse NSCT and inverse PCA. Experimental results show that the proposed fusion method can effectively preserve spectral information while improving the spatial quality, and outperforms the general HIS-, PCA-, Wavelet-, Contourlet-based fusion methods.%研究了主分量分析(PCA)和非下采样Contourlet变换(NSCT),提出一种新的多光谱图像和全色图像的融合算法.该方法对多光谱图像进行PCA变换,对所得的第一主分量(PC1)以及全色图像进行NSCT变换.对二者的低频近似系数再次进行PCA变换以寻求多光谱信息和空间信息的平衡;对于高频细节系数,通过结构相似性指标(SSIM)和局部Sobel梯度进行融合,进一步提高空间信息量;经过逆NSCT和逆PCA变换得到融合图像.实验结果表明,提出的方法在增强融合图像空间细节表现能力的同时,尽可能地保留了多光谱图像的光谱信息,优于传统的基于IHS、PCA、小波变换和Contourlet变换的融合方法,是有效可行的.

  6. Comparison of satellite reflectance algorithms for estimating ...

    Science.gov (United States)

    We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop simple proxies for algal blooms and to facilitate portability between multispectral satellite imagers for regional algal bloom monitoring. Narrow band hyperspectral aircraft images were upscaled spectrally and spatially to simulate 5 current and near future satellite imaging systems. Established and new Chl-a algorithms were then applied to the synthetic satellite images and then compared to calibrated Chl-a water truth measurements collected from 44 sites within one hour of aircraft acquisition of the imagery. Masks based on the spatial resolution of the synthetic satellite imagery were then applied to eliminate mixed pixels including vegetated shorelines. Medium-resolution Landsat and finer resolution data were evaluated against 29 coincident water truth sites. Coarse-resolution MODIS and MERIS-like data were evaluated against 9 coincident water truth sites. Each synthetic satellite data set was then evaluated for the performance of a variety of spectrally appropriate algorithms with regard to the estimation of Chl-a concentrations against the water truth data set. The goal is to inform water resource decisions on the appropriate satellite data acquisition and processing for the es

  7. 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....

  8. 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....

  9. 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.

  10. 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.

  11. 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.

  12. A virtual maintenance-based approach for satellite assembling and troubleshooting assessment

    Science.gov (United States)

    Geng, Jie; Li, Ying; Wang, Ranran; Wang, Zili; Lv, Chuan; Zhou, Dong

    2017-09-01

    In this study, a Virtual Maintenance (VM)-based approach for satellite troubleshooting assessment is proposed. By focusing on various elements in satellite assemble troubleshooting, such as accessibility, ergonomics, wiring, and extent of damage, a systematic, quantitative, and objective assessment model is established to decrease subjectivity in satellite assembling and troubleshooting assessment. Afterwards, based on the established assessment model and satellite virtual prototype, an application process of this model suitable for a virtual environment is presented. Finally, according to the application process, all the elements in satellite troubleshooting are analyzed and assessed. The corresponding improvements, which realize the transformation from a conventional way to a virtual simulation and assessment, are suggested, and the flaws in assembling and troubleshooting are revealed. Assembling or troubleshooting schemes can be improved in the early stage of satellite design with the help of a virtual prototype. Repetition in the practical operation is beneficial to companies as risk and cost are effectively reduced.

  13. Testing of Land Cover Classification from Multispectral Airborne Laser Scanning Data

    Science.gov (United States)

    Bakuła, K.; Kupidura, P.; Jełowicki, Ł.

    2016-06-01

    Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud) acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images), spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and last return

  14. Object Based and Pixel Based Classification Using Rapideye Satellite Imager of ETI-OSA, Lagos, Nigeria

    OpenAIRE

    Esther Oluwafunmilayo Makinde; Ayobami Taofeek Salami; James Bolarinwa Olaleye; Oluwapelumi Comfort Okewusi

    2016-01-01

    Several studies have been carried out to find an appropriate method to classify the remote sensing data. Traditional classification approaches are all pixel-based, and do not utilize the spatial information within an object which is an important source of information to image classification. Thus, this study compared the pixel based and object based classification algorithms using RapidEye satellite image of Eti-Osa LGA, Lagos. In the object-oriented approach, the image was segmented to homog...

  15. Design Considerations, Modeling and Analysis for the Multispectral Thermal Imager

    Energy Technology Data Exchange (ETDEWEB)

    Borel, C.C.; Clodius, W.B.; Cooke, B.J.; Smith, B.W.; Weber, P.G.

    1999-02-01

    The design of remote sensing systems is driven by the need to provide cost-effective, substantive answers to questions posed by our customers. This is especially important for space-based systems, which tend to be expensive, and which generally cannot be changed after they are launched. We report here on the approach we employed in developing the desired attributes of a satellite mission, namely the Multispectral Thermal Imager. After an initial scoping study, we applied a procedure which we call: "End-to-end modeling and analysis (EEM)." We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term "end-to-end modeling and analysis." We base the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolves, and as real hardware is tested, we can update the EEM to facilitate trade studies, and to judge, for example, whether components that deviate from specifications are acceptable.

  16. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA from 2003-08-26 to 2012-05-03 (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  17. 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...

  18. 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.

  19. 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.

  20. Population-based geographic access to parent and satellite National Cancer Institute Cancer Center Facilities.

    Science.gov (United States)

    Onega, Tracy; Alford-Teaster, Jennifer; Wang, Fahui

    2017-09-01

    Satellite facilities of National Cancer Institute (NCI) cancer centers have expanded their regional footprints. This study characterized geographic access to parent and satellite NCI cancer center facilities nationally overall and by sociodemographics. Parent and satellite NCI cancer center facilities, which were geocoded in ArcGIS, were ascertained. Travel times from every census tract in the continental United States and Hawaii to the nearest parent and satellite facilities were calculated. Census-based population attributes were used to characterize measures of geographic access for sociodemographic groups. From the 62 NCI cancer centers providing clinical care in 2014, 76 unique parent locations and 211 satellite locations were mapped. The overall proportion of the population within 60 minutes of a facility was 22% for parent facilities and 32.7% for satellite facilities. When satellites were included for potential access, the proportion of some racial groups for which a satellite was the closest NCI cancer center facility increased notably (Native Americans, 22.6% with parent facilities and 39.7% with satellite facilities; whites, 34.8% with parent facilities and 50.3% with satellite facilities; and Asians, 40.0% with parent facilities and 54.0% with satellite facilities), with less marked increases for Hispanic and black populations. Rural populations of all categories had dramatically low proportions living within 60 minutes of an NCI cancer center facility of any type (1.0%-6.6%). Approximately 14% of the population (n = 43,033,310) lived more than 180 minutes from a parent or satellite facility, and most of these individuals were Native Americans and/or rural residents (37% of Native Americans and 41.7% of isolated rural residents). Racial/ethnic and rural populations showed markedly improved geographic access to NCI cancer center care when satellite facilities were included. Cancer 2017;123:3305-11. © 2017 American Cancer Society. © 2017 American

  1. Preliminary Analysis of a Novel SAR Based Emergency System for Earth Orbit Satellites using Galileo

    NARCIS (Netherlands)

    Gill, E.K.A.; Helderweirt, A.

    2010-01-01

    This paper presents a preliminary analysis of a novel Search and Rescue (SAR) based emergency system for Low Earth Orbit (LEO) satellites using the Galileo Global Navigation Satellite System (GNSS). It starts with a description of the space user SAR system including a concept description, mission ar

  2. Operational Testing of Satellite based Hydrological Model (SHM)

    Science.gov (United States)

    Gaur, Srishti; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghavendra P.

    2017-04-01

    Incorporation of the concept of transposability in model testing is one of the prominent ways to check the credibility of a hydrological model. Successful testing ensures ability of hydrological models to deal with changing conditions, along with its extrapolation capacity. For a newly developed model, a number of contradictions arises regarding its applicability, therefore testing of credibility of model is essential to proficiently assess its strength and limitations. This concept emphasizes to perform 'Hierarchical Operational Testing' of Satellite based Hydrological Model (SHM), a newly developed surface water-groundwater coupled model, under PRACRITI-2 program initiated by Space Application Centre (SAC), Ahmedabad. SHM aims at sustainable water resources management using remote sensing data from Indian satellites. It consists of grid cells of 5km x 5km resolution and comprises of five modules namely: Surface Water (SW), Forest (F), Snow (S), Groundwater (GW) and Routing (ROU). SW module (functions in the grid cells with land cover other than forest and snow) deals with estimation of surface runoff, soil moisture and evapotranspiration by using NRCS-CN method, water balance and Hragreaves method, respectively. The hydrology of F module is dependent entirely on sub-surface processes and water balance is calculated based on it. GW module generates baseflow (depending on water table variation with the level of water in streams) using Boussinesq equation. ROU module is grounded on a cell-to-cell routing technique based on the principle of Time Variant Spatially Distributed Direct Runoff Hydrograph (SDDH) to route the generated runoff and baseflow by different modules up to the outlet. For this study Subarnarekha river basin, flood prone zone of eastern India, has been chosen for hierarchical operational testing scheme which includes tests under stationary as well as transitory conditions. For this the basin has been divided into three sub-basins using three flow

  3. Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

    Science.gov (United States)

    Kang, Do Hyuk; Barros, Ana P.; Kim, Edward J.

    2016-01-01

    This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

  4. A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

    Directory of Open Access Journals (Sweden)

    Dong Jiang

    Full Text Available Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1 images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization with convenience.

  5. A Simple Semi-Automatic Approach for Land Cover Classification from Multispectral Remote Sensing Imagery

    Science.gov (United States)

    Jiang, Dong; Huang, Yaohuan; Zhuang, Dafang; Zhu, Yunqiang; Xu, Xinliang; Ren, Hongyan

    2012-01-01

    Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience. PMID:23049886

  6. Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

    Science.gov (United States)

    Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

    2010-07-02

    This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude.

  7. Quality assessment of butter cookies applying multispectral imaging

    DEFF Research Database (Denmark)

    Stenby Andresen, Mette; Dissing, Bjørn Skovlund; Løje, Hanne

    2013-01-01

    A method for characterization of butter cookie quality by assessing the surface browning and water content using multispectral images is presented. Based on evaluations of the browning of butter cookies, cookies were manually divided into groups. From this categorization, reference values were...... in a forced convection electrically heated oven. In addition to the browning score, a model for predicting the average water content based on the same images is presented. This shows how multispectral images of butter cookies may be used for the assessment of different quality parameters. Statistical analysis...

  8. Groundwater Modelling For Recharge Estimation Using Satellite Based Evapotranspiration

    Science.gov (United States)

    Soheili, Mahmoud; (Tom) Rientjes, T. H. M.; (Christiaan) van der Tol, C.

    2017-04-01

    Groundwater movement is influenced by several factors and processes in the hydrological cycle, from which, recharge is of high relevance. Since the amount of aquifer extractable water directly relates to the recharge amount, estimation of recharge is a perquisite of groundwater resources management. Recharge is highly affected by water loss mechanisms the major of which is actual evapotranspiration (ETa). It is, therefore, essential to have detailed assessment of ETa impact on groundwater recharge. The objective of this study was to evaluate how recharge was affected when satellite-based evapotranspiration was used instead of in-situ based ETa in the Salland area, the Netherlands. The Methodology for Interactive Planning for Water Management (MIPWA) model setup which includes a groundwater model for the northern part of the Netherlands was used for recharge estimation. The Surface Energy Balance Algorithm for Land (SEBAL) based actual evapotranspiration maps from Waterschap Groot Salland were also used. Comparison of SEBAL based ETa estimates with in-situ abased estimates in the Netherlands showed that these SEBAL estimates were not reliable. As such results could not serve for calibrating root zone parameters in the CAPSIM model. The annual cumulative ETa map produced by the model showed that the maximum amount of evapotranspiration occurs in mixed forest areas in the northeast and a portion of central parts. Estimates ranged from 579 mm to a minimum of 0 mm in the highest elevated areas with woody vegetation in the southeast of the region. Variations in mean seasonal hydraulic head and groundwater level for each layer showed that the hydraulic gradient follows elevation in the Salland area from southeast (maximum) to northwest (minimum) of the region which depicts the groundwater flow direction. The mean seasonal water balance in CAPSIM part was evaluated to represent recharge estimation in the first layer. The highest recharge estimated flux was for autumn

  9. Multispectral histogram normalization contrast enhancement

    Science.gov (United States)

    Soha, J. M.; Schwartz, A. A.

    1979-01-01

    A multispectral histogram normalization or decorrelation enhancement which achieves effective color composites by removing interband correlation is described. The enhancement procedure employs either linear or nonlinear transformations to equalize principal component variances. An additional rotation to any set of orthogonal coordinates is thus possible, while full histogram utilization is maintained by avoiding the reintroduction of correlation. For the three-dimensional case, the enhancement procedure may be implemented with a lookup table. An application of the enhancement to Landsat multispectral scanning imagery is presented.

  10. Multi-spectral camera development

    CSIR Research Space (South Africa)

    Holloway, M

    2012-10-01

    Full Text Available stream_source_info Holloway_2012.pdf.txt stream_content_type text/plain stream_size 6209 Content-Encoding ISO-8859-1 stream_name Holloway_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Multi-Spectral Camera... Development 4th Biennial Conference Presented by Mark Holloway 10 October 2012 Fused image ? Red, Green and Blue Applications of the Multi-Spectral Camera ? CSIR 2012 Slide 2 Green and Blue, Near Infrared (IR) RED Applications of the Multi...

  11. Maximizing the Economic Benefits of a Multi-Spectral Mission

    Science.gov (United States)

    Kamoun, P.; Martimort, Ph.

    Several multi-spectral Space missions have been proposed worldwide to meet the requirements of various applications with hopes of substantial return on investment. However experience has shown that up till today, with very few exceptions, most have not reached expectations and several multi-spectral projects are even staying only at the prospective stage. In this paper the results of a thorough analysis of the requirements of several key thematic domains will be presented ( in particular vegetation monitoring, geology, oceanography, urbanism, ... ). This analysis will be followed by the identification of optimum system specifications to establish a commercially viable system. A description of the technical characteristcs of the optimum system in terms of mission, satellite, platform, instrument and ground segment will then be given. Finally a treatment of the business case will be shown and its economic benefits will be qualitatively and quantitatively indicated. The relationship between such a program and its counterparts worldwide will be explored to identify redundancies or synergies.

  12. 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

  13. Introducing multisensor satellite radiance-based evaluation for regional Earth System modeling

    Science.gov (United States)

    Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.; Aires, F.

    2014-07-01

    Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

  14. Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

    Science.gov (United States)

    Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.; hide

    2014-01-01

    Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

  15. PROJECTION BASED STALTISTICAL FEATURE EXTRACTION WITH MULTISPECTRAL IMAGES AND ITS APPLICATIONS ON THE YELLOW RIVER MAINSTREAM LINE DETECTION

    Institute of Scientific and Technical Information of China (English)

    Zhang Yanning; Zhang Haichao; Duan Feng; Liu Xuegong; Han Lin

    2009-01-01

    Mainstream line is significant for the Yellow River situation forecasting and flood control. An effective statistical feature extraction method is proposed in this paper.In this method,a be tween-class scattering matrix based projection algorithm is performed to maximize between-class dif ferences,obtaining effective component for classification;then high-order statistics are utilized as the features to describe the mainstream line in the principal component obtained.Experiments are per formed to verify the applicability of the algorithm.The results both on synthesized and real scenes indicate that this approach could extract the mainstream line of the Yellow River automatically,and has a high precision in mainstream line detection.

  16. Satellite link augmentation of ground based packet switched data networks

    Science.gov (United States)

    Farrell, J. B.; McLane, P. J.; Campbell, L. L.

    Use of satellite link augmentation to improve the performance of a packet switched data network is considered. Particular attention is paid to the analysis of two queues in series from the standpoint of time delay. A finite state machine model is used to aid the analysis. The results from the analysis are then used in a flow deviation routing algorithm. This algorithm is applied to study the performance improvement when satellite links are used to augment the Canadian DATAPAC network. The results are backed up by extensive simulations on a digital computer.

  17. Potential of the multispectral synergism for observing ozone pollution combining measurements of IASI-NG and UVNS onboard EPS-SG

    Science.gov (United States)

    Costantino, Lorenzo; Cuesta, Juan; Emili, Emanuele; Foret, Gilles; Dufour, Gaëlle; Eremenko, Maxim; Chailleux, Yohann; Beekmann, Matthias; Flaud, Jean-Marie

    2016-04-01

    Current and future satellite observations offer a great potential for monitoring air quality on daily and global basis. However, measurements from currently in orbit sensors offer a limited capacity to probe surface concentrations of gaseous pollutants such as tropospheric ozone. Using single-band approaches based on IASI spaceborne thermal infrared measurements, only ozone down to the lower troposphere (3-4 km of altitude at lowest) may be observed (Eremenko et al., 2008). A recent multispectral method combining IASI and GOME-2 (both onboard MetOp satellites) spectra, respectively from the IR and UV, has shown enhanced sensitivity for probing ozone at the lowermost troposphere, but with maximum sensitivity around 2 km at lowest (Cuesta et al., 2013). Future spatial missions will be launched in the upcoming years, such as EPS-SG, carrying new generation sensors like IASI-NG and UVNS that will enhance the capacity to observe ozone pollution, and particularly when combining them through a multispectral synergism. This work presents an analysis of the potential of the multispectral synergism of IASI-NG and UVNS future spaceborne measurements for observing ozone pollution, performed in the framework of SURVEYOZON project (funded by the French Space Agency, CNES). For this, we develop a simulator of synthetic multispectral retrievals or pseudo-observations (referred as OSSE, Observing System Simulation Experiment) derived from IASI-NG+UVNS that will be compared to those from IASI+GOME2. In the first step of the OSSE, we create a pseudo-reality with simulations from the chemical-transport model MOCAGE (provided by CERFACS laboratory), where real O3 data from IASI and surface network stations have been assimilated for a realistic representation of ozone variability at the surface and the free troposphere. We focus on the high pollution event occurred in Europe on 10 July 2010. We use the coupled algorithms KOPRA+VLIDORT to simulate the spectra emitted, scattered and

  18. Theoretical design and material growth of Type-II Antimonide-based superlattices for multi-spectral infrared detection and imaging

    Science.gov (United States)

    Hoang, Anh Minh

    Infrared detectors find applications in many aspects of life, from night vision, target tracking for homeland security and defense, non-destructive failure detection in industry, chemical sensing in medicine, and free-space communication. Currently, the dominant technologies of photodetectors based upon HgCdTe and InSb are experiencing many limitations. Under this circumstance, the Type-II InAs/GaSb/AlSb superlattices which have been intensively studied recently appear to be an excellent candidate to give breakthroughs in the infrared technology. The Type-II SLs with theirs advantages such as great flexibility in bandgap engineering, high carrier effective mass, Auger recombination suppression and high uniformity have shown excellent device performance from MWIR to VLWIR. In the era of the third generation for infrared cameras, Type-II SLs are entering the new phase of development with high performance and multi-spectral detection. The goal of this work is to investigate quantum properties of the superlattice system, design appropriate device architectures and experimentally fabricate infrared detectors which can push further the limit of this material system and outperform existing competing technologies. The binary-binary InAs/GaSb superlattice has gone through much transformation over the years. Incorporating compounds lattice matched to the 6.1A family has invited more possibilities to band engineer the Type-II SLs. For the first time, by employing all three members of this material system, we have designed a new superlattice structure and demonstrated shortwavelength infrared (SWIR) photodiodes based on Type-II InAs/GaSb/AlSb with high electrical and optical performance. The photodiodes exhibited a quantum efficiency of 60% with very low dark current, can be operated at room temperature. In addition to the range of MWIR to VLWIR, a new channel of detection has been added to the GaSb based type-II SL material system. The new realization of SWIR photodiodes has

  19. Evaluation of satellite-based precipitation estimates in winter season using an object-based approach

    Science.gov (United States)

    Li, J.; Hsu, K.; AghaKouchak, A.; Sorooshian, S.

