Academic literature on the topic 'Aspire 400 satellite data unit'
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Journal articles on the topic "Aspire 400 satellite data unit"
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Wang, Xiang, and Haiyan Jiang. "A 13-Year Global Climatology of Tropical Cyclone Warm-Core Structures from AIRS Data." Monthly Weather Review 147, no. 3 (February 6, 2019): 773–90. http://dx.doi.org/10.1175/mwr-d-18-0276.1.
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Abstract There is uncertainty as to whether the typical warm-core structure of tropical cyclones (TCs) is featured as an upper-level warm core or not. It has been hypothesized that data from the satellite-borne Advanced Microwave Sounding Unit (AMSU) are inadequate to resolve a realistic TC warm-core structure. This study first evaluates 13 years of Atmospheric Infrared Sounder (AIRS) temperature retrieval against recent dropsonde measurements in TCs. AIRS can resolve the TC warm-core structure well, comparable to the dropsonde observations, although the AMSU-A retrievals fail to do so. Using 13-yr AIRS data in global TCs, a global climatology of the TC warm-core structure is generated in this study. The typical warm-core height is at the upper level around 300–400 hPa for all TCs and increases with TC intensity: 400 hPa (~8 km) for tropical storms, 300 hPa (~10 km) for category 1–3 hurricanes, 250–300 hPa (~10–11 km) for category 4 hurricanes, and 150 hPa (~14 km) for category 5 hurricanes. The range of warm-core height varies with TC intensity as well. A strong correlation between TC intensity and warm-core strength is found. A weaker but still significant correlation between TC intensity and warm-core height is also found.
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Ray, S. S. "EXPLORING MACHINE LEARNING CLASSIFICATION ALGORITHMS FOR CROP CLASSIFICATION USING SENTINEL 2 DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W6 (July 26, 2019): 573–78. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w6-573-2019.
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<p><strong>Abstract.</strong> Crop Classification and recognition is a very important application of Remote Sensing. In the last few years, Machine learning classification techniques have been emerging for crop classification. Google Earth Engine (GEE) is a platform to explore the multiple satellite data with different advanced classification techniques without even downloading the satellite data. The main objective of this study is to explore the ability of different machine learning classification techniques like, Random Forest (RF), Classification And Regression Trees (CART) and Support Vector Machine (SVM) for crop classification. High Resolution optical data, Sentinel-2, MSI (10&thinsp;m) was used for crop classification in the Indian Agricultural Research Institute (IARI) farm for the Rabi season 2016 for major crops. Around 100 crop fields (~400 Hectare) in IARI were analysed. Smart phone-based ground truth data were collected. The best cloud free image of Sentinel 2 MSI data (5 Feb 2016) was used for classification using automatic filtering by percentage cloud cover property using the GEE. Polygons as feature space was used as training data sets based on the ground truth data for crop classification using machine learning techniques. Post classification, accuracy assessment analysis was done through the generation of the confusion matrix (producer and user accuracy), kappa coefficient and F value. In this study it was found that using GEE through cloud platform, satellite data accessing, filtering and pre-processing of satellite data could be done very efficiently. In terms of overall classification accuracy and kappa coefficient, Random Forest (93.3%, 0.9178) and CART (73.4%, 0.6755) classifiers performed better than SVM (74.3%, 0.6867) classifier. For validation, Field Operation Service Unit (FOSU) division of IARI, data was used and encouraging results were obtained.</p>
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Manfreda, S., T. Lacava, B. Onorati, N. Pergola, M. Di Leo, M. R. Margiotta, and V. Tramutoli. "On the use of AMSU-based products for the description of soil water content at basin scale." Hydrology and Earth System Sciences 15, no. 9 (September 9, 2011): 2839–52. http://dx.doi.org/10.5194/hess-15-2839-2011.
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Abstract. Characterizing the dynamics of soil moisture fields is a key issue in hydrology, offering a strategy to improve our understanding of complex climate-soil-vegetation interactions. Besides in-situ measurements and hydrological models, soil moisture dynamics can be inferred by analyzing data acquired by sensors on board of airborne and/or satellite platforms. In this work, we investigated the use of the National Oceanic and Atmospheric Administration – Advanced Microwave Sounding Unit-