    2012-12-01

    Verification has become an integral component of satellite precipitation algorithms and products. A number of object-based verification methods have been proposed to provide diagnostic information regarding the precipitation products' ability to capture the spatial pattern, intensity, and placement of precipitation. However, most object-based methods are not capable of investigating precipitation objects at the storm-scale. In this study, an image processing approach known as watershed segmentation was adopted to detect the storm-scale rainfall objects. Then, a fuzzy logic-based technique was utilized to diagnose and analyze storm-scale object attributes, including centroid distance, area ratio, intersection area ratio and orientation angle difference. Three verification metrics (i.e., false alarm ratio, missing ratio and overall membership score) were generated for validation and verification. Three satellite-based precipitation products, including PERSIANN, CMORPH, 3B42RT, were evaluated against NOAA stage IV MPE multi-sensor composite rain analysis at 0.25° by 0.25° on a daily scale in the winter season of 2010 over the contiguous United States. Winter season is dominated by frontal systems which usually have larger area coverage. All three products and the stage IV observation tend to find large size storm objects. With respect to the evaluation attributes, PERSIANN tends to obtain larger area ratio and consequently has larger centroid distance to the stage IV observations, while 3B42RT are found to be closer to the stage IV for the object size. All evaluation products give small orientation angle differences but vary significantly for the missing ratio and false alarm ratio. This implies that satellite estimates can fail to detect storms in winter. The overall membership scores are close for all three different products which indicate that all three satellite-based precipitation products perform well for capturing the spatial and geometric characteristics of

  20. Performance tests of a satellite-based asymmetric communication network for the 'hyper hospital'.

    Science.gov (United States)

    Yamaguchi, T

    1997-01-01

    The Hyper Hospital is a prototype networked telemedicine system which uses virtual reality. We measured the performance of a novel multimedia network based on satellite communications. The network was a hybrid system consisting of a satellite channel in one direction and a terrestrial channel in the other. Each user was equipped with a standard satellite communication receiver and a telephone connection. Requests from the users were sent by modern and telephone line and responses were received by satellite. The user requests were initiated by clicking buttons on a World Wide Web browser screen. The transmission rates of satellite and normal telephone-line communications were compared for standardized text data. Satellite communication was three to five times faster. The transmission rate was also measured for standardized graphical data (GIF format). With a file size of about 400 kByte, satellite-mediated communication was 10 times faster than telephone lines. The effect of simultaneous access on performance was also explored. For simultaneous access of nine users to a single graphics file, 78% of the transmission speed was obtained in comparison with that of a single user. The satellite-based system showed excellent high-speed communication performance, particularly for multimedia data.

  1. GPS/Magnetometer Based Satellite Navigation and Attitude Determination

    Science.gov (United States)

    Deutschmann, Julie; Bar-Itzhack, Itzhack; Harman, Rick; Bauer, Frank H. (Technical Monitor)

    2001-01-01

    In recent years algorithms were developed for orbit, attitude and angular-rate determination of Low Earth Orbiting (LEO) satellites. Those algorithms rely on measurements of magnetometers, which are standard, relatively inexpensive, sensors that are normally installed on every LEO satellite. Although magnetometers alone are sufficient for obtaining the desired information, the convergence of the algorithms to the correct values of the satellite orbital parameters, position, attitude and angular velocity is very slow. The addition of sun sensors reduces the convergence time considerably. However, for many LEO satellites the sun data is not available during portions of the orbit when the spacecraft (SC) is in the earth shadow. It is here where the GPS space vehicles (SV) can provide valuable support. This is clearly demonstrated in the present paper. Although GPS measurements alone can be used to obtain SC position, velocity, attitude and angular-rate, the use of magnetometers improve the results due to the synergistic effect of sensor fusion. Moreover, it is possible to obtain these results with less than three SVs. In this paper we introduce an estimation algorithm, which is a combination of an Extended Kalman Filter (EKF) and a Pseudo Linear Kalman Filter (PSELIKA).

  2. A Constraint Based Approach for Building Operationally Responsive Satellites

    Science.gov (United States)

    2008-09-01

    discipline specific software codes into a common environment. LLB team also uses MATLAB R© to integrate CAD tools such as Catia , Pro/Engineer with FE...satellite configuration through a Catia CAD tool. The LLB approach is similar to the approach discussed in this research because it provides a method

  3. Stereoscopic observations from meteorological satellites

    Science.gov (United States)

    Hasler, A. F.; Mack, R.; Negri, A.

    two satellites. A general solution for accurate height computation depends on precise navigation of the two satellites. Validation of the geosynchronous satellite stereo using high altitude mountain lakes and vertically pointing aircraft lidar leads to a height accuracy estimate of +/- 500 m for typical clouds which have been studied. Applications of the satellite stereo include: 1) cloud top and base height measurements, 2) cloud-wind height assignment, 3) vertical motion estimates for convective clouds (Mack et al. [13], [14]), 4) temperature vs. height measurements when stereo is used together with infrared observations and 5) cloud emissivity measurements when stereo, infrared and temperature sounding are used together (see Szejwach et al. [15]). When true satellite stereo image pairs are not available, synthetic stereo may be generated. The combination of multispectral satellite data using computer produced stereo image pairs is a dramatic example of synthetic stereoscopic display. The classic case uses the combination of infrared and visible data as first demonstrated by Pichel et al. [16]. Hasler et at. [17], Mosher and Young [18] and Lorenz [19], have expanded this concept to display many channels of data from various radiometers as well as real and simulated data fields. A future system of stereoscopic satellites would be comprised of both low orbiters (as suggested by Lorenz and Schmidt [20], [19]) and a global system of geosynchronous satellites. The low earth orbiters would provide stereo coverage day and night and include the poles. An optimum global system of stereoscopic geosynchronous satellites would require international standarization of scan rate and direction, and scan times (synchronization) and resolution of at least 1 km in all imaging channels. A stereoscopic satellite system as suggested here would make an extremely important contribution to the understanding and prediction of the atmosphere.

  4. Compact multi-spectral imaging system for dermatology and neurosurgery

    Science.gov (United States)

    Noordmans, Herke Jan; de Roode, Rowland; Verdaasdonk, Rudolf

    2007-03-01

    A compact multi-spectral imaging system is presented as diagnostic tool in dermatology and neurosurgery. Using an electronically tunable filter, a sensitive high resolution digital camera, 140 spectral images from 400 nm up to 720 nm are acquired in 40 s. Advanced image processing algorithms are used to enable interactive acquisition, viewing, image registration and image analysis. Experiments in the department of dermatology and neurosurgery show that multispectral imaging reveals much more detail than conventional medical photography or a surgical microscope, as images can be reprocessed to enhance the view on e.g. tumor boundaries. Using a hardware-based interactive registration algorithm, multi-spectral images can be aligned to correct for motion occurred during image acquisition or to compare acquisitions from different moments in time. The system shows to be a powerful diagnostics tool for medical imaging in the visual and near IR range.

  5. Satellite-based remote sensing of running water habitats at large riverscape scales: Tools to analyze habitat heterogeneity for river ecosystem management

    Science.gov (United States)

    Hugue, F.; Lapointe, M.; Eaton, B. C.; Lepoutre, A.

    2016-01-01

    We illustrate an approach to quantify patterns in hydraulic habitat composition and local heterogeneity applicable at low cost over very large river extents, with selectable reach window scales. Ongoing developments in remote sensing and geographical information science massively improve efficiencies in analyzing earth surface features. With the development of new satellite sensors and drone platforms and with the lowered cost of high resolution multispectral imagery, fluvial geomorphology is experiencing a revolution in mapping streams at high resolution. Exploiting the power of aerial or satellite imagery is particularly useful in a riverscape research framework (Fausch et al., 2002), where high resolution sampling of fluvial features and very large coverage extents are needed. This study presents a satellite remote sensing method that requires very limited field calibration data to estimate over various scales ranging from 1 m to many tens or river kilometers (i) spatial composition metrics for key hydraulic mesohabitat types and (ii) reach-scale wetted habitat heterogeneity indices such as the hydromorphological index of diversity (HMID). When the purpose is hydraulic habitat characterization applied over long river networks, the proposed method (although less accurate) is much less computationally expensive and less data demanding than two dimensional computational fluid dynamics (CFD). Here, we illustrate the tools based on a Worldview 2 satellite image of the Kiamika River, near Mont Laurier, Quebec, Canada, specifically over a 17-km river reach below the Kiamika dam. In the first step, a high resolution water depth (D) map is produced from a spectral band ratio (calculated from the multispectral image), calibrated with limited field measurements. Next, based only on known river discharge and estimated cross section depths at time of image capture, empirical-based pseudo-2D hydraulic rules are used to rapidly generate a two-dimensional map of flow velocity

  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. Multispectral Landsat images of Antartica

    Energy Technology Data Exchange (ETDEWEB)

    Lucchitta, B.K.; Bowell, J.A.; Edwards, K.L.; Eliason, E.M.; Fergurson, H.M.

    1988-01-01

    The U.S. Geological Survey has a program to map Antarctica by using colored, digitally enhanced Landsat multispectral scanner images to increase existing map coverage and to improve upon previously published Landsat maps. This report is a compilation of images and image mosaic that covers four complete and two partial 1:250,000-scale quadrangles of the McMurdo Sound region.

  8. Limiting Factors for Satellite-Based Retrievals of Surface-Level Carbon Monoxide

    Science.gov (United States)

    Martinez-Alonso, S.; Deeter, M. N.; Worden, H. M.; Barré, J.

    2015-12-01

    CO is mostly produced in the lower troposphere by incomplete combustion of biomass and fuels. CO oxidation consumes ~75% of the tropospheric OH, which then is not available to remove CH4 and other greenhouse gases. CO oxidation also leads to the production of tropospheric O3. These critical impacts of CO on air quality and climate require accurate determination of the abundance and evolution of CO near the surface.Satellite retrievals would be well-suited to monitor surface CO globally. However, how do they compare to actual surface abundances? Some aspects to be considered include: the vertical sensitivity of retrievals (given by the averaging kernels), or how thick are the atmospheric layers that can be resolved; the vertical correlation length of CO with respect to the thickness of those layers; and the horizontal variability of CO with respect to the instrument's footprint.To investigate these questions we analyze MOPITT retrievals, DISCOVER-AQ and NOAA profiles, as well as WDCGG surface measurements. MOPITT, on board NASA's Terra satellite, has been measuring tropospheric CO since 2000, providing the longest global CO record to date. Its unique multispectral CO product offers enhanced sensitivity to CO near the surface. Vertical profiles of the lower troposphere were acquired during the DISCOVER-AQ airborne campaigns over selected regions of the USA. NOAA's airborne flask sampling program results in a multi-year, multi-seasonal record of vertical profiles from near the surface up to the mid troposphere, acquired over a number of stations, mostly in North America. Long-term, cross-calibrated surface CO data from ground stations worldwide are available through the WDCGG.Statistical analyses of the DISCOVER-AQ and NOAA profiles indicate that surface vertical correlation length varies greatly depending on geographic location. This may explain contrasting results obtained for different ground stations when comparing MOPITT and WDCGG co-located data and timeseries.

  9. Spline model of the high latitude scintillation based on in situ satellite data

    Science.gov (United States)

    Priyadarshi, S.; Wernik, A. W.

    2013-12-01

    We present a spline model for the high latitude ionospheric scintillation using satellite in situ measurements made by the Dynamic Explorer 2 (DE 2) satellite. DE 2 satellite measurements give observations only along satellite orbit but our interpolation model fills the gaps between the satellite orbits. This analytical model is based on products of cubic B-splines and coefficients determined by least squares fit to the binned data and constrained to make the fit periodic in 24 hours of geomagnetic local time, periodic in 360 degrees of invariant longitude, in geomagnetic indices and solar radio flux. Discussion of our results clearly shows the seasonal and diurnal behavior of ionospheric parameters important in scintillation modeling for different geophysical and solar activity conditions. We also show that results obtained from our analytical model match observations obtained from in situ measurements. Shishir Priyadarshi Space Research Centre, Poland

  10. 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...

  11. A Satellite Based Method for Wetland Inundation Mapping

    Science.gov (United States)

    Di Vittorio, C.; Georgakakos, A. P.

    2016-12-01

    Hydrologic models of wetlands enable hydrologists and water resources managers to appreciate the environmental and societal roles of wetlands and manage them in ways that preserve their integrity and sustain their valuable services. However, wetland model reliability and accuracy are often unsatisfactory due to the complexity of the underlying processes and the lack of adequate in-situ data. In this research, we demonstrate how MODIS satellite imagery can be used to characterize wetland flooding over time and to support the development of more reliable wetland models. We apply this method to the Sudd, a seasonal wetland in South Sudan that is part of the Nile River Basin. The database consists of 16 years of 8-day composite ground surface reflectance data with a 500 m spatial resolution downloaded from Earth Explorer. After masking poor quality pixels, monthly mean NDWI and NDVI values were extracted. Based on literature and personal accounts describing the Sudd as well as Google Earth imagery, a set of ground truth locations were identified for each land class and monthly distributions of the indices were derived. The indices were then combined in a unique way and statistics of the new distributions were used to classify land types present in the full area of interest. Subsequently, annual statistics were derived from the same indices and used to identify pixels that undergo flooding as well as the timing and duration of flooding for each year (2000-2015). An independent set of ground truth locations were selected for method validation. The combined indices demonstrate high land classification accuracy and outperform the individual indices as well as other existing land classification algorithms. The derived monthly inundation series agrees well with literature and anecdotal observations. This information is currently being used to develop wetland models as part of a comprehensive modeling system for the Nile River Basin. The new method is general and can be used

  12. Geographic object-based delineation of neighborhoods of Accra, Ghana using QuickBird satellite imagery.

    Science.gov (United States)

    Stow, Douglas A; Lippitt, Christopher D; Weeks, John R

    2010-08-01

    The objective was to test GEographic Object-based Image Analysis (GEOBIA) techniques for delineating neighborhoods of Accra, Ghana using QuickBird multispectral imagery. Two approaches to aggregating census enumeration areas (EAs) based on image-derived measures of vegetation objects were tested: (1) merging adjacent EAs according to vegetation measures and (2) image segmentation. Both approaches exploit readily available functions within commercial GEOBIA software. Image-derived neighborhood maps were compared to a reference map derived by spatial clustering of slum index values (from census data), to provide a relative assessment of potential map utility. A size-constrained iterative segmentation approach to aggregation was more successful than standard image segmentation or feature merge techniques. The segmentation approaches account for size and shape characteristics, enabling more realistic neighborhood boundaries to be delineated. The percentage of vegetation patches within each EA yielded more realistic delineation of potential neighborhoods than mean vegetation patch size per EA.

  13. 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

  14. LANDSAT 8 MULTISPECTRAL AND PANSHARPENED IMAGERY PROCESSING ON THE STUDY OF CIVIL ENGINEERING ISSUES

    Directory of Open Access Journals (Sweden)

    M. A. Lazaridou

    2016-06-01

    Full Text Available Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM – Landsat 8 is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion – pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  15. Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

    Science.gov (United States)

    Lazaridou, M. A.; Karagianni, A. Ch.

    2016-06-01

    Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  16. Simultaneous ground- and satellite-based observation of MF/HF auroral radio emissions

    Science.gov (United States)

    Sato, Yuka; Kumamoto, Atsushi; Katoh, Yuto; Shinbori, Atsuki; Kadokura, Akira; Ogawa, Yasunobu

    2016-05-01

    We report on the first simultaneous measurements of medium-high frequency (MF/HF) auroral radio emissions (above 1 MHz) by ground- and satellite-based instruments. Observational data were obtained by the ground-based passive receivers in Iceland and Svalbard, and by the Plasma Waves and Sounder experiment (PWS) mounted on the Akebono satellite. We observed two simultaneous appearance events, during which the frequencies of the auroral roar and MF bursts detected at ground level were different from those of the terrestrial hectometric radiation (THR) observed by the Akebono satellite passing over the ground-based stations. This frequency difference confirms that auroral roar and THR are generated at different altitudes across the F peak. We did not observe any simultaneous observations that indicated an identical generation region of auroral roar and THR. In most cases, MF/HF auroral radio emissions were observed only by the ground-based detector, or by the satellite-based detector, even when the satellite was passing directly over the ground-based stations. A higher detection rate was observed from space than from ground level. This can primarily be explained in terms of the idea that the Akebono satellite can detect THR emissions coming from a wider region, and because a considerable portion of auroral radio emissions generated in the bottomside F region are masked by ionospheric absorption and screening in the D/E regions associated with ionization which results from auroral electrons and solar UV radiation.

  17. Research on Coal Exploration Technology Based on Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Dong Xiao

    2016-01-01

    Full Text Available Coal is the main source of energy. In China and Vietnam, coal resources are very rich, but the exploration level is relatively low. This is mainly caused by the complicated geological structure, the low efficiency, the related damage, and other bad situations. To this end, we need to make use of some advanced technologies to guarantee the resource exploration is implemented smoothly and orderly. Numerous studies show that remote sensing technology is an effective way in coal exploration and measurement. In this paper, we try to measure the distribution and reserves of open-air coal area through satellite imagery. The satellite picture of open-air coal mining region in Quang Ninh Province of Vietnam was collected as the experimental data. Firstly, the ENVI software is used to eliminate satellite imagery spectral interference. Then, the image classification model is established by the improved ELM algorithm. Finally, the effectiveness of the improved ELM algorithm is verified by using MATLAB simulations. The results show that the accuracies of the testing set reach 96.5%. And it reaches 83% of the image discernment precision compared with the same image from Google.

  18. A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm.

    Science.gov (United States)

    Song, Jiancai; Xue, Guixiang; Kang, Yanan

    2016-01-01

    In this paper, a novel method for selecting a navigation satellite subset for a global positioning system (GPS) based on a genetic algorithm is presented. This approach is based on minimizing the factors in the geometric dilution of precision (GDOP) using a modified genetic algorithm (MGA) with an elite conservation strategy, adaptive selection, adaptive mutation, and a hybrid genetic algorithm that can select a subset of the satellites represented by specific numbers in the interval (4 ∼ n) while maintaining position accuracy. A comprehensive simulation demonstrates that the MGA-based satellite selection method effectively selects the correct number of optimal satellite subsets using receiver autonomous integrity monitoring (RAIM) or fault detection and exclusion (FDE). This method is more adaptable and flexible for GPS receivers, particularly for those used in handset equipment and mobile phones.

  19. A Novel Onboard-gateway-based Mechanism to Improve TCP Performance in Aeronautical Satellite Networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The IP-based networks on aircraft serve to support Internet services via satellites. However, in aeronautical satellite hybrid networks, the TCP protocol performance often deteriorates due to improper decreases and slow recovery of the congestion window. This paper proposes a window size determination and notification mechanism, onboard-gateway-based mechanism (OGBM), which is based on the onboard gateway in the networks on aircraft. A cross-layer approach is adopted by the onboard gateway to obtain the satellite link bandwidth information. And then, by the gateway, through changing the receiver's advertised window field in ACK packets, TCP sources are notified of the window size of each TCP source calculated on the ground of bandwidth delay product and flow numbers. The mechanism is able to avoid improper changes of TCP window and serve multiple users. Simulation results show that the mechanism with the fairness index close to 1 improves TCP performance in aeronautical satellite networks.

  20. Lossless compression of multispectral images using spectral information

    Science.gov (United States)

    Ma, Long; Shi, Zelin; Tang, Xusheng

    2009-10-01

    Multispectral images are available for different purposes due to developments in spectral imaging systems. The sizes of multispectral images are enormous. Thus transmission and storage of these volumes of data require huge time and memory resources. That is why compression algorithms must be developed. A salient property of multispectral images is that strong spectral correlation exists throughout almost all bands. This fact is successfully used to predict each band based on the previous bands. We propose to use spectral linear prediction and entropy coding with context modeling for encoding multispectral images. Linear prediction predicts the value for the next sample and computes the difference between predicted value and the original value. This difference is usually small, so it can be encoded with less its than the original value. The technique implies prediction of each image band by involving number of bands along the image spectra. Each pixel is predicted using information provided by pixels in the previous bands in the same spatial position. As done in the JPEG-LS, the proposed coder also represents the mapped residuals by using an adaptive Golomb-Rice code with context modeling. This residual coding is context adaptive, where the context used for the current sample is identified by a context quantization function of the three gradients. Then, context-dependent Golomb-Rice code and bias parameters are estimated sample by sample. The proposed scheme was compared with three algorithms applied to the lossless compression of multispectral images, namely JPEG-LS, Rice coding, and JPEG2000. Simulation tests performed on AVIRIS images have demonstrated that the proposed compression scheme is suitable for multispectral images.

  1. Radiometric Cross-Calibration of GF-4 in Multispectral Bands

    Directory of Open Access Journals (Sweden)

    Aixia Yang

    2017-03-01

    Full Text Available The GaoFen-4 (GF-4, launched at the end of December 2015, is China’s first high-resolution geostationary optical satellite. A panchromatic and multispectral sensor (PMS is onboard the GF-4 satellite. Unfortunately, the GF-4 has no onboard calibration assembly, so on-orbit radiometric calibration is required. Like the charge-coupled device (CCD onboard HuanJing-1 (HJ or the wide field of view sensor (WFV onboard GaoFen-1 (GF-1, GF-4 also has a wide field of view, which provides challenges for cross-calibration with narrow field of view sensors, like the Landsat series. A new technique has been developed and used to calibrate HJ-1/CCD and GF-1/WFV, which is verified viable. The technique has three key steps: (1 calculate the surface using the bi-directional reflectance distribution function (BRDF characterization of a site, taking advantage of its uniform surface material and natural topographic variation using Landsat Enhanced Thematic Mapper Plus (ETM+/Operational Land Imager (OLI imagery and digital elevation model (DEM products; (2 calculate the radiance at the top-of-the atmosphere (TOA with the simulated surface reflectance using the atmosphere radiant transfer model; and (3 fit the calibration coefficients with the TOA radiance and corresponding Digital Number (DN values of the image. This study attempts to demonstrate the technique is also feasible to calibrate GF-4 multispectral bands. After fitting the calibration coefficients using the technique, extensive validation is conducted by cross-validation using the image pairs of GF-4/PMS and Landsat-8/OLI with similar transit times and close view zenith. The validation result indicates a higher accuracy and frequency than that given by the China Centre for Resources Satellite Data and Application (CRESDA using vicarious calibration. The study shows that the new technique is also quite feasible for GF-4 multispectral bands as a routine long-term procedure.

  2. Detection of sudden death syndrome using a multispectral imaging sensor

    Science.gov (United States)

    Sudden death syndrome (SDS), caused by the fungus Fusarium solani f. sp. glycines, is a widespread mid- to late-season disease with distinctive foliar symptoms. This paper reported the development of an image analysis based method to detect SDS using a multispectral image sensor. A hue, saturation a...

  3. A comparing design of satellite attitude control system based on reaction wheel

    Institute of Scientific and Technical Information of China (English)

    CHENG Hao; GE Sheng-min; SHEN Yi

    2008-01-01

    The disturbance caused by the reaction wheel with a current controller greatly influences the accuracy and stability of the satellite attitude control system.To solve this problem,the idea of speed feedback compensation control reaction wheel is put forward.This paper introduces the comparison on design and performance of two satellite attitude control systems,which are separately based on the current control reaction wheel and the speed feedback compensation control reaction wheel.Analysis shows that the speed feedback compensation control flywheel system may effectively suppress the torque fluctuation.Simulation results indicate that the satellite attitude control system with the speed feedback compensation control flywheel has improved performance.

  4. A DISTRIBUTED QOS ROUTING BASED ON ANT ALGORITHM FOR LEO SATELLITE NETWORK

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Low Earth Orbit (LEO) satellites provide short round-trip delays and are becoming increasingly important. One of the challenges in LEO satellite networks is the development of specialized and efficient routing algorithms. To satisfy the QoS requirements of multimedia applications, satellite routing protocols should consider handovers and minimize their effect on the active connections. A distributed QoS routing scheme based on heuristic ant algorithm is proposed for satisfying delay bound and avoiding link congestion. Simulation results show that the call blocking probabilities of this algorithm are less than that of Shortest Path First (SPF) with different delay bound.

  5. Extraction and classification of objects in multispectral images

    Science.gov (United States)

    Robertson, T. V.

    1973-01-01

    Presented here is an algorithm that partitions a digitized multispectral image into parts that correspond to objects in the scene being sensed. The algorithm partitions an image into successively smaller rectangles and produces a partition that tends to minimize a criterion function. Supervised and unsupervised classification techniques can be applied to partitioned images. This partition-then-classify approach is used to process images sensed from aircraft and the ERTS-1 satellite, and the method is shown to give relatively accurate results in classifying agricultural areas and extracting urban areas.

  6. 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.

  7. Assessment of multispectral glacier mapping methods and derivation of glacier area changes, 1978–2002, in the central Southern Alps, New Zealand, from ASTER satellite data, field survey and existing inventory data

    CSIR Research Space (South Africa)

    Gjermundsen, EF

    2011-09-01

    Full Text Available can be made by the use of satellite remote sensing, capable of acquiring comprehensive, uniform and frequent global observations of glaciers and ice sheets. In New Zealand the first and only glacier inventory including the two main islands...? glaciers was made from aerial photographs recorded in 1978 (Chinn, unpublished). The mapping showed that the Southern Alps hosted 3144 glaciers exceeding 0.01 km2, totalling an area of 1158 km2 and an estimated ice volume of 53.3 km3 (Chinn, 2001...

  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...... based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method....

  9. A Novel Sampling Method for Satellite-Based Offshore Wind Resource Estimation

    DEFF Research Database (Denmark)

    Badger, Merete; Badger, Jake; Hasager, Charlotte Bay

    Synthetic aperture radar (SAR) measurements from satellites can be used to estimate the spatial wind speed variation offshore in great detail. The radar senses cm-scale roughness at the sea surface which can be translated to wind speed at the height 10 m using an empirical geophysical model......-based wind climatology have improved gradually as more data were collected. The satellite scenes have been treated as random samples and weighted equally in our previous analyses. Here we introduce a novel sampling strategy based on the wind class methodology that is normally applied in numerical modeling...... 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...

  10. Design and simulation of satellite attitude control system based on Simulink and VR

    Science.gov (United States)

    Zhang, Yang; Gan, Qingbo; Kang, Jingshu

    2016-01-01

    In order to research satellite attitude control system design and visual simulation, the simulation framework of satellite dynamics and attitude control using Simulink were established. The design of satellite earth-oriented control system based on quaternion feedback was completed. The 3D scene based on VR was created and models in the scene were driven by simulation data of Simulink. By coordinate transformation. successful observing the scene in inertial coordinate system, orbit coordinate system and body coordinate system. The result shows that application of simulation method of Simulink combined with VR in the design of satellite attitude control system field, has the advantages of high confidence level, hard real-time property, multi-perspective and multi-coordinate system observing the scene, and improves the comprehensibility and accuracy of the design.

  11. UKF-based attitude determination method for gyroless satellite

    Institute of Scientific and Technical Information of China (English)

    张红梅; 邓正隆

    2004-01-01

    UKF (unscented Kalman filtering) is a new filtering method suitable to nonlinear systems. The method need not linearize nonlinear systems at the prediction stage of filtering, which is indispensable in EKF (extended Kalman filtering). As a result, the linearization error is avoided, and the filtering accuracy is greatly improved. UKF is applied to the attitude determination for gyroless satellite. Simulations are made to compare the new filter with the traditional EKF.The results indicate that under same conditions, compared with EKF, UKF has faster convergence speed, higher filtering accuracy and more stable estimation performance.

  12. Satellite -Based Networks for U-Health & U-Learning

    Science.gov (United States)

    Graschew, G.; Roelofs, T. A.; Rakowsky, S.; Schlag, P. M.

    2008-08-01

    The use of modern Information and Communication Technologies (ICT) as enabling tools for healthcare services (eHealth) introduces new ways of creating ubiquitous access to high-level medical care for all, anytime and anywhere (uHealth). Satellite communication constitutes one of the most flexible methods of broadband communication offering high reliability and cost-effectiveness of connections meeting telemedicine communication requirements. Global networks and the use of computers for educational purposes stimulate and support the development of virtual universities for e-learning. Especially real-time interactive applications can play an important role in tailored and personalised services.

  13. Space-Based Observations of Satellites From the MOST Microsatellite

    Science.gov (United States)

    2006-11-01

    observations spatiales canadiennes d’un objet en orbite terrestre . Deux satellites de géolocalisation GPS ont été suivis à l’aide du télescope optique monté...the derived orbital metric data with high precision ephemerides yielded root mean square errors of 13 arcseconds. The errors are shown to result...space surveillance from an orbiting platform. Résumé Le 12 octobre 2005, le microsatellite MOST du Canada a acquis les premières images

  14. MRO/CRISM Retrieval of Surface Lambert Albedos for Multispectral Mapping of Mars with DISORT-based Rad. Transfer Modeling: Phase 1 - Using Historical Climatology for Temperatures, Aerosol Opacities, & Atmo. Pressures

    CERN Document Server

    McGuire, P C; Smith, M D; Arvidson, R E; Murchie, S L; Clancy, R T; Roush, T L; Cull, S C; Lichtenberg, K A; Wiseman, S M; Green, R O; Martin, T Z; Milliken, R E; Cavender, P J; Humm, D C; Seelos, F P; Seelos, K D; Taylor, H W; Ehlmann, B L; Mustard, J F; Pelkey, S M; Titus, T N; Hash, C D; Malaret, E R

    2009-01-01

    We discuss the DISORT-based radiative transfer pipeline ('CRISM_LambertAlb') for atmospheric and thermal correction of MRO/CRISM data acquired in multispectral mapping mode (~200 m/pixel, 72 spectral channels). Currently, in this phase-one version of the system, we use aerosol optical depths, surface temperatures, and lower-atmospheric temperatures, all from climatology derived from Mars Global Surveyor Thermal Emission Spectrometer (MGS-TES) data, and surface altimetry derived from MGS Mars Orbiter Laser Altimeter (MOLA). The DISORT-based model takes as input the dust and ice aerosol optical depths (scaled to the CRISM wavelength range), the surface pressures (computed from MOLA altimetry, MGS-TES lower-atmospheric thermometry, and Viking-based pressure climatology), the surface temperatures, the reconstructed instrumental photometric angles, and the measured I/F spectrum, and then outputs a Lambertian albedo spectrum. The Lambertian albedo spectrum is valuable geologically since it allows the mineralogical ...

  15. Cloud-type discrimination via multispectral textural analysis

    Science.gov (United States)

    Lamei, Niloufar; Hutchison, Keith D.; Crawford, Melba M.; Khazenie, Nahid

    1994-04-01

    In recent years, with the development of satellite and computer technology, Earth observation and atmospheric research have become highly dependent on digital imagery. One of the primary interests in digital image processing is the development of robust methods to perform feature detection, extraction, and classification. Until recently, classification methods for cloud discrimination were mainly based on the spectral information of the imagery. However, because of the spectral similarities of certain features (such as ice clouds and snow) and the effects of atmospheric attenuation, multispectral rule-based classifications do not necessarily produce accurate feature discrimination. Spectral homogeneity of two different features within a scene can lead to misclassification. Furthermore, the opposite problem can occur when one feature exhibits different spectral signatures locally but is homogeneous in its cyclic spatial variation. The exploration of spatial information is often advantageous in these discrimination problems. A texture- based method for feature identification has been investigated. This method uses a set of localized spatial filters known as 2-D Gabor functions. Gabor filters can be described as a sinusoidal plane wave within a 2-D Gaussian envelope. The frequency and orientation of the sine plane and the width of the Gaussian envelope are determine by the Gabor parameters. These tunable channels yield joint optimal information both in the spatial and the frequency domains. The new method has been applied to the thermal channels of the NOAA Advanced Very High Resolution Radiometer data for cloud-type discrimination. Results show that additional texture information improves discrimination between cloud types (especially thin cirrus).

  16. Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite%基于多源卫星多光谱遥感数据的过火面积估算研究

    Institute of Scientific and Technical Information of China (English)

    余超; 陈良富; 李莘莘; 陶金花; 苏林

    2015-01-01

    largest source of error in the emission invento-ry.Satellite-based fire observations can offer a reliable source of fire occurrence data on regional and global scales,a variety of sensors have been used to detect and map fires in two general approaches:burn scar mapping and active fire detection.However, both of the two approaches have limitations.In this article,we explore the relationship between hotspot data and burned area for the Southeastern United States,where a significant amount of biomass burnings from both prescribed and wild fire took place. MODIS (Moderate resolution imaging spectrometer)data,which has high temporal-resolution,can be used to monitor ground biomass burning in time and provided hot spot data in this study.However,pixel size of MODIS hot spot can’t stand for the real ground burned area.Through analysis of the variation of vegetation band reflectance between pre-and post-burn,we extracted the burned area from Landsat-5 TM (Thematic Mapper)images by using the differential normalized burn ratio (dNBR)which is based on TM band4 (0.84 μm)and TM band 7 (2.22 μm)data.We combined MODIS fire hot spot data and Landsat-5 TM burned scars data to build the burned area estimation model,results showed that the linear correlation coefficient is 0.63 and the relationships vary as a function of vegetation cover.Based on the National Land Cover Database (NLCD),we built burned area estimation model over different vegetation cover,and got effective burned area per fire pixel,values for forest,grassland, shrub,cropland and wetland are 0.69,1.27,0.86,0.72 and 0.94 km2 respectively.We validated the burned area estimates by using the ground survey data from National Interagency Fire Center (NIFC),our results are more close to the ground survey da-ta than burned area from Global Fire Emissions Database(GFED)and MODIS burned area product (MCD45 ),which omitted many small prescribed fires.We concluded that our model can provide more accurate burned area parameters for

  17. COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSION

    Directory of Open Access Journals (Sweden)

    Preema Mole

    2016-07-01

    Full Text Available The availability of imaging sensors operating in multiple spectral bands has led to the requirement of image fusion algorithms that would combine the image from these sensors in an efficient way to give an image that is more perceptible to human eye. Multispectral Image fusion is the process of combining images optically acquired in more than one spectral band. In this paper, we present a pixel-level image fusion that combines four images from four different spectral bands namely near infrared(0.76-0.90um, mid infrared(1.55-1.75um,thermal- infrared(10.4-12.5um and mid infrared(2.08-2.35um to give a composite colour image. The work coalesces a fusion technique that involves linear transformation based on Cholesky decomposition of the covariance matrix of source data that converts multispectral source images which are in grayscale into colour image. This work is composed of different segments that includes estimation of covariance matrix of images, cholesky decomposition and transformation ones. Finally, the fused colour image is compared with the fused image obtained by PCA transformation.

  18. Multispectral observations of the surf zone

    Science.gov (United States)

    Schoonmaker, Jon S.; Dirbas, Joseph; Gilbert, Gary

    2003-09-01

    Airborne multispectral imagery was collected over various targets on the beach and in the water in an attempt to characterize the surf zone environment with respect to electro-optical system capabilities and to assess the utility of very low cost, small multispectral systems in mine counter measures (MCM) and intelligence, surveillance and reconnaissance applications. The data was collected by PAR Government Systems Corporation (PGSC) at the Army Corps of Engineers Field Research Facility at Duck North Carolina and on the beaches of Camp Pendleton Marine Corps Base in Southern California. PGSC flew the first two of its MANTIS (Mission Adaptable Narrowband Tunable Imaging Sensor) systems. Both MANTIS systems were flown in an IR - red - green - blue (700, 600, 550, 480 nm) configuration from altitudes ranging from 200 to 700 meters. Data collected has been lightly analyzed and a surf zone index (SZI) defined and calculated. This index allows mine hunting system performance measurements in the surf zone to be normalized by environmental conditions. The SZI takes into account water clarity, wave energy, and foam persistence.

  19. Multispectral Enhancement towards Digital Staining

    Directory of Open Access Journals (Sweden)

    Pinky A. Bautista

    2012-01-01

    Full Text Available Background: Digital staining can be considered as a special form of image enhancement wherein the concern is not only to increase the contrast between the background objects and objects of interest, but to also impart the colors that mark the objects’ unique reactions to a specific stain. In this paper, we extended the previously proposed multispectral enhancement methods such that the colors of the background pixels can also be changed.

  20. Satellite image based methods for fuels maps updating

    Science.gov (United States)

    Alonso-Benito, Alfonso; Hernandez-Leal, Pedro A.; Arbelo, Manuel; Gonzalez-Calvo, Alejandro; Moreno-Ruiz, Jose A.; Garcia-Lazaro, Jose R.

    2016-10-01

    Regular updating of fuels maps is important for forest fire management. Nevertheless complex and time consuming field work is usually necessary for this purpose, which prevents a more frequent update. That is why the assessment of the usefulness of satellite data and the development of remote sensing techniques that enable the automatic updating of these maps, is of vital interest. In this work, we have tested the use of the spectral bands of OLI (Operational Land Imager) sensor on board Landsat 8 satellite, for updating the fuels map of El Hierro Island (Spain). From previously digitized map, a set of 200 reference plots for different fuel types was created. A 50% of the plots were randomly used as a training set and the rest were considered for validation. Six supervised and 2 unsupervised classification methods were applied, considering two levels of detail. A first level with only 5 classes (Meadow, Brushwood, Undergrowth canopy cover >50%, Undergrowth canopy cover <15%, and Xeric formations), and the second one containing 19 fuel types. The level 1 classification methods yielded an overall accuracy ranging from 44% for Parellelepided to an 84% for Maximun Likelihood. Meanwhile, level 2 results showed at best, an unacceptable overall accuracy of 34%, which prevents the use of this data for such a detailed characterization. Anyway it has been demonstrated that in some conditions, images of medium spatial resolution, like Landsat 8-OLI, could be a valid tool for an automatic upgrade of fuels maps, minimizing costs and complementing traditional methodologies.

  1. Authentication Scheme Based on Principal Component Analysis for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ashraf. K. Helmy

    2009-09-01

    Full Text Available This paper presents a multi-band wavelet image content authentication scheme for satellite images by incorporating the principal component analysis (PCA. The proposed schemeachieves higher perceptual transparency and stronger robustness. Specifically, the developed watermarking scheme can successfully resist common signal processing such as JPEG compression and geometric distortions such as cropping. In addition, the proposed scheme can be parameterized, thus resulting in more security. That is, an attacker may not be able to extract the embedded watermark if the attacker does not know the parameter.In an order to meet these requirements, the host image is transformed to YIQ to decrease the correlation between different bands, Then Multi-band Wavelet transform (M-WT is applied to each channel separately obtaining one approximate sub band and fifteen detail sub bands. PCA is then applied to the coefficients corresponding to the same spatial location in all detail sub bands. The last principle component band represents an excellent domain forinserting the water mark since it represents lowest correlated features in high frequency area of host image.One of the most important aspects of satellite images is spectral signature, the behavior of different features in different spectral bands, the results of proposed algorithm shows that the spectral stamp for different features doesn't tainted after inserting the watermark.

  2. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    Science.gov (United States)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  3. Validation of PV performance models using satellite-based irradiance measurements : a case study.

    Energy Technology Data Exchange (ETDEWEB)

    Stein, Joshua S.; Parkins, Andrew (Clean Power Research); Perez, Richard (University at Albany)

    2010-05-01

    Photovoltaic (PV) system performance models are relied upon to provide accurate predictions of energy production for proposed and existing PV systems under a wide variety of environmental conditions. Ground based meteorological measurements are only available from a relatively small number of locations. In contrast, satellite-based radiation and weather data (e.g., SUNY database) are becoming increasingly available for most locations in North America, Europe, and Asia on a 10 x 10 km grid or better. This paper presents a study of how PV performance model results are affected when satellite-based weather data is used in place of ground-based measurements.

  4. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2006-01-01

    An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

  5. Multispectral recordings and analysis of psoriasis lesions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2006-01-01

    An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising for furt......An objective method to evaluate the severeness of psoriasis lesions is proposed. In order to obtain objectivity multi-spectral imaging is used. The multi-spectral images give rise to a large p, small n problem which is solved by use of elastic net model selection. The method is promising...

  6. Towards a satellite-based sea ice climate data record

    Science.gov (United States)

    Meier, W. N.; Fetterer, F.; Stroeve, J.; Cavalieri, D.; Parkinson, C.; Comiso, J.; Weaver, R.

    2005-12-01

    Sea ice plays an important role in the Earth's climate through its influence on the surface albedo, heat and moisture transfer between the ocean and the atmosphere, and the thermohaline circulation. Satellite data reveal that since 1979, summer Arctic sea ice has, overall, been declining at a rate of almost 8%/decade, with recent summers (beginning in 2002) being particularly low. The receding sea ice is having an effect on wildlife and indigenous peoples in the Arctic, and concern exists that these effects may become increasingly severe. Thus, a long-term, ongoing climate data record of sea ice is crucial for tracking the changes in sea ice and for assessing the significance of long-term trends. Since the advent of passive microwave satellite instruments in the early 1970s, sea ice has been one of the most consistently monitored climate parameters. There is now a 27+ year record of sea ice extent and concentration from multi-channel passive microwave radiometers that has undergone inter-sensor calibration and other quality controls to ensure consistency throughout the record. Several algorithms have been developed over the years to retrieve sea ice extent and concentration and two of the most commonly used algorithms, the NASA Team and Bootstrap, have been applied to the entire SMMR-SSM/I record to obtain a consistent time series. These algorithms were developed at NASA Goddard Space Flight Center and are archived at the National Snow and Ice Data Center. However, the complex surface properties of sea ice affect the microwave signature, and algorithms can yield ambiguous results; no single algorithm has been found to work uniformly well under all sea ice conditions. Thus there are ongoing efforts to further refine the algorithms and the time series. One approach is to develop data fusion methods to optimally combine sea ice fields from two or more algorithms. Another approach is to take advantage of the improved capabilities of JAXA's AMSR-E sensor on NASA's Aqua

  7. Energy-Efficient Network Transmission between Satellite Swarms and Earth Stations Based on Lyapunov Optimization Techniques

    Directory of Open Access Journals (Sweden)

    Weiwei Fang

    2014-01-01

    Full Text Available The recent advent of satellite swarm technologies has enabled space exploration with a massive number of picoclass, low-power, and low-weight spacecraft. However, developing swarm-based satellite systems, from conceptualization to validation, is a complex multidisciplinary activity. One of the primary challenges is how to achieve energy-efficient data transmission between the satellite swarm and terrestrial terminal stations. Employing Lyapunov optimization techniques, we present an online control algorithm to optimally dispatch traffic load among different satellite-ground links for minimizing overall energy consumption over time. Our algorithm is able to independently and simultaneously make control decisions on traffic dispatching over intersatellite-links and up-down-links so as to offer provable energy and delay guarantees, without requiring any statistical information of traffic arrivals and link condition. Rigorous analysis and extensive simulations have demonstrated the performance and robustness of the proposed new algorithm.

  8. Satellite Fault Diagnosis Using Support Vector Machines Based on a Hybrid Voting Mechanism

    Directory of Open Access Journals (Sweden)

    Hong Yin

    2014-01-01

    Full Text Available The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved.

  9. Validation of satellite-based noontime UVI with NDACC ground-based instruments: influence of topography, environment and satellite overpass time

    Science.gov (United States)

    Brogniez, Colette; Auriol, Frédérique; Deroo, Christine; Arola, Antti; Kujanpää, Jukka; Sauvage, Béatrice; Kalakoski, Niilo; Riku Aleksi Pitkänen, Mikko; Catalfamo, Maxime; Metzger, Jean-Marc; Tournois, Guy; Da Conceicao, Pierre

    2016-12-01

    Spectral solar UV radiation measurements are performed in France using three spectroradiometers located at very different sites. One is installed in Villeneuve d'Ascq, in the north of France (VDA). It is an urban site in a topographically flat region. Another instrument is installed in Observatoire de Haute-Provence, located in the southern French Alps (OHP). It is a rural mountainous site. The third instrument is installed in Saint-Denis, Réunion Island (SDR). It is a coastal urban site on a small mountainous island in the southern tropics. The three instruments are affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC) and carry out routine measurements to monitor the spectral solar UV radiation and enable derivation of UV index (UVI). The ground-based UVI values observed at solar noon are compared to similar quantities derived from the Ozone Monitoring Instrument (OMI, onboard the Aura satellite) and the second Global Ozone Monitoring Experiment (GOME-2, onboard the Metop-A satellite) measurements for validation of these satellite-based products. The present study concerns the period 2009-September 2012, date of the implementation of a new OMI processing tool. The new version (v1.3) introduces a correction for absorbing aerosols that were not considered in the old version (v1.2). Both versions of the OMI UVI products were available before September 2012 and are used to assess the improvement of the new processing tool. On average, estimates from satellite instruments always overestimate surface UVI at solar noon. Under cloudless conditions, the satellite-derived estimates of UVI compare satisfactorily with ground-based data: the median relative bias is less than 8 % at VDA and 4 % at SDR for both OMI v1.3 and GOME-2, and about 6 % for OMI v1.3 and 2 % for GOME-2 at OHP. The correlation between satellite-based and ground-based data is better at VDA and OHP (about 0.99) than at SDR (0.96) for both space-borne instruments. For all

  10. Fairness based channel borrowing strategy in multimedia LEO satellite communications

    Institute of Scientific and Technical Information of China (English)

    HUANG Fei; XU Hui; WU Shiqi

    2007-01-01

    A novel bandwidth allocation strategy along with a connection admission control technique was proposed to improve the utilization of network resources.It provides the network with better quality-of-service (QoS) guarantees,such as new call blocking probability (CBP) and handoff call dropping probability (CDP) in multimedia low earth orbit (LEO) satellite networks.Simulation results show that,compared with other bandwidth allocation schemes,the proposed scheme offers very low call dropping probability for real-time connections while,at the same time,keeping resource utilization high.Finally we discussed the fairness for the borrowed nonreal-time connections under three different channel borrowing methods.

  11. A new algorithm for agile satellite-based acquisition operations

    Science.gov (United States)

    Bunkheila, Federico; Ortore, Emiliano; Circi, Christian

    2016-06-01

    Taking advantage of the high manoeuvrability and the accurate pointing of the so-called agile satellites, an algorithm which allows efficient management of the operations concerning optical acquisitions is described. Fundamentally, this algorithm can be subdivided into two parts: in the first one the algorithm operates a geometric classification of the areas of interest and a partitioning of these areas into stripes which develop along the optimal scan directions; in the second one it computes the succession of the time windows in which the acquisition operations of the areas of interest are feasible, taking into consideration the potential restrictions associated with these operations and with the geometric and stereoscopic constraints. The results and the performances of the proposed algorithm have been determined and discussed considering the case of the Periodic Sun-Synchronous Orbits.

  12. Characterization of satellite based proxies for estimating nucleation mode particles over South Africa

    Directory of Open Access Journals (Sweden)

    A.-M. Sundström

    2014-10-01

    Full Text Available In this work satellite observations from the NASA's A-Train constellation were used to derive the values of primary emission and regional nucleation proxies over South Africa to estimate the potential for new particle formation. As derived in Kulmala et al. (2011, the satellite based proxies consist of source terms (NO2, SO2 and UV-B radiation, and a sink term describing the pre-existing aerosols. The first goal of this work was to study in detail the use of satellite aerosol optical depth (AOD as a substitute to the in situ based condensation sink (CS. One of the major factors affecting the agreement of CS and AOD was the elevated aerosol layers that increased the value of column integrated AOD but not affected the in situ CS. However, when the AOD in the proxy sink was replaced by an estimate from linear bivariate fit between AOD and CS, the agreement with the actual nucleation mode number concentration improved somewhat. The second goal of the work was to estimate how well the satellite based proxies can predict the potential for new particle formation. For each proxy the highest potential for new particle formation were observed over the Highveld industrial area, where the emissions were high but the sink due to pre-existing aerosols was relatively low. Best agreement between the satellite and in situ based proxies were obtained for NO2/AOD and UV-B/AOD2, whereas proxies including SO2 in the source term had lower correlation. Even though the OMI SO2 boundary layer product showed reasonable spatial pattern and detected the major sources over the study area, some of the known minor point sources were not detected. When defining the satellite proxies only for days when new particle formation event was observed, it was seen that for all the satellite based proxies the event day medians were higher than the entire measurement period median.

  13. Wave energy resource assessment based on satellite observations around Indonesia

    Science.gov (United States)

    Ribal, Agustinus; Zieger, Stefan

    2016-06-01

    A preliminary assessment of wave energy resource around Indonesian's ocean has been carried out by means of analyzing satellite observations. The wave energy flux or wave power can be approximated using parameterized sea states. Wave power scales with significant wave height, characteristic wave period and water depth. In this approach, the significant wave heights were obtained from ENVISAT (Environmental Satellite) data which have been calibrated. However, as the characteristic wave period is rarely specified and therefore must be estimated from other variables when information about the wave spectra is unknown. Here, the characteristic wave period was calculated with an empirical model that utilizes altimeter estimates of wave height and backscatter coefficient originally proposed. For the Indonesian region, wave power energy is calculated over two periods of one year each and was compared with the results from global hindcast carried out with a recent release of wave model WAVEWATCH III. We found that, the most promising wave power energy regions around the Indonesian archipelago are located in the south of Java island and the south west of Sumatera island. In these locations, about 20 - 30 kW/m (90th percentile: 30-50 kW/m, 99th percentile: 40-60 kW/m) wave power energy on average has been found around south of Java island during 2010. Similar results have been found during 2011 at the same locations. Some small areas which are located around north of Irian Jaya (West Papua) are also very promising and need further investigation to determine its capacity as a wave energy resource.

  14. Simulation and Analysis of Autonomous Time Synchronization Based on Asynchronism Two-way Inter-satellite Link

    Science.gov (United States)

    Fang, L.; Yang, X. H.; Sun, B. Q.; Qin, W. J.; Kong, Y.

    2013-09-01

    The measurement of the inter-satellite link is one of the key techniques in the autonomous operation of satellite navigation system. Based on the asynchronism inter-satellite two-way measurement mode in GPS constellation, the reduction formula of the inter-satellite time synchronization is built in this paper. Moreover, the corrective method of main systematic errors is proposed. Inter-satellite two-way time synchronization is simulated on the basis of IGS (International GNSS Service) precise ephemeris. The impacts of the epoch domestication of asynchronism inter-satellite link pseudo-range, the initial orbit, and the main systematic errors on satellite time synchronization are analyzed. Furthermore, the broadcast clock error of each satellite is calculated by the ``centralized'' inter-satellite autonomous time synchronization. Simulation results show that the epoch domestication of asynchronism inter-satellite link pseudo-range and the initial orbit have little impact on the satellite clock errors, and thus they needn't be taken into account. The errors caused by the relativistic effect and the asymmetry of path travel have large impact on the satellite clock errors. These should be corrected with theoretical formula. Compared with the IGS precise clock error, the root mean square of the broadcast clock error of each satellite is about 0.4 ns.

  15. Object Based and Pixel Based Classification Using Rapideye Satellite Imager of ETI-OSA, Lagos, Nigeria

    Directory of Open Access Journals (Sweden)

    Esther Oluwafunmilayo Makinde

    2016-12-01

    Full Text Available Several studies have been carried out to find an appropriate method to classify the remote sensing data. Traditional classification approaches are all pixel-based, and do not utilize the spatial information within an object which is an important source of information to image classification. Thus, this study compared the pixel based and object based classification algorithms using RapidEye satellite image of Eti-Osa LGA, Lagos. In the object-oriented approach, the image was segmented to homogenous area by suitable parameters such as scale parameter, compactness, shape etc. Classification based on segments was done by a nearest neighbour classifier. In the pixel-based classification, the spectral angle mapper was used to classify the images. The user accuracy for each class using object based classification were 98.31% for waterbody, 92.31% for vegetation, 86.67% for bare soil and 90.57% for Built up while the user accuracy for the pixel based classification were 98.28% for waterbody, 84.06% for Vegetation 86.36% and 79.41% for Built up. These classification techniques were subjected to accuracy assessment and the overall accuracy of the Object based classification was 94.47%, while that of Pixel based classification yielded 86.64%. The result of classification and accuracy assessment show that the object-based approach gave more accurate and satisfying results

  16. Thermal surveillance of Cascade Range volcanoes using ERTS-1 multispectral scanner, aircraft imaging systems, and ground-based data communication platforms

    Science.gov (United States)

    Friedman, J. D.; Frank, D. G.; Preble, D.; Painter, J. E.

    1973-01-01

    A combination of infrared images depicting areas of thermal emission and ground calibration points have proved to be particularly useful in plotting time-dependent changes in surface temperatures and radiance and in delimiting areas of predominantly convective heat flow to the earth's surface in the Cascade Range and on Surtsey Volcano, Iceland. In an integrated experiment group using ERTS-1 multispectral scanner (MSS) and aircraft infrared imaging systems in conjunction with multiple thermistor arrays, volcano surface temperatures are relayed daily to Washington via data communication platform (DCP) transmitters and ERTS-1. ERTS-1 MSS imagery has revealed curvilinear structures at Lassen, the full extent of which have not been previously mapped. Interestingly, the major surface thermal manifestations at Lassen are aligned along these structures, particularly in the Warner Valley.

  17. Spot-5 multispectral image for 60-75 days of rice mapping

    Science.gov (United States)

    Amiruddin Ramli, Mohd; Shariff, Abdul Rashid Mohamed; Khairunniza Bejo, Siti

    2014-06-01

    The objective of this study is to investigate the potential application of Spot-5 multispectral satellite data in monitoring rice cultivation areas in IADA (Integrated Agriculture Development Area) located at Kerian District, Perak Malaysia. Information of the rice cultivation areas is a global economic and environmental significance. Multi-spectral images acquired at high spatial resolution are an important tool, especially in agricultural applications. This paper addresses the relationship between normalize difference vegetation index (NDVI) and ancillary data acquired from Farmers Organization Authority (PPK) for 217 farmer's field in IADA Kerian. The results indicated that NDVI range 0.62 - 0.75 has a strong positive relationship with the ground survey area estimation with (r = 0.85; p Malaysia. The results appear promising and rice mapping operations using SPOT-5 multispectral image data can be foreseen.

  18. Adjusting thresholds of satellite-based convective initiation interest fields based on the cloud environment

    Science.gov (United States)

    Jewett, Christopher P.; Mecikalski, John R.

    2013-11-01

    The Time-Space Exchangeability (TSE) concept states that similar characteristics of a given property are closely related statistically for objects or features within close proximity. In this exercise, the objects considered are growing cumulus clouds, and the data sets to be considered in a statistical sense are geostationary satellite infrared (IR) fields that help describe cloud growth rates, cloud top heights, and whether cloud tops contain significant amounts of frozen hydrometeors. In this exercise, the TSE concept is applied to alter otherwise static thresholds of IR fields of interest used within a satellite-based convective initiation (CI) nowcasting algorithm. The convective environment in which the clouds develop dictate growth rate and precipitation processes, and cumuli growing within similar mesoscale environments should have similar growth characteristics. Using environmental information provided by regional statistics of the interest fields, the thresholds are examined for adjustment toward improving the accuracy of 0-1 h CI nowcasts. Growing cumulus clouds are observed within a CI algorithm through IR fields for many 1000 s of cumulus cloud objects, from which statistics are generated on mesoscales. Initial results show a reduction in the number of false alarms of ~50%, yet at the cost of eliminating approximately ~20% of the correct CI forecasts. For comparison, static thresholds (i.e., with the same threshold values applied across the entire satellite domain) within the CI algorithm often produce a relatively high probability of detection, with false alarms being a significant problem. In addition to increased algorithm performance, a benefit of using a method like TSE is that a variety of unknown variables that influence cumulus cloud growth can be accounted for without need for explicit near-cloud observations that can be difficult to obtain.

  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. DETECTING ANOMALY REGIONS IN SATELLITE IMAGE TIME SERIES BASED ON SESAONAL AUTOCORRELATION ANALYSIS

    Directory of Open Access Journals (Sweden)

    Z.-G. Zhou

    2016-06-01

    Full Text Available 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.

  1. Object-based illumination normalization for multi-temporal satellite images in urban area

    Science.gov (United States)

    Su, Nan; Zhang, Ye; Tian, Shu; Yan, Yiming

    2016-09-01

    Multi-temporal satellite images acquisition with different illumination conditions cause radiometric difference to have a huge effect on image quality during remote sensing image processing. In particular, image matching of satellite stereo images with great difference between acquisition dates is very difficult for the high-precision DSM generation in the field of satellite photogrammetry. Therefore, illumination normalization is one of the greatest application technology to eliminate radiometric difference for image matching and other image applications. In this paper, we proposed a novel method of object-based illumination normalization to improve image matching of different temporal satellite stereo images in urban area. Our proposed method include two main steps: 1) the object extraction 2) multi-level illumination normalization. Firstly, we proposed a object extraction method for the same objects extraction among the multi-temporal satellite images, which can keep the object structural attribute. Moreover, the multi-level illumination normalization is proposed by combining gradient domain method and singular value decomposition (SVD) according to characteristic information of relevant objects. Our proposed method has great improvement for the illumination of object area to be benefit for image matching in urban area with multiple objects. And the histogram similarity parameter and matching rate are used for illumination consistency quantitative evaluation. The experiments have been conducted on different satellite images with different acquisition dates in the same urban area to verify the effectiveness of our proposed method. The experimental results demonstrate a good performance by comparing other methods.

  2. Assessing Satellite-Based Fire Data for use in the National Emissions Inventory

    Science.gov (United States)

    Soja, Amber J.; Al-Saadi, Jassim; Giglio, Louis; Randall, Dave; Kittaka, Chieko; Pouliot, George; Kordzi, Joseph J.; Raffuse, Sean; Pace, Thompson G.; Pierce, Thomas E.; Moore, Tom; Biswadev, Roy; Pierce, R. Bradley; Szykman, James J.

    2009-01-01

    Biomass burning is significant to emission estimates because: (1) it can be a major contributor of particulate matter and other pollutants; (2) it is one of the most poorly documented of all sources; (3) it can adversely affect human health; and (4) it has been identified as a significant contributor to climate change through feedbacks with the radiation budget. Additionally, biomass burning can be a significant contributor to a regions inability to achieve the National Ambient Air Quality Standards for PM 2.5 and ozone, particularly on the top 20% worst air quality days. The United States does not have a standard methodology to track fire occurrence or area burned, which are essential components to estimating fire emissions. Satellite imagery is available almost instantaneously and has great potential to enhance emission estimates and their timeliness. This investigation compares satellite-derived fire data to ground-based data to assign statistical error and helps provide confidence in these data. The largest fires are identified by all satellites and their spatial domain is accurately sensed. MODIS provides enhanced spatial and temporal information, and GOES ABBA data are able to capture more small agricultural fires. A methodology is presented that combines these satellite data in Near-Real-Time to produce a product that captures 81 to 92% of the total area burned by wildfire, prescribed, agricultural and rangeland burning. Each satellite possesses distinct temporal and spatial capabilities that permit the detection of unique fires that could be omitted if using data from only one satellite.

  3. Satellite-Based actual evapotranspiration over drying semiarid terrain in West-Africa

    NARCIS (Netherlands)

    Schuttemeyer, D.; Schillings, Ch.; Moene, A.F.; Bruin, de H.A.R.

    2007-01-01

    A simple satellite-based algorithm for estimating actual evaporation based on Makkink¿s equation is applied to a seasonal cycle in 2002 at three test sites in Ghana, West Africa: at a location in the humid tropical southern region and two in the drier northern region. The required input for the algo

  4. Neural Network Based Lna Design for Mobile Satellite Receiver

    Directory of Open Access Journals (Sweden)

    Abhijeet Upadhya

    2014-08-01

    Full Text Available Paper presents a Neural Network Modelling approach to microwave LNA design. To acknowledge the specifications of the amplifier, Mobile Satellite Systems are analyzed. Scattering parameters of the LNA in the frequency range 0.5 to 18 GHz are calculated using a Multilayer Perceptron Artificial Neural Network model and corresponding smith charts and polar charts are plotted as output to the model. From these plots, the microwave scattering parameter description of the LNA are obtained. Model is efficiently trained using Agilent ATF 331M4 InGaAs/InP Low Noise pHEMT amplifier datasheet and the neural model’s output seem to follow the various device characteristic curves with high regression. Next, Maximum Allowable Gain and Noise figure of the device are modelled and plotted for the same frequency range. Finally, the optimized model is utilized as an interpolator and the resolution of the amplifying capability with noise characteristics are obtained for the L Band of MSS operation.

  5. 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.

  6. The comparison analysis of land cover change based on vegetation index and multispectral classification (Case study Leihitu Peninsula Ambon City District

    Directory of Open Access Journals (Sweden)

    W.A. Siahaya

    2015-07-01

    Full Text Available The study utilizes Landsat-7 ETM+ 2001and Landsat TM5 2009 based on Normalized Differences Vegetation Index (NDVI and 457 colour composite at the study area located in Leihitu Peninsula, Ambon City District, Ambon Island, Moluccas Province. The classified satellite data under NDVI and 457 colour composite of 2001 and 2009 of 2001 and 2009 were used to determine land cover change that have occurred in the study areas. This study attempts to use a comparative change detection analysis in land cover that has occurred in the study area with NDVI and 457 colour composite over 9 year period (2001 to 2009. The results of the present study disclose that total area increased their land cover were bare land and impermeable surface, herbaceous and shrubs, low density vegetation, and medium density vegetation, while high density vegetation is decreasing in both NDVI and 457 colour composite analysis. Overall accuracy was estimated to be around 94.3 % for NDVI and for 457 Colour composites was 84.7%. The study area has experienced a change in its land cover between 2001 and 2009 in both NDVI and 457 false colour composite analyses. The whole land cover types have experienced increased in both methods, except high density vegetation. The transformations of spectral vegetation (NDVI product more closely with actual land cover compared with 457 colour composite product.

  7. 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

  8. Multispectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2012-01-01

    only with fish oil. In this study, multispectral image analysis of pellets captured reflection in 20 wavelengths (385–1050 nm). Linear discriminant analysis (LDA), principal component analysis, and support vector machine were used as statistical analysis. The features extracted from the multispectral...

  9. Perceptual evaluation of color transformed multispectral imagery

    NARCIS (Netherlands)

    Toet, A.; Jong, M.J. de; Hogervorst, M.A.; Hooge, I.T.C.

    2014-01-01

    Color remapping can give multispectral imagery a realistic appearance. We assessed the practical value of this technique in two observer experiments using monochrome intensified (II) and long-wave infrared (IR) imagery, and color daylight (REF) and fused multispectral (CF) imagery. First, we investi

  10. Satellite-based assessment of yield variation and its determinants in smallholder African systems

    Science.gov (United States)

    Lobell, David B.

    2017-01-01

    The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest (R2 up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods. PMID:28202728

  11. PARTICLE SWARM OPTIMIZATION BASED ON PYRAMID MODEL FOR SATELLITE MODULE LAYOUT

    Institute of Scientific and Technical Information of China (English)

    Zhang Bao; Teng Hongfei

    2005-01-01

    To improve the global search ability of particle swarm optimization (PSO), a multi-population PSO based on pyramid model (PPSO) is presented. Then, it is applied to solve the layout optimization problems against the background of an international commercial communication satellite (INTELSAT-Ⅲ) module. Three improvements are developed, including multi-population search based on pyramid model, adaptive collision avoidance among particles, and mutation of degraded particles. In the numerical examples of the layout design of this simplified satellite module, the performance of PPSO is compared to global version PSO and local version PSO (ring and Neumann PSO). The results show that PPSO has higher computational accuracy, efficiency and success ratio.

  12. A MEMS-based Adaptive AHRS for Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

    Wang, Yunlong; Hussain, Dil Muhammed Akbar; Soltani, Mohsen

    2015-01-01

    Satellite tracking is a challenging task for marine applications. An attitude determination system should estimate the wave disturbances on the ship body accurately. To achieve this, an Attitude Heading Reference System (AHRS) based on Micro-Electro-Mechanical Systems (MEMS) sensors, composed...... of three-axis gyroscope, accelerometer and magnetometer, is developed for Marine Satellite Tracking Antenna (MSTA). In this paper, the attitude determination algorithm is improved using an adaptive mechanism that tunes the attitude estimator parameters based on an estimation of ship motion frequency...

  13. Multi-spectral confocal microendoscope for in-vivo imaging

    Science.gov (United States)

    Rouse, Andrew Robert

    The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

  14. Evaluation of satellite soil moisture products over Norway using ground-based observations

    Science.gov (United States)

    Griesfeller, A.; Lahoz, W. A.; Jeu, R. A. M. de; Dorigo, W.; Haugen, L. E.; Svendby, T. M.; Wagner, W.

    2016-03-01

    In this study we evaluate satellite soil moisture products from the advanced SCATterometer (ASCAT) and the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over Norway using ground-based observations from the Norwegian water resources and energy directorate. The ASCAT data are produced using the change detection approach of Wagner et al. (1999), and the AMSR-E data are produced using the VUA-NASA algorithm (Owe et al., 2001, 2008). Although satellite and ground-based soil moisture data for Norway have been available for several years, hitherto, such an evaluation has not been performed. This is partly because satellite measurements of soil moisture over Norway are complicated owing to the presence of snow, ice, water bodies, orography, rocks, and a very high coastline-to-area ratio. This work extends the European areas over which satellite soil moisture is validated to the Nordic regions. Owing to the challenging conditions for soil moisture measurements over Norway, the work described in this paper provides a stringent test of the capabilities of satellite sensors to measure soil moisture remotely. We show that the satellite and in situ data agree well, with averaged correlation (R) values of 0.72 and 0.68 for ASCAT descending and ascending data vs in situ data, and 0.64 and 0.52 for AMSR-E descending and ascending data vs in situ data for the summer/autumn season (1 June-15 October), over a period of 3 years (2009-2011). This level of agreement indicates that, generally, the ASCAT and AMSR-E soil moisture products over Norway have high quality, and would be useful for various applications, including land surface monitoring, weather forecasting, hydrological modelling, and climate studies. The increasing emphasis on coupled approaches to study the earth system, including the interactions between the land surface and the atmosphere, will benefit from the availability of validated and improved soil moisture satellite datasets, including those

  15. Unmodelled magnetic contributions in satellite-based models

    Science.gov (United States)

    Tozzi, Roberta; Mandea, Mioara; De Michelis, Paola

    2016-06-01

    A complex system of electric currents flowing in the ionosphere and magnetosphere originates from the interaction of the solar wind and the Interplanetary Magnetic Field (IMF) with the Earth's magnetic field. These electric currents generate magnetic fields contributing themselves to those measured by both ground observatories and satellites. Here, low-resolution (1 Hz) magnetic vector data recorded between 1 March 2014 and 31 May 2015 by the recently launched Swarm constellation are considered. The core and crustal magnetic fields and part of that originating in the magnetosphere are removed from Swarm measurements using CHAOS-5 model. Low- and mid-latitude residuals of the geomagnetic field representing the ionospheric and the unmodelled magnetospheric contributions are investigated, in the Solar Magnetic frame, according to the polarity of IMF B y (azimuthal) and B z (north-south) components and to different geomagnetic activity levels. The proposed approach makes it possible to investigate the features of unmodelled contributions due to the external sources of the geomagnetic field. Results show, on one side, the existence of a relation between the analysed residuals and IMF components B y and B z , possibly due to the long distance effect of high-latitude field-aligned currents. On the other side, they suggest the presence of a contribution due to the partial ring current that is activated during the main phase of geomagnetic storms. The perturbation observed on residuals is also compatible with the effect of the net field-aligned currents. Moreover, we have quantitatively estimated the effect of these current systems on computed residuals.

  16. Variability and trends of surface solar radiation in Europe based on CM SAF satellite data records

    Science.gov (United States)

    Trentmann, Jörg; Pfeifroth, Uwe; Sanchez-Lorenzo, Arturo; Urbain, Manon; Clerbaux, Nicolas

    2017-04-01

    The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based high-quality climate data records, with a focus on the global energy and water cycle. Here, the latest releases of the CM SAF's data records of surface solar radiation, Surface Solar Radiation Data Set - Heliosat (SARAH), and CM SAF cLouds, Albedo and Radiation dataset from AVHRR data (CLARA), are analyzed and validated with reference to ground-based measurements, e.g., provided by the Baseline Surface Radiation Network (BSRN), the World Radiation Data Center (WRDC) and the Global Energy Balance Archive (GEBA). Focus is given to the trends and the variability of the surface irradiance in Europe as derived from the surface and the satellite-based data records. Both data sources show an overall increase (i.e., brightening) after the 1980s, and indicate substantial decadal variability with periods of reduced increase (or even a decrease) and periods with a comparable high increase. Also the increase shows a pronounced spatial pattern, which is also found to be consistent between the two data sources. The good correspondence between the satellite-based data records and the surface measurements highlight the potential of the satellite data to represent the variability and changes in the surface irradiance and document the dominant role of clouds over aerosol to explain its variations. Reasons for remaining differences between the satellite- and the surface-based data records (e.g., in Southern Europe) will be discussed. To test the consistency of the CM SAF solar radiation data records we also assess the decadal variability of the solar reflected radiation at the top-of-the atmosphere (TOA) from the CM SAF climate data record based on the MVIRI / SEVIRI measurements from 1983 to 2015. This data record complements the SARAH data record in its temporal and spatial coverage; fewer and different assumptions are used in the retrieval to generate the TOA reflected solar

  17. Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

    Science.gov (United States)

    Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

    2016-09-01

    The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

  18. 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.

  19. 基于小波分解的油菜多光谱图像与深度图像数据融合方法%Data fusion of multispectral and depth image for rape plant based on wavelet decomposition

    Institute of Scientific and Technical Information of China (English)

    张艳超; 肖宇钊; 庄载椿; 许凯雯; 何勇

    2016-01-01

    Multi-source image fusion can reduce the miscalculation caused by using single source image. Using the complement and redundancies between multi-source data fusion between complete data can improve the reliability of data. This research was done based on the wavelet decomposition reconstruction method on near ground unmanned aerial vehicle (UAV) simulation platform. Two source image, respectively multispectral image and depth image of rapeseed were acquired. Camera produced by PMD Company, an active imaging sensor which measures the time of flight of infrared light from generator to sensor was used to acquire depth image. Three kinds of image data was acquired from PMD camera namely distance image, intensity image and amplitude image. The three images were different forms of same data from sensor while the intensity image was more sensitive to the edge information in visual field. Tetracam ADC multispectral camera was used for multispectral image acquisition. The images acquired were calibrated using white board. To register the image, depth imaging principle was analyzed and intensity image was used for camera internal parameter calibration. Pinhole model was used and chessboard calibration method was used for camera internal parameters. Since the distance image can’t see Harris points, intensity image was used for image calibration instead. The distance image and intensity image had same internal parameters. The internal parameters were final used for depth image correction so as to generate lens distortion –free images. SIFT method was used to find the corresponding points between two images. The first step was to find feature point descriptors, the second step was to use Mahalanobis distance to find proper matches. Match ratio of 0.6 was appropriate through tests for this purpose. After feature points were found and matched, multispectral image and depth image were resized to same zoom level then were registered and cropped to same size based on the

  20. The Huber’s Method-based Gas Concentration Reconstruction in Multicomponent Gas Mixtures from Multispectral Laser Measurements under Noise Overshoot Conditions

    Directory of Open Access Journals (Sweden)

    V. A. Gorodnichev

    2016-01-01

    Full Text Available Laser gas analysers are the most promising for the rapid quantitative analysis of gaseous air pollution. A laser gas analysis problem is that there are instable results in reconstruction of gas mixture components concentration under real noise in the recorded laser signal. This necessitates using the special processing algorithms. When reconstructing the quantitative composition of multi-component gas mixtures from the multispectral laser measurements are efficiently used methods such as Tikhonov regularization, quasi-solution search, and finding of Bayesian estimators. These methods enable using the single measurement results to determine the quantitative composition of gas mixtures under measurement noise. In remote sensing the stationary gas formations or in laboratory analysis of the previously selected (when the gas mixture is stationary air samples the reconstruction procedures under measurement noise of gas concentrations in multicomponent mixtures can be much simpler. The paper considers a problem of multispectral laser analysis of stationary gas mixtures for which it is possible to conduct a series of measurements. With noise overshoots in the recorded laser signal (and, consequently, overshoots of gas concentrations determined by a single measurement must be used stable (robust estimation techniques for substantial reducing an impact of the overshoots on the estimate of required parameters. The paper proposes the Huber method to determine gas concentrations in multicomponent mixtures under signal overshoot. To estimate the value of Huber parameter and the efficiency of Huber's method to find the stable estimates of gas concentrations in multicomponent stationary mixtures from the laser measurements the mathematical modelling was conducted. Science & Education of the Bauman MSTU 108 The mathematical modelling results show that despite the considerable difference among the errors of the mixture gas components themselves a character of

  1. Face Shape and Reflectance Acquisition using a Multispectral Light Stage

    CERN Document Server

    Dutta, Abhishek

    2011-01-01

    In this thesis, we discuss the design and calibration (geometric and radiometric) of a novel shape and reflectance acquisition device called the "Multispectral Light Stage". This device can capture highly detailed facial geometry (down to the level of skin pores detail) and Multispectral reflectance map which can be used to estimate biophysical skin parameters such as the distribution of pigmentation and blood beneath the surface of the skin. We extend the analysis of the original spherical gradient photometric stereo method to study the effects of deformed diffuse lobes on the quality of recovered surface normals. Based on our modified radiance equations, we develop a minimal image set method to recover high quality photometric normals using only four, instead of six, spherical gradient images. Using the same radiance equations, we explore a Quadratic Programming (QP) based algorithm for correction of surface normals obtained using spherical gradient photometric stereo. Based on the proposed minimal image se...

  2. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2010-09-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved retrievals of surface soil moisture variations at global scales. Here we propose a technique to take advantage of retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates over sparse-to-moderately vegetated areas to obtain an improved soil moisture product. To do this, absolute soil moisture values from AMSR-E and relative soil moisture derived from ASCAT are rescaled against a reference land surface model date set using a cumulative distribution function (CDF matching approach. While this technique imposes the bias of the reference to the rescaled satellite products, it adjusts both satellite products to the same range and almost preserves the correlation between satellite products and in situ measurements. Comparisons with in situ data demonstrated that over the regions where the correlation coefficient between rescaled AMSR-E and ASCAT is above 0.65 (hereafter referred to as transitional regions, merging the different satellite products together increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT are respectively used in the merged product. Thus the merged product carries the advantages of better spatial coverage overall and increased number of observations particularly for the transitional regions. The combination approach developed in this study has the potential to be applied to existing microwave satellites as well as to new microwave missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  3. Motivating Students to Develop Satellites in a Problem and Project-Based Learning Environment

    DEFF Research Database (Denmark)

    Larsen, Jesper Abildgaard; Nielsen, Jens Frederik Dalsgaard; Zhou, Chunfang

    2013-01-01

    During the last decade, a total of three student satellites have been developed by engineering students in a Problem and Project-Based Learning (PBL) environment at Aalborg University (AAU), Denmark. As solving such a complex project, we emphasize that a high level of motivation is needed...... satellite projects in a PBL environment. Empirically, a total of 12 student participants were interviewed. The results show that students’ motivation is highly stimulated by the project management with a series of factors, such as the task characteristics, support of peers, help of supervisors, and openness...

  4. Research of Multi-Agent System based satellite fault diagnosis technology

    Institute of Scientific and Technical Information of China (English)

    范显峰; 姜兴渭; 黄文虎; 谷吉海

    2002-01-01

    Following the theory of Multi-Agent System (MAS) and using series-wound structure and shunt-wound structure of Agents, the performance of Agent was improved to satisfy the need of satellite fault diagno-sis, and a tridimensional MAS model of satellite fault diagnosis was thus established for the MAS based planardiagnosis system, which decentralizes the whole diagnosing task into subtasks to be performed by different func-tional Agents to make the complicated fault diagnosis very simple and the diagnosis system more intelligent.This method improved the reliability and accuracy of diagnosis and made the maintenance and upgrading of thesatellite fault diagnosis system very easy as well.

  5. Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates

    Energy Technology Data Exchange (ETDEWEB)

    Sengupta, M.; Gotseff, P.

    2013-12-01

    This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear sky model performance.

  6. Satellite-based empirical models linking river plume dynamics with hypoxic area andvolume

    Science.gov (United States)

    Satellite-based empirical models explaining hypoxic area and volume variation were developed for the seasonally hypoxic (O2 < 2 mg L−1) northern Gulf of Mexico adjacent to the Mississippi River. Annual variations in midsummer hypoxic area and ...

  7. Efficient GOCE satellite gravity field recovery based on least-squares using QR decomposition

    NARCIS (Netherlands)

    Baur, O.; Austen, G.; Kusche, J.

    2007-01-01

    We develop and apply an efficient strategy for Earth gravity field recovery from satellite gravity gradiometry data. Our approach is based upon the Paige-Saunders iterative least-squares method using QR decomposition (LSQR). We modify the original algorithm for space-geodetic applications: firstly,

  8. MISAT : Designing a Series of Powerful Small Satellites Based upon Micro Systems Technology

    NARCIS (Netherlands)

    Gill, E.; Monna, G.L.E.; Scherpen, J.M.A.; Verhoeven, C.J.M.

    2007-01-01

    MISAT is a research and development cluster which will create a small satellite platform based on Micro Systems Technology (MST) aiming at innovative space as well as terrestrial applications. MISAT is part of the Dutch MicroNed program which has established a microsystems infrastructure to fully

  9. MISAT : Designing a Series of Powerful Small Satellites Based upon Micro Systems Technology

    NARCIS (Netherlands)

    Gill, E.; Monna, G.L.E.; Scherpen, J.M.A.; Verhoeven, C.J.M.

    2007-01-01

    MISAT is a research and development cluster which will create a small satellite platform based on Micro Systems Technology (MST) aiming at innovative space as well as terrestrial applications. MISAT is part of the Dutch MicroNed program which has established a microsystems infrastructure to fully ex

  10. 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.

  11. THE SATELLITE STRUCTURE TOPOLOGY OPTIMIZATION BASED ON HOMOGENIZATION METHOD AND ITS SIZE SENSITIVITY ANALYSIS

    Institute of Scientific and Technical Information of China (English)

    ChenChangya; PanJin; WangDeyu

    2005-01-01

    With the development of satellite structure technology, more and more design parameters will affect its structural performance. It is desirable to obtain an optimal structure design with a minimum weight, including optimal configuration and sizes. The present paper aims to describe an optimization analysis for a satellite structure, including topology optimization and size optimization. Based on the homogenization method, the topology optimization is carried out for the main supporting frame of service module under given constraints and load conditions, and then the sensitivity analysis is made of 15 structural size parameters of the whole satellite and the optimal sizes are obtained. The numerical result shows that the present optimization design method is very effective.

  12. Protocol Support for a New Satellite-Based Airspace Communication Network

    Science.gov (United States)

    Shang, Yadong; Hadjitheodosiou, Michael; Baras, John

    2004-01-01

    We recommend suitable transport protocols for an aeronautical network supporting Internet and data services via satellite. We study the characteristics of an aeronautical satellite hybrid network and focus on the problems that cause dramatically degraded performance of the Transport Protocol. We discuss various extensions to standard TCP that alleviate some of these performance problems. Through simulation, we identify those TCP implementations that can be expected to perform well. Based on the observation that it is difficult for an end-to-end solution to solve these problems effectively, we propose a new TCP-splitting protocol, termed Aeronautical Transport Control Protocol (AeroTCP). The main idea of this protocol is to use a fixed window for flow control and one duplicated acknowledgement (ACK) for fast recovery. Our simulation results show that AeroTCP can maintain higher utilization for the satellite link than end-to-end TCP, especially in high BER environment.

  13. Satellites vs. fiber optics based networks and services - Road map to strategic planning

    Science.gov (United States)

    Marandi, James H. R.

    An overview of a generic telecommunications network and its components is presented, and the current developments in satellite and fiber optics technologies are discussed with an eye on the trends in industry. A baseline model is proposed, and a cost comparison of fiber- vs satellite-based networks is made. A step-by-step 'road map' to the successful strategic planning of telecommunications services and facilities is presented. This road map provides for optimization of the current and future networks and services through effective utilization of both satellites and fiber optics. The road map is then applied to different segments of the telecommunications industry and market place, to show its effectiveness for the strategic planning of executives of three types: (1) those heading telecommunications manufacturing concerns, (2) those leading communication service companies, and (3) managers of telecommunication/MIS departments of major corporations. Future networking issues, such as developments in integrated-services digital network standards and technologies, are addressed.

  14. Deep Learning-Based Large-Scale Automatic Satellite Crosswalk Classification

    Science.gov (United States)

    Berriel, Rodrigo F.; Lopes, Andre Teixeira; de Souza, Alberto F.; Oliveira-Santos, Thiago

    2017-09-01

    High-resolution satellite imagery have been increasingly used on remote sensing classification problems. One of the main factors is the availability of this kind of data. Even though, very little effort has been placed on the zebra crossing classification problem. In this letter, crowdsourcing systems are exploited in order to enable the automatic acquisition and annotation of a large-scale satellite imagery database for crosswalks related tasks. Then, this dataset is used to train deep-learning-based models in order to accurately classify satellite images that contains or not zebra crossings. A novel dataset with more than 240,000 images from 3 continents, 9 countries and more than 20 cities was used in the experiments. Experimental results showed that freely available crowdsourcing data can be used to accurately (97.11%) train robust models to perform crosswalk classification on a global scale.

  15. Multi-Objective Reinforcement Learning for Cognitive Radio-Based Satellite Communications

    Science.gov (United States)

    Ferreira, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

    2016-01-01

    Previous research on cognitive radios has addressed the performance of various machine-learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different cross-layer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3.5 times for clear sky conditions and 6.8 times for rain conditions.

  16. A Handover Strategy in the LEO Satellite-Based Constellation Networks with ISLs

    Institute of Scientific and Technical Information of China (English)

    LIU Gang; GOU Dingyong; WU Shiqi

    2003-01-01

    A new handover strategy named minimal-hops handover(MHH) strategy for the low earth orbit(LEO) satellite constellations networks equipped with inter-satellite links(ISLs) is proposed.MHH strategy, which is based on the hops of the end-to-end connection paths and makes good use of the regularity of the constellation network topology, can appropriately combine the handover procedure with routing and efficiently solve the inter-satellite handover issue. Moreover, MHH strategy can provide quality of services( QoS) guarantees to some extent. The system performances of the MHH strategy, such as time propagation delay and handover frequency, are evaluated and compared with that of other previous strategies. The simulation results show that MHH strategy performs better than other previous handover strategies.

  17. Satellite-based annual evaporation estimates of invasive alien plant ...

    African Journals Online (AJOL)

    2013-12-17

    Dec 17, 2013 ... Water (WFW) programme, have on total evaporation (ET) and the availability of water resources in two highly-invaded ... on water resources were based on the results from the paired catchment ...... Tourism, Pretoria. 85 pp.

  18. Cucumber disease diagnosis using multispectral images

    Science.gov (United States)

    Feng, Jie; Li, Hongning; Shi, Junsheng; Yang, Weiping; Liao, Ningfang

    2009-07-01

    In this paper, multispectral imaging technique for plant diseases diagnosis is presented. Firstly, multispectral imaging system is designed. This system utilizes 15 narrow-band filters, a panchromatic band, a monochrome CCD camera, and standard illumination observing environment. The spectral reflectance and color of 8 Macbeth color patches are reproduced between 400nm and 700nm in the process. In addition, spectral reflectance angle and color difference is obtained through measurements and analysis of color patches using spectrometer and multispectral imaging system. The result shows that 16 narrow-bands multispectral imaging system realizes good accuracy in spectral reflectance and color reproduction. Secondly, a horticultural plant, cucumber' familiar disease are the researching objects. 210 multispectral samples are obtained by multispectral and are classified by BP artificial neural network. The classification accuracies of Sphaerotheca fuliginea, Corynespora cassiicola, Pseudoperonospora cubensis are 100%. Trichothecium roseum and Cladosporium cucumerinum are 96.67% and 90.00%. It is confirmed that the multispectral imaging system realizes good accuracy in the cucumber diseases diagnosis.

  19. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2011-02-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved estimates of surface soil moisture at global scale. We develop and evaluate a methodology that takes advantage of the retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates to produce an improved soil moisture product. First, volumetric soil water content (m3 m−3 from AMSR-E and degree of saturation (% from ASCAT are rescaled against a reference land surface model data set using a cumulative distribution function matching approach. While this imposes any bias of the reference on the rescaled satellite products, it adjusts them to the same range and preserves the dynamics of original satellite-based products. Comparison with in situ measurements demonstrates that where the correlation coefficient between rescaled AMSR-E and ASCAT is greater than 0.65 ("transitional regions", merging the different satellite products increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT, respectively, are used for the merged product. Therefore the merged product carries the advantages of better spatial coverage overall and increased number of observations, particularly for the transitional regions. The combination method developed has the potential to be applied to existing microwave satellites as well as to new missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  20. [In-flight absolute radiometric calibration of UAV multispectral sensor].

    Science.gov (United States)

    Chen, Wei; Yan, Lei; Gou, Zhi-Yang; Zhao, Hong-Ying; Liu, Da-Ping; Duan, Yi-Ni

    2012-12-01

    Based on the data of the scientific experiment in Urad Front Banner for UAV Remote Sensing Load Calibration Field project, with the help of 6 hyperspectral radiometric targets with good Lambertian property, the wide-view multispectral camera in UAV was calibrated adopting reflectance-based method. The result reveals that for green, red and infrared channel, whose images were successfully captured, the linear correlation coefficients between the DN and radiance are all larger than 99%. In final analysis, the comprehensive error is no more than 6%. The calibration results demonstrate that the hyperspectral targets equipped by the calibration field are well suitable for air-borne multispectral load in-flight calibration. The calibration result is reliable and could be used in the retrieval of geophysical parameters.

  1. Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile

    Science.gov (United States)

    Yang, Zhongwen; Hsu, Kuolin; Sorooshian, Soroosh; Xu, Xinyi; Braithwaite, Dan; Verbist, Koen M. J.

    2016-04-01

    Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009-2014. The historical data (satellite and gauge) for 2009-2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide.

  2. Evaluation of Satellite and Ground Based Precipitation Products for Flood Forecasting

    Science.gov (United States)

    Chintalapudi, S.; Sharif, H.; Yeggina, S.

    2012-04-01

    The development in satellite-derived rainfall estimates encouraged the hydrological modeling in sparse gauged basins or ungauged basins. Especially, physically-based distributed hydrological models can benefit from the good spatial and temporal coverage of satellite precipitation products. In this study, three satellite derived precipitation datasets (TRMM, CMORPH, and PERSIANN), NEXRAD, and rain gauge precipitation datasets were used to drive the hydrological model. The physically-based, distributed hydrological model Gridded Surface Subsurface Hydrological Analysis (GSSHA) was used in this study. Focus will be on the results from the Guadalupe River Basin above Canyon Lake and below Comfort, Texas. The Guadalupe River Basin above Canyon Lake and below Comfort Texas drains an area of 1232 km2. Different storm events will be used in these simulations. August 2007 event was used as calibration and June 2007 event was used as validation. Results are discussed interms of accuracy of satellite precipitation estimates with the ground based precipitation estimates, predicting peak discharges, runoff volumes, time lag, and spatial distribution. The initial results showed that, model was able to predict the peak discharges and runoff volumes when using NEXRAD MPE data, and TRMM 3B42 precipitation product. The results also showed that there was time lag in hydrographs driven by both PERSIANN and CMORPH data sets.

  3. Operational use of VIIRS Multispectral Imagery and NUCAPS Soundings in Short-term Weather Forecasting

    Science.gov (United States)

    Molthan, A.; Fuell, K. K.; Berndt, E.; Schultz, L. A.

    2016-12-01

    The NASA/SPoRT Program supports the NOAA/JPSS program through the transition of S-NPP VIIRS and CrIS/ATMS products to prepare users for the upcoming JPSS-1/-2 missions. Several multispectral (i.e. RGB) imagery products can be created from VIIRS based on internationally-accepted recipes developed by EUMETSAT. Initial transition of a Nighttime Microphysics RGB to operations revealed improved distinction between low clouds and fog compared with legacy satellite imagery, and hence, improvement in short-term aviation and public forecasts. An increased number of S-NPP passes at high latitude combined with other instruments led to a series of "microphysical" RGBs to be introduced to NWS forecasters in Alaska at both local weather offices as well as regional aviation centers. Forecasters in Alaska also applied VIIRS microphysical RGBs to identify small scale features such as valley/coastal fog, volcanic ash, and convective precipitation. Further use of a "Dust" RGB in the U.S. southwest led to changes in NWS forecast products due to improvements in detection and monitoring of dust aloft. As multispectral imagery has gained operational acceptance, additional work has begun to develop quantitative products to assist users with their interpretation of RGB imagery. For example, National Center forecasters often use an "Air Mass" RGB to differentiate between possible stratospheric /tropospheric interactions, moist tropical air masses, and cool, continental/maritime air masses. Research was done to demonstrate how the NUCAPS CrIS/ATMS infrared retrieved temperature, moisture, and ozone profiles can aid Air Mass RGB imagery interpretation as well as how these quantitative values are important for anticipating tropical to extratropical transition events. In addition, an enhanced stratospheric depth product was developed to identify the dynamic tropopause from the NUCAPS retrieved ozone profiles to aid identification of stratospheric air influence. Forecasters from National Centers

  4. Satellite-based estimation of rainfall erosivity for Africa

    NARCIS (Netherlands)

    Vrieling, A.; Sterk, G.; Jong, S.M. de

    2010-01-01

    Rainfall erosivity is a measure for the erosive force of rainfall. Rainfall kinetic energy determines the erosivity and is in turn greatly dependent on rainfall intensity. Attempts for its large-scale mapping are rare. Most are based on interpolation of erosivity values derived from rain gauge data.

  5. Linear and Nonlinear Relative Navigation Strategies for Small Satellite Formation Flying Based on Relative Position Measurement

    Science.gov (United States)

    Zhang, Xiaomin; Zheng, You

    Based on linear and nonlinear mathematical model of spacecraft formation flying and technology of relative position measurement of small satellites, the linear and nonlinear relative navigation strategies are developed in this paper. The dynamical characteristics of multi spacecraft formation flying have been researched in many references, including the authors' several International Astronautical Congress papers with numbers of IAF-98-A.2.06, IAA-99-IAA.11.1.09, IAA-01-IAA.11.4.08. Under conditions of short distance and short time, the linear model can describe relative orbit motion; otherwise, nonlinear model must be adopted. Furthermore the means of measurement and their error will influence relative navigation. Thus three kinds of relative navigation strategy are progressed. With consideration of difficulty in relative velocity measurement of small satellites, the three relative navigation strategies are proposed and only depend on sequential data of relative position through measuring the relative distance and relative orientation. The first kind of relative navigation strategy is based on linear model. The second relative navigation strategy is based on nonlinear model, with inclusion of the second order item. In fact the measurement error can not be avoided especially for small satellites, it is mainly considered in the third relative navigation strategy. This research is theoretical yet and a series of formulas of relative navigation are presented in this paper. Also the authors analyzed the three strategies qualitatively and quantitatively. According to results of simulation, the ranges of application are indicated and suggested in allusion to the three strategies of relative navigation. On the view of authors, the relative navigation strategies for small satellite formation flying based on relative position measurement are significant for engineering of small satellite formation flying.

  6. Studies of oceanic tectonics based on GEOS-3 satellite altimetry

    Science.gov (United States)

    Poehls, K. A.; Kaula, W. M.; Schubert, G.; Sandwell, D.

    1979-01-01

    Using statistical analysis, geoidal admittance (the relationship between the ocean geoid and seafloor topography) obtained from GEOS-3 altimetry was compared to various model admittances. Analysis of several altimetry tracks in the Pacific Ocean demonstrated a low coherence between altimetry and seafloor topography except where the track crosses active or recent tectonic features. However, global statistical studies using the much larger data base of all available gravimetry showed a positive correlation of oceanic gravity with topography. The oceanic lithosphere was modeled by simultaneously inverting surface wave dispersion, topography, and gravity data. Efforts to incorporate geoid data into the inversion showed that the base of the subchannel can be better resolved with geoid rather than gravity data. Thermomechanical models of seafloor spreading taking into account differing plate velocities, heat source distributions, and rock rheologies were discussed.

  7. Spacetime effects on satellite-based quantum communications

    Science.gov (United States)

    Bruschi, David Edward; Ralph, Timothy C.; Fuentes, Ivette; Jennewein, Thomas; Razavi, Mohsen

    2014-08-01

    We investigate the consequences of space-time being curved on space-based quantum communication protocols. We analyze tasks that require either the exchange of single photons in a certain entanglement distribution protocol or beams of light in a continuous-variable quantum key distribution scheme. We find that gravity affects the propagation of photons, therefore adding additional noise to the channel for the transmission of information. The effects could be measured with current technology.

  8. Spacetime effects on satellite-based quantum communications

    CERN Document Server

    Bruschi, David Edward; Fuentes, Ivette; Jennewein, Thomas; Razavi, Mohsen

    2013-01-01

    We investigate the effects of space-time curvature on space-based quantum communication protocols. We analyze tasks that require either the exchange of single photons in a certain entanglement distribution protocol or beams of light in a continuous-variable quantum key distribution scheme. We find that gravity affects the propagation of photons, therefore acting as a noisy channel for the transmission of information. The effects can be measured with current technology.

  9. China Plans to Launch FY-3 Meteorological Satellite in 2006

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    China's new generation polar orbit weather satellite FY-3 will be launched by LM-4B launch vehicle in 2006. The FY-3 would be equipped with new global, all-weather, multi-spectral, threedimensional sensors. The new satellite, an improved version of the FY-1, has the resolution of 250m and

  10. Implementing earth observation and advanced satellite based atmospheric sounders for water resource and climate modelling

    DEFF Research Database (Denmark)

    Boegh, E.; Dellwik, Ebba; Hahmann, Andrea N.;

    This paper discusses preliminary remote sensing (MODIS) based hydrological modelling results for the Danish island Sjælland (7330 km2) in relation to project objectives and methodologies of a new research project “Implementing Earth observation and advanced satellite based atmospheric sounders...... for effective land surface representation in water resource modeling” (2009- 2012). The purpose of the new research project is to develop remote sensing based model tools capable of quantifying the relative effects of site-specific land use change and climate variability at different spatial scales....... For this purpose, a) internal catchment processes will be studied using a Distributed Temperature Sensing (DTS) system, b) Earth observations will be used to upscale from field to regional scales, and c) at the largest scale, satellite based atmospheric sounders and meso-scale climate modelling will be used...

  11. Neural network-based recognition of whistlers on spectrograms detected by satellite

    Science.gov (United States)

    Conti, Livio

    2016-04-01

    We present a system to automatically recognize and classify the occurrence of whistler waves on spectrograms of electric field measurements performed by satellite. Whistlers - VLF waves generated by lightning, with a specific spectral dispersion relation - can induce precipitation of trapped Van Allen particles and have a role in the chemistry of some atmospheric components (mainly NOx). Moreover, it has also been suggested that the increase of the number of anomalous whistlers (i.e. whistlers with high value of dispersion constant) could be induced by disturbances in the Earth-ionosphere wave-guide, generated by seismo-electromagnetic emissions. On satellite, the recognition of whistlers asks for analyzing high-resolution spectrograms that cannot be downloaded to Earth, due to the limits of data transmission. For this reason, a real time identification and classification must be performed on satellite, by avoiding downloading all the unprocessed data. The procedure that we have developed is based on a Time Delay Neural Network (TDNN). The TDNN, proposed some years ago for speech recognition, can be fruitfully also applied in real-time analysis of electromagnetic spectrograms in order to detect phenomena characterized by a specific shape/signature such as those of the whistler waves. Some studies have been performed by the RNF experiment on board of the DEMETER satellite and our algorithm could be adopted on board of the satellite CSES (China Seismo-Electromagnetic Satellite), launch scheduled by the end of 2016. Moreover, the procedure can be also adopted to automatic analysis of whistlers detected on ground.

  12. Comparison of NO2 vertical profiles from satellite and ground based measurements over Antarctica

    OpenAIRE

    Kulkarni, Pavan; Bortoli, Daniele; Costa, Maria João; Silva, Ana Maria; Ravegnani, Fabrizio; Giovanelli, Giorgio

    2011-01-01

    The Intercomparison of nitrogen dioxide (NO2) vertical profiles, derived from the satellite based HALogen Occultation Experiment (HALOE) measurements and from the ground based UV-VIS spectrometer GASCOD (Gas Analyzer Spectrometer Correlating Optical Differences) observations at the Mario Zucchelli Station (MZS), in Antarctica, are done for the first time. It is shown here that both datasets are in good agreement showing the same features in terms of magnitude, profile structure, a...

  13. A Satellite-Based Multi-Pollutant Index of Global Air Quality

    Science.gov (United States)

    Cooper, Mathew J.; Martin, Randall V.; vanDonkelaar, Aaron; Lamsal, Lok; Brauer, Michael; Brook, Jeffrey R.

    2012-01-01

    Air pollution is a major health hazard that is responsible formillions of annual excess deaths worldwide. Simpleindicators are useful for comparative studies and to asses strends over time. The development of global indicators hasbeen impeded by the lack of ground-based observations in vast regions of the world. Recognition is growing of the need for amultipollutant approach to air quality to better represent human exposure. Here we introduce the prospect of amultipollutant air quality indicator based on observations from satellite remote sensing.

  14. Heavy precipitation retrieval from combined satellite observations and ground-based lightning measurements

    Science.gov (United States)

    Mugnai, A.; Dietrich, S.; Casella, D.; di Paola, F.; Formenton, M.; Sanò, P.

    2010-09-01

    We have developed a series of algorithms for the retrieval of precipitation (especially, heavy precipitation) over the Mediterranean area using satellite observations from the available microwave (MW) radiometers onboard low Earth orbit (LEO) satellites and from the visible-infrared (VIS-IR) SEVIRI radiometer onboard the European geosynchronous (GEO) satellite Meteosat Second Generation (MSG), in conjunction with lightning data from ground-based networks - such as ZEUS and LINET. These are: • A new approach for precipitation retrieval from space (which we call the Cloud Dynamics and Radiation Database approach, CDRD) that incorporates lightning and environmental/dynamical information in addition to the upwelling microwave brightness temperatures (TB’s) so as to reduce the retrieval uncertainty and improve the retrieval performance; • A new combined MW-IR technique for producing frequent precipitation retrievals from space (which we call PM-GCD technique), that uses passive-microwave (PM) retrievals in conjunction with lightning information and the Global Convection Detection (GCD) technique to discriminate deep convective clouds within the GEO observations; • A new morphing approach (which we call the Lightning-based Precipitation Evolving Technique, L-PET) that uses the available lightning measurements for propagating the rainfall estimates from satellite-borne MW radiometers to a much higher time resolution than the MW observations. We will present and discuss our combined MW/IR/lightning precipitation algorithms and analyses with special reference to some case studies over the western Mediterranean.

  15. Planetary gearbox condition monitoring of ship-based satellite communication antennas using ensemble multiwavelet analysis method

    Science.gov (United States)

    Chen, Jinglong; Zhang, Chunlin; Zhang, Xiaoyan; Zi, Yanyang; He, Shuilong; Yang, Zhe

    2015-03-01

    Satellite communication antennas are key devices of a measurement ship to support voice, data, fax and video integration services. Condition monitoring of mechanical equipment from the vibration measurement data is significant for guaranteeing safe operation and avoiding the unscheduled breakdown. So, condition monitoring system for ship-based satellite communication antennas is designed and developed. Planetary gearboxes play an important role in the transmission train of satellite communication antenna. However, condition monitoring of planetary gearbox still faces challenges due to complexity and weak condition feature. This paper provides a possibility for planetary gearbox condition monitoring by proposing ensemble a multiwavelet analysis method. Benefit from the property on multi-resolution analysis and the multiple wavelet basis functions, multiwavelet has the advantage over characterizing the non-stationary signal. In order to realize the accurate detection of the condition feature and multi-resolution analysis in the whole frequency band, adaptive multiwavelet basis function is constructed via increasing multiplicity and then vibration signal is processed by the ensemble multiwavelet transform. Finally, normalized ensemble multiwavelet transform information entropy is computed to describe the condition of planetary gearbox. The effectiveness of proposed method is first validated through condition monitoring of experimental planetary gearbox. Then this method is used for planetary gearbox condition monitoring of ship-based satellite communication antennas and the results support its feasibility.

  16. Satellite image blind restoration based on surface fitting and multivariate model

    Institute of Scientific and Technical Information of China (English)

    CHEN Xin-bing; YANG Shi-zhi; WANG Xian-hua; QIAO Yan-li

    2009-01-01

    Owing to the blurring effect from atmosphere and camera system in the satellite imaging a blind image restoration algo-rithm is proposed which includes the modulation transfer function (MTF) estimation and the image restoration. In the MTF estimation stage, based on every degradation process of satellite imaging-chain, a combined parametric model of MTF is given and used to fit the surface of normalized logarithmic amplitude spectrum of degraded image. In the image restoration stage, a maximum a posteriori (MAP) based edge-preserving image restoration method is presented which introduces multivariate Laplacian model to characterize the prior distribution of wavelet coefficients of original image. During the image restoration, in order to avoid solving high nonlinear equations, optimization transfer algorithm is adopted to decom-pose the image restoration procedure into two simple steps: Landweber iteration and wavelet thresholding denoising. In the numerical experiment, the satellite image restoration results from SPOT-5 and high resolution camera (HR) of China & Brazil earth resource satellite (CBERS-02B) ane compared, and the proposed algorithm is superior in the image edge preservation and noise inhibition.

  17. On-Line Change Monitoring with Transformed Multi-Spectral Time Series, a Study Case in Tropical Forest

    Science.gov (United States)

    Lu, Meng; Hamunyela, Eliakim

    2016-10-01

    In recent years, the methods for detecting structural changes in time series have been adapted for forest disturbance monitoring using satellite data. The BFAST (Breaks For Additive Season and Trend) Monitor framework, which detects forest cover disturbances from satellite image time series based on empirical fluctuation tests, is particularly used for near real-time deforestation monitoring, and it has been shown to be robust in detecting forest disturbances. Typically, a vegetation index that is transformed from spectral bands into feature space (e.g. normalised difference vegetation index (NDVI)) is used as input for BFAST Monitor. However, using a vegetation index for deforestation monitoring is a major limitation because it is difficult to separate deforestation from multiple seasonality effects, noise, and other forest disturbance. In this study, we address such limitation by exploiting the multi-spectral band of satellite data. To demonstrate our approach, we carried out a case study in a deciduous tropical forest in Bolivia, South America. We reduce the dimensionality from spectral bands, space and time with projective methods particularly the Principal Component Analysis (PCA), resulting in a new index that is more suitable for change monitoring. Our results show significantly improved temporal delay in deforestation detection. With our approach, we achieved a median temporal lag of 6 observations, which was significantly shorter than the temporal lags from conventional approaches (14 to 21 observations).

  18. A MODIS-Based Robust Satellite Technique (RST for Timely Detection of Oil Spilled Areas

    Directory of Open Access Journals (Sweden)

    Teodosio Lacava

    2017-02-01

    Full Text Available Natural crude-oil seepages, together with the oil released into seawater as a consequence of oil exploration/production/transportation activities, and operational discharges from tankers (i.e., oil dumped during cleaning actions represent the main sources of sea oil pollution. Satellite remote sensing can be a useful tool for the management of such types of marine hazards, namely oil spills, mainly owing to the synoptic view and the good trade-off between spatial and temporal resolution, depending on the specific platform/sensor system used. In this paper, an innovative satellite-based technique for oil spill detection, based on the general robust satellite technique (RST approach, is presented. It exploits the multi-temporal analysis of data acquired in the visible channels of the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Aqua satellite in order to automatically and quickly detect the presence of oil spills on the sea surface, with an attempt to minimize “false detections” caused by spurious effects associated with, for instance, cloud edges, sun/satellite geometries, sea currents, etc. The oil spill event that occurred in June 2007 off the south coast of Cyprus in the Mediterranean Sea has been considered as a test case. The resulting data, the reliability of which has been evaluated by both carrying out a confutation analysis and comparing them with those provided by the application of another independent MODIS-based method, showcase the potential of RST in identifying the presence of oil with a high level of accuracy.

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

    Data.gov (United States)

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

  20. Tasseled cap transformation for HJ multispectral remote sensing data

    Science.gov (United States)

    Han, Ling; Han, Xiaoyong

    2015-12-01

    The tasseled cap transformation of remote sensing data has been widely used in environment, agriculture, forest and ecology. Tasseled cap transformation coefficients matrix of HJ multi-spectrum data has been established through Givens rotation matrix to rotate principal component transform vector to whiteness, greenness and blueness direction of ground object basing on 24 scenes year-round HJ multispectral remote sensing data. The whiteness component enhances the brightness difference of ground object, and the greenness component preserves more detailed information of vegetation change while enhances the vegetation characteristic, and the blueness component significantly enhances factory with blue plastic house roof around the town and also can enhance brightness of water. Tasseled cap transformation coefficients matrix of HJ will enhance the application effect of HJ multispectral remote sensing data in their application fields.

  1. Use of multispectral images and chemometrics in tomato seed studies

    DEFF Research Database (Denmark)

    Shrestha, Santosh; Deleuran, Lise Christina; Gislum, René

    During the production of tomato seeds, green tomatoes are normally discarded before seed extraction irrespective of their maturity stage. Studies indicate that seeds from green tomatoes may reach be able to reach full germination capacity. Thus the potential of multispectral imaging for non......-destructive discrimination of seeds based on their germination capacity was investigated. A total of 840 seeds extracted from green and red tomatoes were divided into two sets; a training set and a test set consisting of 648 and 192 seeds respectively. Each set consisted of 96 seeds from green tomatoes. The multispectral......, respectively. Similarly, dead seeds were predicted with 98% of accuracy. Results also showed that 23 and 14 seeds from green tomatoes in the training and test sets respectively were viable, while only one viable seed in the test set was misclassified. The results indicate that green tomatoes might be mature...

  2. 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

  3. Vicarious Calibration of Beijing-1 Multispectral Imagers

    Directory of Open Access Journals (Sweden)

    Zhengchao Chen

    2014-02-01

    Full Text Available For on-orbit calibration of the Beijing-1 multispectral imagers (Beijing-1/MS, a field calibration campaign was performed at the Dunhuang calibration site during September and October of 2008. Based on the in situ data and images from Beijing-1 and Terra/Moderate Resolution Imaging Spectroradiometer (MODIS, three vicarious calibration methods (i.e., reflectance-based, irradiance-based, and cross-calibration were used to calculate the top-of-atmosphere (TOA radiance of Beijing-1. An analysis was then performed to determine or identify systematic and accidental errors, and the overall uncertainty was assessed for each individual method. The findings show that the reflectance-based method has an uncertainty of more than 10% if the aerosol optical depth (AOD exceeds 0.2. The cross-calibration method is able to reach an error level within 7% if the images are selected carefully. The final calibration coefficients were derived from the irradiance-based data for 6 September 2008, with an uncertainty estimated to be less than 5%.

  4. Satellite-based RAR performance simulation for measuring directional ocean wave spectrum based on SAR inversion spectrum

    Institute of Scientific and Technical Information of China (English)

    REN Lin; MAO Zhihua; HUANG Haiqing; GONG Fang

    2010-01-01

    Some missions have been carried out to measure wave directional spectrum by synthetic aperture radar (SAR) and airborne real aperture radar (RAR) at a low incidence. Both them have their own advantages and limitations. Scientists hope that SAR and satellite-based RAR can complement each other for the research on wave properties in the future. For this study, the authors aim to simulate the satellite-based RAR system to validate performance for measuring the directional wave spectrum. The principal measurements are introduced and the simulation methods based on the one developed by Hauser are adopted and slightly modified. To enhance the authenticity of input spectrum and the wave spectrum measuring consistency for SAR and satellite-based RAR, the wave height spectrum inversed from Envisat ASAR data by cross spectrum technology is used as the input spectrum of the simulation system. In the process of simulation, the sea surface, backscattering signal, modulation spectrum and the estimated wave height spectrum are simulated in each look direction. Directional wave spectrum are measured based on the simulated observations from 0° to 360~. From the estimated wave spectrum, it has an 180° ambiguity like SAR, but it has no special high wave number cut off in all the direction. Finally, the estimated spectrum is compared with the input one in terms of the dominant wave wavelength, direction and SWH and the results are promising. The simulation shows that satellite-based RAR should be capable of measuring the directional wave properties. Moreover, it indicates satellite-based RAR basically can measure waves that SAR can measure.

  5. Multiangle Bistatic SAR Imaging and Fusion Based on BeiDou-2 Navigation Satellite System

    Directory of Open Access Journals (Sweden)

    Zeng Tao

    2015-01-01

    Full Text Available Bistatic Synthetic Aperture Radar (BSAR based on the Global Navigation Service System (GNSSBSAR uses navigation satellites as radar transmitters, which are low in cost. However, GNSS-BSAR images have poor resolution and low Signal-to-Noise Ratios (SNR. In this paper, a multiangle observation and data processing strategy are presented based on BeiDou-2 navigation satellite imagery, from which twenty-six BSAR images in different configurations are obtained. A region-based fusion algorithm using region of interest segmentation is proposed, and a high-quality fusion image is obtained. The results reveal that the multiangle imaging method can extend the applications of GNSS-BSAR.

  6. BeiDou satellite's differential code biases estimation based on uncombined precise point positioning with triple-frequency observable

    Science.gov (United States)

    Fan, Lei; Li, Min; Wang, Cheng; Shi, Chuang

    2017-02-01

    The differential code bias (DCB) of BeiDou satellite is an important topic to make better use of BeiDou system (BDS) for many practical applications. This paper proposes a new method to estimate the BDS satellite DCBs based on triple-frequency uncombined precise point positioning (UPPP). A general model of both triple-frequency UPPP and Geometry-Free linear combination of Phase-Smoothed Range (GFPSR) is presented, in which, the ionospheric observable and the combination of triple-frequency satellite and receiver DCBs (TF-SRDCBs) are derived. Then the satellite and receiver DCBs (SRDCBs) are estimated together with the ionospheric delay that is modeled at each individual station in a weighted least-squares estimator, and the satellite DCBs are determined by introducing the zero-mean condition of all available BDS satellites. To validate the new method, 90 day's real tracking GNSS data (from January to March in 2014) collected from 9 Multi-GNSS Experiment (MGEX) stations (equipped with Trimble NETR9 receiver) is used, and the BDS satellite DCB products from German Aerospace Center (DLR) are taken as reference values for comparison. Results show that the proposed method is able to precisely estimate BDS satellite DCBs: (1) the mean value of the day-to-day scattering for all available BDS satellites is about 0.24 ns, which is reduced in average by 23% when compared with the results derived by only GFPSR. Moreover, the mean value of the day-to-day scattering of IGSO satellites is lower than that of GEO and MEO satellites; (2) the mean value of RMS of the difference with respect to DLR DCB products is about 0.39 ns, which is improved by an average of 11% when compared with the results derived by only GFPSR. Besides, the RMS of IGSO and MEO satellites is at the same level which is better than that of GEO satellites.

  7. Formulation of geopotential difference determination using optical-atomic clocks onboard satellites and on ground based on Doppler cancellation system

    Science.gov (United States)

    Shen, Ziyu; Shen, Wen-Bin; Zhang, Shuangxi

    2016-08-01

    In this study, we propose an approach for determining the geopotential difference using high-frequency-stability microwave links between satellite and ground station based on Doppler cancellation system. Suppose a satellite and a ground station are equipped with precise optical-atomic clocks (OACs) and oscillators. The ground oscillator emits a signal with frequency fa towards the satellite and the satellite receiver (connected with the satellite oscillator) receives this signal with frequency fb which contains the gravitational frequency shift effect and other signals and noises. After receiving this signal, the satellite oscillator transmits and emits, respectively, two signals with frequencies fb and fc towards the ground station. Via Doppler cancellation technique, the geopotential difference between the satellite and the ground station can be determined based on gravitational frequency shift equation by a combination of these three frequencies. For arbitrary two stations on ground, based on similar procedures as described above, we may determine the geopotential difference between these two stations via a satellite. Our analysis shows that the accuracy can reach 1 m2 s- 2 based on the clocks' inaccuracy of about 10-17 (s s-1) level. Since OACs with instability around 10-18 in several hours and inaccuracy around 10-18 level have been generated in laboratory, the proposed approach may have prospective applications in geoscience, and especially, based on this approach a unified world height system could be realized with one-centimetre level accuracy in the near future.

  8. Integration between terrestrial-based and satellite-based land mobile communications systems

    Science.gov (United States)

    Arcidiancono, Antonio

    A survey is given of several approaches to improving the performance and marketability of mobile satellite systems (MSS). The provision of voice/data services in the future regional European Land Mobile Satellite System (LMSS), network integration between the Digital Cellular Mobile System (GSM) and LMSS, the identification of critical areas for the implementation of integrated GSM/LMSS areas, space segment scenarios, LMSS for digital trunked private mobile radio (PMR) services, and code division multiple access (CDMA) techniques for a terrestrial/satellite system are covered.

  9. Integration between terrestrial-based and satellite-based land mobile communications systems

    Science.gov (United States)

    Arcidiancono, Antonio

    1990-01-01

    A survey is given of several approaches to improving the performance and marketability of mobile satellite systems (MSS). The provision of voice/data services in the future regional European Land Mobile Satellite System (LMSS), network integration between the Digital Cellular Mobile System (GSM) and LMSS, the identification of critical areas for the implementation of integrated GSM/LMSS areas, space segment scenarios, LMSS for digital trunked private mobile radio (PMR) services, and code division multiple access (CDMA) techniques for a terrestrial/satellite system are covered.

  10. Satellite-based phenology detection in broadleaf forests in South-Western Germany

    Science.gov (United States)

    Misra, Gourav; Buras, Allan; Menzel, Annette

    2016-04-01

    Many techniques exist for extracting phenological information from time series of satellite data. However, there have been only a few successful attempts to temporarily match satellite-derived observations with ground based phenological observations (Fisher et al., 2006; Hamunyela et al., 2013; Galiano et al., 2015). Such studies are primarily plagued with problems relating to shorter time series of satellite data including spatial and temporal resolution issues. A great challenge is to correlate spatially continuous and pixel-based satellite information with spatially discontinuous and point-based, mostly species-specific, ground observations of phenology. Moreover, the minute differences in phenology observed by ground volunteers might not be sufficient to produce changes in satellite-measured reflectance of vegetation, which also exposes the difference in the definitions of phenology (Badeck et al., 2004; White et al., 2014). In this study Start of Season (SOS) was determined for broadleaf forests at a site in south-western Germany using MODIS-sensor time series of Normalised Difference Vegetation Index (NDVI) data for the years covering 2001 to 2013. The NDVI time series raster data was masked for broadleaf forests using Corine Land Cover dataset, filtered and corrected for snow and cloud contaminations, smoothed with a Gaussian filter and interpolated to daily values. Several SOS techniques cited in literature, namely thresholds of amplitudes (20%, 50%, 60% and 75%), rates of change (1st, 2nd and 3rd derivative) and delayed moving average (DMA) were tested for determination of satellite SOS. The different satellite SOS were then compared with a species-rich ground based phenology information (e.g. understory leaf unfolding, broad leaf unfolding and greening of evergreen tree species). Working with all the pixels at a finer resolution, it is seen that the temporal trends in understory and broad leaf species are well captured. Initial analyses show promising

  11. Quality assessment of butter cookies applying multispectral imaging

    Science.gov (United States)

    Andresen, Mette S; Dissing, Bjørn S; Løje, Hanne

    2013-01-01

    A method for characterization of butter cookie quality by assessing the surface browning and water content using multispectral images is presented. Based on evaluations of the browning of butter cookies, cookies were manually divided into groups. From this categorization, reference values were calculated for a statistical prediction model correlating multispectral images with a browning score. The browning score is calculated as a function of oven temperature and baking time. It is presented as a quadratic response surface. The investigated process window was the intervals 4–16 min and 160–200°C in a forced convection electrically heated oven. In addition to the browning score, a model for predicting the average water content based on the same images is presented. This shows how multispectral images of butter cookies may be used for the assessment of different quality parameters. Statistical analysis showed that the most significant wavelengths for browning predictions were in the interval 400–700 nm and the wavelengths significant for water prediction were primarily located in the near-infrared spectrum. The water prediction model was found to correctly estimate the average water content with an absolute error of 0.22%. From the images it was also possible to follow the browning and drying propagation from the cookie edge toward the center. PMID:24804036

  12. Multispectral tissue analysis and classification towards enabling automated robotic surgery

    Science.gov (United States)

    Triana, Brian; Cha, Jaepyeong; Shademan, Azad; Krieger, Axel; Kang, Jin U.; Kim, Peter C. W.

    2014-02-01

    Accurate optical characterization of different tissue types is an important tool for potentially guiding surgeons and enabling automated robotic surgery. Multispectral imaging and analysis have been used in the literature to detect spectral variations in tissue reflectance that may be visible to the naked eye. Using this technique, hidden structures can be visualized and analyzed for effective tissue classification. Here, we investigated the feasibility of automated tissue classification using multispectral tissue analysis. Broadband reflectance spectra (200-1050 nm) were collected from nine different ex vivo porcine tissues types using an optical fiber-probe based spectrometer system. We created a mathematical model to train and distinguish different tissue types based upon analysis of the observed spectra using total principal component regression (TPCR). Compared to other reported methods, our technique is computationally inexpensive and suitable for real-time implementation. Each of the 92 spectra was cross-referenced against the nine tissue types. Preliminary results show a mean detection rate of 91.3%, with detection rates of 100% and 70.0% (inner and outer kidney), 100% and 100% (inner and outer liver), 100% (outer stomach), and 90.9%, 100%, 70.0%, 85.7% (four different inner stomach areas, respectively). We conclude that automated tissue differentiation using our multispectral tissue analysis method is feasible in multiple ex vivo tissue specimens. Although measurements were performed using ex vivo tissues, these results suggest that real-time, in vivo tissue identification during surgery may be possible.

  13. Code-excited linear predictive coding of multispectral MR images

    Science.gov (United States)

    Hu, Jian-Hong; Wang, Yao; Cahill, Patrick

    1996-02-01

    This paper reports a multispectral code excited linear predictive coding method for the compression of well-registered multispectral MR images. Different linear prediction models and the adaptation schemes have been compared. The method which uses forward adaptive autoregressive (AR) model has proven to achieve a good compromise between performance, complexity and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over non-overlapping square macroblocks. Each macro-block is further divided into several micro-blocks and, the best excitation signals for each microblock are determined through an analysis-by-synthesis procedure. To satisfy the high quality requirement for medical images, the error between the original images and the synthesized ones are further specified using a vector quantizer. The MFCELP method has been applied to 26 sets of clinical MR neuro images (20 slices/set, 3 spectral bands/slice, 256 by 256 pixels/image, 12 bits/pixel). It provides a significant improvement over the discrete cosine transform (DCT) based JPEG method, a wavelet transform based embedded zero-tree wavelet (EZW) coding method, as well as the MSARMA method we developed before.

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

    Directory of Open Access Journals (Sweden)

    Ahmad Chaddad

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

  15. Developing a sustainable satellite-based environmental monitoring system In Nigeria

    Science.gov (United States)

    Akinyede, J. O.; Adepoju, K. A.; Akinluyi, F. O.; Anifowose, A. Y. B.

    2015-10-01

    Increased anthropogenic activities over the year have remained a major factor of the Earth changing environment. This phenomenon has given rise to a number of environmental degraded sites that characterize the Nigeria's landscape. The human-induced elements include gully erosion, mangrove ecosystems degradation, desertification and deforestation, particularly in the south east, Niger Delta, north east and south west of Nigeria respectively, as well as river flooding/flood plain inundation and land degradation around Kainji lake area. Because of little or no effective management measures, the attendant environmental hazards have been extremely damaging to the infrastructures and socio-economic development of the affected area. Hence, a concerted effort, through integrated and space-based research, is being intensified to manage and monitor the environment in order to restore the stability, goods and services of the environment. This has justified Nigeria's investment in its space programme, especially the launch of NigeriaSat-1, an Earth observation micro-satellite in constellation with five (5) other similar satellites, Alsat-1, China DMC, Bilsat-1, DEMOS and UK DMC belonging to Algeria, China, Turkey, Spain and United Kingdom respectively. The use of data from these satellites, particularly NigeriaSat-1, in conjunction with associated technologies has proved to be very useful in understanding the influence of both natural and human activities on the Nigeria's ecosystems and environment. The results of some researches on specific applications of Nigerian satellites are presented in this paper. Appropriate sustainable land and water resources management in the affected areas, based on Nigeria's satellite data capture and integration, are also discussed.

  16. DroughtView: Satellite Based Drought Monitoring and Assessment

    Science.gov (United States)

    Hartfield, K. A.; Van Leeuwen, W. J. D.; Crimmins, M.; Marsh, S. E.; Torrey, Y.; Rahr, M.; Orr, B. J.

    2014-12-01

    Drought is an ever growing concern within the United States and Mexico. Extended periods of below-average precipitation can adversely affect agricultural production and ecosystems, impact local water resources and create conditions prime for wildfire. DroughtView (www.droughtview.arizona.edu) is a new on-line resource for scientists, natural resource managers, and the public that brings a new perspective to remote-sensing based drought impact assessment that is not currently available. DroughtView allows users to monitor the impact of drought on vegetation cover for the entire continental United States and the northern regions of Mexico. As a spatially and temporally dynamic geospatial decision support tool, DroughtView is an excellent educational introduction to the relationship between remotely sensed vegetation condition and drought. The system serves up Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) data generated from 250 meter 16-day composite Moderate-resolution Imaging Spectroradiometer (MODIS) imagery from 2000 to the present. Calculation of difference from average, previous period and previous year greenness products provide the user with a proxy for drought conditions and insight on the secondary impacts of drought, such as wildfire. The various image products and overlays are served up via the ArcGIS Server platform. DroughtView serves as a useful tool to introduce and teach vegetation time series analysis to those unfamiliar with the science. High spatial resolution imagery is available as a reference layer to locate points of interest, zoom in and export images for implementation in reports and presentations. Animation of vegetation time series allows users to examine ecosystem disturbances and climate data is also available to examine the relationship between precipitation, temperature and vegetation. The tool is mobile friendly allowing users to access the system while in the field. The systems capabilities and

  17. A space weather forecasting system with multiple satellites based on a self-recognizing network.

    Science.gov (United States)

    Tokumitsu, Masahiro; Ishida, Yoshiteru

    2014-05-05

    This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  18. An Attitude Modelling Method Based on the Inherent Frequency of a Satellite Platform

    Science.gov (United States)

    Mo, F.; Tang, X.; Xie, J.; Yan, C.

    2017-05-01

    The accuracy of attitude determination plays a key role in the improvement of surveying and mapping accuracy for high-resolution remote-sensing satellites, and it is a bottleneck in large-scale satellite topographical mapping. As the on-board energy is constrained and the performance of an attitude-measurement device is limited, the attitude acquired is discretely sampled with a settled time interval. The larger the interval, the easier the data transmission, and the more deviation the attitude data will have. Meanwhile, several kinds of jitter frequencies have been detected in satellite platforms. This paper presents a novel attitude modelling (AttModel) method that sufficiently considers the discrete and periodic characteristics, and the attitude model built is continuous and consists of several inherent waves of different frequencies. The process of modelling includes two steps: (a) frequency detection, which uses raw gyroscope data within a period of time to detect the attitude frequencies (as the gyroscope data can actually reflect continuous, very small changes of the satellite platform), and (b) attitude modelling , which processes the attitude data that was filtered by extended Kalman filtering based on general polynomial and trigonometric polynomials, and these trigonometric polynomials are rebuilt by those frequencies detected in the first part of the modelling process. Finally, one experiment designed for verifying the effectiveness of the presented method shows that the AttModel method can reach a slightly better pointing accuracy without ground-control points than traditional attitude-interpolation methods.

  19. 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.

  20. Constellation design for earth observation based on the characteristics of the satellite ground track

    Science.gov (United States)

    Luo, Xin; Wang, Maocai; Dai, Guangming; Song, Zhiming

    2017-04-01

    This paper responds to the increasing need for Earth observation missions and deals with the design of Repeating Sun-Synchronous Constellations (RSSCs) which takes into consideration of constellations composed of one or more orbital planes. Based on the mature design approach of Repeating Sun-synchronous orbits, a novel technique to design RSSCs is presented, which takes the second gravitational zonal harmonic into consideration. In order to obtain regular cycles of observation of the Earth by a single satellite, the orbital relationships have to be satisfied firstly are illustrated. Then, by making full analyses of the characteristics of the satellite ground track, orbital parameters are properly calculated to make other satellites pass on the same or different ground track of the single satellite. Last, single-plane or multi-plane constellations are used to improve the repetitions of the observation and the ground resolution. RSSCs allow observing the same region once at the same local time in a solar day and several times at the different local time in a solar day. Therefore, this kind of constellations meets all requirements for the remote sensing applications, which need to observe the same region under the same or different visible conditions. Through various case studies, the calculation technique is successfully demonstrated.

  1. Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Singaiah Chintalapudi

    2014-05-01

    Full Text Available In this study, seven precipitation products (rain gauges, NEXRAD MPE, PERSIANN 0.25 degree, PERSIANN CCS-3hr, PERSIANN CCS-1hr, TRMM 3B42V7, and CMORPH were used to force a physically-based distributed hydrologic model. The model was driven by these products to simulate the hydrologic response of a 1232 km2 watershed in the Guadalupe River basin, Texas. Storm events in 2007 were used to analyze the precipitation products. Comparison with rain gauge observations reveals that there were significant biases in the satellite rainfall products and large variations in the estimated amounts. The radar basin average precipitation compared very well with the rain gauge product while the gauge-adjusted TRMM 3B42V7 precipitation compared best with observed rainfall among all satellite precipitation products. The NEXRAD MPE simulated streamflows matched the observed ones the best yielding the highest Nash-Sutcliffe Efficiency correlation coefficient values for both the July and August 2007 events. Simulations driven by TRMM 3B42V7 matched the observed streamflow better than other satellite products for both events. The PERSIANN coarse resolution product yielded better runoff results than the higher resolution product. The study reveals that satellite rainfall products are viable alternatives when rain gauge or ground radar observations are sparse or non-existent.

  2. Assessment of the quality of OSIRIS mesospheric temperatures using satellite and ground-based measurements

    Directory of Open Access Journals (Sweden)

    P. E. Sheese

    2012-12-01

    Full Text Available The Optical Spectrograph and InfraRed Imaging System (OSIRIS on the Odin satellite is currently in its 12th year of observing the Earth's limb. For the first time, continuous temperature profiles extending from the stratopause to the upper mesosphere have been derived from OSIRIS measurements of Rayleigh-scattered sunlight. Through most of the mesosphere, OSIRIS temperatures are in good agreement with coincident temperature profiles derived from other satellite and ground-based measurements. In the altitude region of 55–80 km, OSIRIS temperatures are typically within 4–5 K of those from the SABER, ACE-FTS, and SOFIE instruments on the TIMED, SciSat-I, and AIM satellites, respectively. The mean differences between individual OSIRIS profiles and those of the other satellite instruments are typically within the combined uncertainties and previously reported biases. OSIRIS temperatures are typically within 2 K of those from the University of Western Ontario's Purple Crow Lidar in the altitude region of 52–79 km, where the mean differences are within combined uncertainties. Near 84 km, OSIRIS temperatures exhibit a cold bias of 10–15 K, which is due to a cold bias in OSIRIS O2 A-band temperatures at 85 km, the upper boundary of the Rayleigh-scatter derived temperatures; and near 48 km OSIRIS temperatures exhibit a cold bias of 5–15 K, which is likely due to multiple-scatter effects that are not taken into account in the retrieval.

  3. A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

    Directory of Open Access Journals (Sweden)

    Masahiro Tokumitsu

    2014-05-01

    Full Text Available This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV. The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  4. Detecting aircrafts from satellite images using saliency and conical pyramid based template representation

    Indian Academy of Sciences (India)

    SAMIK BANERJEE; NITIN GUPTA; SUKHENDU DAS; PINAKI ROY CHOWDHURY; L K SINHA

    2016-10-01

    Automatic target localization in satellite images still remains as a challenging problem in the field of computer vision. The issues involved in locating targets in satellite images are viewpoint, spectral (intensity) and scale variations. Diversity in background texture and target clutter also adds up to the complexity of the problem of localizing aircrafts in satellite images. Failure of modern feature extraction and object detection methods highlight the complexity of the problem. In the proposed work, pre-processing techniques, viz.denoising and contrast enhancement, are first used to improve the quality of the images. Then, the concept of unsupervised saliency is used to detect the potential regions of interest, which reduces the search space. Parts from the salient regions are further processed using clustering and morphological processing to get the probable regions of isolated aircraft targets. Finally, a novel conical pyramid based framework for template representation of the target samples is proposed for matching. Experimental results shown on a few satellite images exhibit the superior performance of the proposed methods.

  5. The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

    Science.gov (United States)

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

    2017-04-01

    We present a summary and some first results of 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 satellite instruments, 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. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse

  6. Assessing satellite AOD based and WRF/CMAQ output PM2.5 estimators

    Science.gov (United States)

    Cordero, Lina; Wu, Yonghua; Gross, Barry M.; Moshary, Fred

    2013-05-01

    Fine particulate matter measurements (PM2.5) are essential for air quality monitoring and related public health; however, the shortage of reliable measurmennts constrains researchers to use other means for obtaining reliable estimates over large scales. In particular, model forecasters and satellite community use their respective products to develop ground particulate matter estimations but few experiments have explored how the remote sensing approaches compare to the high resolution models. . In this paper we focus on studying the performance of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Geostationary Operational Environmental Satellites (GOES) regression based estimates in comparison to more direct bias corrected outputs from the Community Multiscale Air Quality (CMAQ) model, We use a two-year dataset (2005-2006) and apply urban, season and hour filters to illustrate the agreement between estimated and in-situ measured fine particulate matter from the New York State Department of Environmental Conservation (NYSDEC). We first begin by analyzing the correspondence between ground aerosol optical depth (AOD) measurements from an AERONET (AErosol RObotic NETwork) Cimel sun/sky radiometer with both satellite and model products in one urban location; we show that satellite readings perform better than model outputs, especially during the summer (RMODIS>=0.65, RCMAQ>=0.37). This is a clear symptom of the difficulty in the models to properly model realistic optical properties. We then turn to a direct assessment of PM2.5 presenting individual comparisons between ground PM2.5 measurements with satellite/model predictions and demonstrate the higher accuracy from model estimations (RurbanMODIS >= 0.74, RurbanCMAQ >= 0.77; Rnon-urbanMODIS >= 0.48, Rnon-urbanCMAQ >= 0.78). In general, we find that the bias corrected CMAQ estimates are superior to satellite based estimators except at very high resolution. Finally, we show that when using both model and

  7. A Better Method for SAR Image and Multi-Spectral Image Fusion Based on Nonsubsampled Contourlet Transform (NSCT) and Genetic Algorithm%基于NSCT和遗传算法的SAR图像和多光谱图像融合

    Institute of Scientific and Technical Information of China (English)

    时丕丽; 郭雷; 李晖晖; 杨宁; 陈智慧

    2012-01-01

    SAR image or multispectral image has big difference in imaging mechanism and spectral characteristics. Sections 1 and 2 of the full paper explain our image fusion method mentioned in the title, which we believe is new and better than previous ones. Their cpre consists of : (1) by using the multi-scale, multi-direction ad spare decomposition capability of the NSCT, we transform the SAR and multispectral source images into NSCT domain; (2) we fuse the low frequencey coefficients by maximizing the regional entropy; then we calculate the values of the high-frequence subband regional correlation coefficients, divide them into different ranges according to the threshold values selected by genetic algorithm and fuse the correlation coefficients in different ranges, ( 3) we take the inverse NSCT transform, thus obtatining the fused images. Section 3 simulates our image fusion method; the simulation results , given in Fig. 4 and Table 1, and their analysis show preliminarily that our image fusion method performs indeed much better than the exsiting regional-based/pixel-based Contourlet/NSCT.%合成孔径雷达(SAR)图像与多光谱图像成像机理和光谱特性差异较大,一般的融合方法很难取得满意的融合结果.文章提出了一种基于Nonsuosampled Contourlet transform(NSCT)和遗传算法的融合算法,首先将经过预处理后的图像进行NSCT分解,低频系数采取区域信息熵最大的准则融合;高频子带计算区域相关性,对相关性在不同阈值范围内的系数进行融合,阈值的选取采用遗传算法进行搜索;最后对融合系数进行NSCT逆变换,得到融合结果.仿真结果表明该算法显著优于基于像素点和基于区域的融合方法.

  8. Calibration for Relative Interior Orientation Relationship and Band-to-band Registration with High Accuracy of ZY-3 Multi-spectral Image

    Directory of Open Access Journals (Sweden)

    LI Qijun

    2016-06-01

    Full Text Available Using high accuracy match points extracted between the multi-spectral images that obtained at the same time,a position model of the CCD chips of the ZY-3 multi-spectral camera was proposed. Relative interior orientation relationship parameters were calculated and accurate band-to-band automatic registration of ZY-3 multi-spectral image was achieved based on the position model. The experimental result indicates that the band-to-band automatic registration accuracy of ZY-3 multi-spectral image is better than 0.3 pixels with the proposed method.

  9. A Positioning System based on Communication Satellites and the Chinese Area Positioning System (CAPS)

    Science.gov (United States)

    Ai, Guo-Xiang; Shi, Hu-Li; Wu, Hai-Tao; Yan, Yi-Hua; Bian, Yu-Jing; Hu, Yong-Hui; Li, Zhi-Gang; Guo, Ji; Xian-DeCai

    2008-12-01

    The Chinese Area Positioning System (CAPS) is a positioning system based on satellite communication that is fundamentally different from the 3``G'' (GPS, GLONASS and GALILEO) systems. The latter use special-purpose navigation satellites to broadcast navigation information generated on-board to users, while the CAPS transfers ground-generated navigation information to users via the communication satellite. In order to achieve accurate Positioning, Velocity and Time (PVT), the CAPS employs the following strategies to overcome the three main obstacles caused by using the communication satellite: (a) by real-time following-up frequency stabilization to achieve stable frequency; (b) by using a single carrier in the transponder with 36 MHz band-width to gain sufficient power; (c) by incorporating Decommissioned Geostationary Orbit communication satellite (DGEO), barometric pressure and Inclined Geostationary Orbit communication satellite (IGSO) to achieve the 3-D positioning. Furthermore, the abundant transponders available on DGEO can be used to realize the large capacity of communication as well as the integrated navigation and communication. With the communication functions incorporated, five new functions appear in the CAPS: (1) combination of navigation and communication; (2) combination of navigation and high accuracy orbit measurement; (3) combination of navigation message and wide/local area differential processing; (4) combination of the switching of satellites, frequencies and codes; and (5) combination of the navigation message and the barometric altimetry. The CAPS is thereby labelled a PVT5C system of high accuracy. In order to validate the working principle and the performance of the CAPS, a trial system was established in the course of two years at a cost of about 20 million dollars. The trial constellation consists of two GEO satellites located at E87.5° and E110.5°, two DGEOs located at E130° and E142°, as well as barometric altimetry as a virtual

  10. A Positioning System based on Communication Satellites and the Chinese Area Positioning System (CAPS)

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The Chinese Area Positioning System (CAPS) is a positioning system based on satellite communication that is fundamentally different from the 3"G" (GPS, GLONASS and GALILEO) systems. The latter use special-purpose navigation satellites to broadcast navi-gation information generated on-board to users, while the CAPS transfers ground-generated navigation information to users via the communication satellite. In order to achieve accurate Positioning, Velocity and Time (PVT), the CAPS employs the following strategies to over-come the three main obstacles caused by using the communication satellite: (a) by real-time following-up frequency stabilization to achieve stable frequency; (b) by using a single carrier in the transponder with 36 MHz band-width to gain sufficient power; (c) by incorporating Decommissioned Geostationary Orbit communication satellite (DGEO), barometric pressure and Inclined Geostationary Orbit communication satellite (IGSO) to achieve the 3-D posi-tioning. Furthermore, the abundant transponders available on DGEO can be used to realize the large capacity of communication as well as the integrated navigation and communication. With the communication functions incorporated, five new functions appear in the CAPS: (1) combination of navigation and communication; (2) combination of navigation and high accu-racy orbit measurement; (3) combination of navigation message and wide/local area differen-tial processing; (4) combination of the switching of satellites, frequencies and codes; and (5) combination of the navigation message and the barometric altimetry. The CAPS is thereby labelled a PVT5C system of high accuracy. In order to validate the working principle and the performance of the CAPS, a trial system was established in the course of two years at a cost of about 20 million dollars. The trial constellation consists of two GEO satellites located at E87.5°and E110.5°, two DGEOs located at E130° and E142°, as well as barometric altimetry as a virtual

  11. Satellite single-axis attitude determination based on Automatic Dependent Surveillance - Broadcast signals

    Science.gov (United States)

    Zhou, Kaixing; Sun, Xiucong; Huang, Hai; Wang, Xinsheng; Ren, Guangwei

    2017-10-01

    The space-based Automatic Dependent Surveillance - Broadcast (ADS-B) is a new technology for air traffic management. The satellite equipped with spaceborne ADS-B system receives the broadcast signals from aircraft and transfers the message to ground stations, so as to extend the coverage area of terrestrial-based ADS-B. In this work, a novel satellite single-axis attitude determination solution based on the ADS-B receiving system is proposed. This solution utilizes the signal-to-noise ratio (SNR) measurement of the broadcast signals from aircraft to determine the boresight orientation of the ADS-B receiving antenna fixed on the satellite. The basic principle of this solution is described. The feasibility study of this new attitude determination solution is implemented, including the link budget and the access analysis. On this basis, the nonlinear least squares estimation based on the Levenberg-Marquardt method is applied to estimate the single-axis orientation. A full digital simulation has been carried out to verify the effectiveness and performance of this solution. Finally, the corresponding results are processed and presented minutely.

  12. Satellite-based climate information within the WMO RA VI Regional Climate Centre on Climate Monitoring

    Science.gov (United States)

    Obregón, A.; Nitsche, H.; Körber, M.; Kreis, A.; Bissolli, P.; Friedrich, K.; Rösner, S.

    2014-05-01

    The World Meteorological Organization (WMO) established Regional Climate Centres (RCCs) around the world to create science-based climate information on a regional scale within the Global Framework for Climate Services (GFCS). The paper introduces the satellite component of the WMO Regional Climate Centre on Climate Monitoring (RCC-CM) for Europe and the Middle East. The RCC-CM product portfolio is based on essential climate variables (ECVs) as defined by the Global Climate Observing System (GCOS), spanning the atmospheric (radiation, clouds, water vapour) and terrestrial domains (snow cover, soil moisture). In the first part, the input data sets are briefly described, which are provided by the EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) Satellite Application Facilities (SAF), in particular CM SAF, and by the ESA (European Space Agency) Climate Change Initiative (CCI). In the second part, the derived RCC-CM products are presented, which are divided into two groups: (i) operational monitoring products (e.g. monthly means and anomalies) based on near-real-time environmental data records (EDRs) and (ii) climate information records (e.g. climatologies, time series, trend maps) based on long-term thematic climate data records (TCDRs) with adequate stability, accuracy and homogeneity. The products are provided as maps, statistical plots and gridded data, which are made available through the RCC-CM website (www.dwd.de/rcc-cm).

  13. Satellite-based monitoring of particulate matter pollution at very high resolution: the HOTBAR method

    Science.gov (United States)

    Wilson, Robin; Milton, Edward; Nield, Joanna

    2016-04-01

    Particulate matter air pollution is a major health risk, and is responsible for millions of premature deaths each year. Concentrations tend to be highest in urban areas - particularly in the mega-cities of rapidly industrialising countries, where there are limited ground monitoring networks. Satellite-based monitoring has been used for many years to assess regional-scale trends in air quality, but currently available satellite products produce data at 1-10km resolution: too coarse to discern the small-scale patterns of sources and sinks seen in urban areas. Higher-resolution satellite products are required to provide accurate assessments of particulate matter concentrations in these areas, and to allow analysis of localised air quality effects on health. The Haze Optimized Transform-based Aerosol Retrieval (HOTBAR) method is a novel method which provides estimates of PM2.5 concentrations from high-resolution (approximately 30m) satellite imagery. This method is designed to work over a wide range of land covers and performs well over the complex land-cover mosaic found in urban areas. It requires only standard visible and near-infrared data, making it applicable to a range of data from sensors such as Landsat, SPOT and Sentinel-2. The method is based upon an extension of the Haze Optimized Transform (HOT), which was originally designed for assessing areas of thick haze in satellite imagery. This was done by calculating a 'haziness' value for each pixel in an image as the distance from a 'Clear Line' in feature space, defined by the high correlation between visible bands. Here, we adapt the HOT method and use it to estimate Aerosol Optical Thickness (a measure of the column-integrated haziness of the atmosphere) instead, from which PM2.5 concentrations can then be estimated. Significant extensions to the original HOT method include Monte Carlo estimation of the 'Clear Line', object-based correction for land cover, and estimation of AOT from the haziness values

  14. Multivariate alteration detection (MAD) in multispectral, bi-temporal image data: A new approach to change detction studies

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Conradsen, Knut

    for the definition of the MAD transformation is proven. As opposed to traditional univariate change detection schemes our scheme transforms two sets of multivariate observations (e.g. two multispectral satellite images covering the same geographical area acquired at different points in time) into a difference......-processing introduces a new spatial element into our change detection scheme which is highly relevant for image data. Two case studies using multispectral SPOT HRV data from 5 February 1987 and 12 February 1989 covering coffee and pineapple plantations in central Kenya, and Landsat TM data from 6 June 1986 and 27 June...

  15. Error analysis for satellite gravity field determination based on two-dimensional Fourier methods

    CERN Document Server

    Cai, Lin; Hsu, Houtse; Gao, Fang; Zhu, Zhu; Luo, Jun

    2012-01-01

    The time-wise and space-wise approaches are generally applied to data processing and error analysis for satellite gravimetry missions. But both the approaches, which are based on least-squares collocation, address the whole effect of measurement errors and estimate the resolution of gravity field models mainly from a numerical point of indirect view. Moreover, requirement for higher accuracy and resolution gravity field models could make the computation more difficult, and serious numerical instabilities arise. In order to overcome the problems, this study focuses on constructing a direct relationship between power spectral density of the satellite gravimetry measurements and coefficients of the Earth's gravity potential. Based on two-dimensional Fourier transform, the relationship is analytically concluded. By taking advantage of the analytical expression, it is efficient and distinct for parameter estimation and error analysis of missions. From the relationship and the simulations, it is analytically confir...

  16. Coherent receiving efficiency in satellite-ground coherent laser communication system based on analysis of polarization

    Science.gov (United States)

    Hao, Shiqi; Zhang, Dai; Zhao, Qingsong; Wang, Lei; Zhao, Qi

    2017-06-01

    Aimed at analyzing the coherent receiving efficiency of a satellite-ground coherent laser communication system, polarization state of the received light is analyzed. We choose the circularly polarized, partially coherent laser as transmitted light source. The analysis process includes 3 parts. Firstly, an theoretical model to analyze received light's polarization state is constructed based on Gaussian-Schell model (GSM) and cross spectral density function matrix. Then, analytic formulas to calculate coherent receiving efficiency are derived in which both initial ellipticity modification and deflection angle between polarization axes of the received light and the intrinsic light are considered. At last, numerical simulations are operated based on our study. The research findings investigate variations of polarization state and obtain analytic formulas to calculate the coherent receiving efficiency. Our study has theoretical guiding significances in construction and optimization of satellite-ground coherent laser communication system.

  17. Multiagent Attitude Control System for Satellites Based in Momentum Wheels and Event-Driven Synchronization

    Science.gov (United States)

    Garcia, Juan L.; Moreno, Jose Sanchez

    2012-12-01

    Attitude control is a requirement always present in spacecraft design. Several kinds of actuators exist to accomplish this control, being momentum wheels one of the most employed. Usually satellites carry redundant momentum wheels to handle any possible single failure, but the controller remains as a single centralized element, posing problems in case of failures. In this work a decentralized agent-based event-driven algorithm for attitude control is presented as a possible solution. Several agents based in momentum wheels will interact among them to accomplish the satellite control. A simulation environment has been developed to analyze the behavior of this architecture. This environment has been made available through the web page http://www.dia.uned.es.

  18. Massive information sharing among global data centers based on satellite laser communication

    Science.gov (United States)

    Yi, Longteng; Li, Cong; Liu, Naijin

    2015-10-01

    With the development of big data and information globalization, the requirements of massive information transmitting and sharing among data centers are expanding, especially among those data centers which are extremely far away from each other. In the above field, conventional optical fiber transmission faces many problems such as complex networking, poor security, long node switching delay, high lease and maintain cost and low migration flexibility. Besides, in the near future, data centers may tend to be built in the remote Polar Regions or on the sea for natural cooling. For the above situation, sharing the massive information among global data centers based on satellite laser communication is proposed in this paper. This proposal includes advantage analysis, research of restraining atmosphere interference, etc. At last, by comparison with conventional technology, the research result shows that massive information transmitting and sharing among global data centers based on satellite laser communication has far reaching application potential.

  19. Environmental Testing Philosophy for a Sandia National Laboratories' Small Satellite Project - A Retrospective

    Energy Technology Data Exchange (ETDEWEB)

    CAP,JEROME S.

    2000-08-24

    Sandia has recently completed the flight certification test series for the Multi-Spectral Thermal Imaging satellite (MTI), which is a small satellite for which Sandia was the system integrator. A paper was presented at the 16th Aerospace Testing Seminar discussing plans for performing the structural dynamics certification program for that satellite. The testing philosophy was originally based on a combination of system level vibroacoustic tests and component level shock and vibration tests. However, the plans evolved to include computational analyses using both Finite Element Analysis and Statistical Energy Analysis techniques. This paper outlines the final certification process and discuss lessons learned including both things that went well and things that should/could have been done differently.

  20. Optimizing statistical classification accuracy of satellite remotely sensed imagery for supporting fast flood hydrological analysis

    Science.gov (United States)

    Alexakis, Dimitrios; Agapiou, Athos; Hadjimitsis, Diofantos; Retalis, Adrianos

    2012-06-01

    The aim of this study is to improve classification results of multispectral satellite imagery for supporting flood risk assessment analysis in a catchment area in Cyprus. For this purpose, precipitation and ground spectroradiometric data have been collected and analyzed with innovative statistical analysis methods. Samples of regolith and construction material were in situ collected and examined in the spectroscopy laboratory for their spectral response under consecutive different conditions of humidity. Moreover, reflectance values were extracted from the same targets using Landsat TM/ETM+ images, for drought and humid time periods, using archived meteorological data. The comparison of the results showed that spectral responses for all the specimens were less correlated in cases of substantial humidity, both in laboratory and satellite images. These results were validated with the application of different classification algorithms (ISODATA, maximum likelihood, object based, maximum entropy) to satellite images acquired during time period when precipitation phenomena had been recorded.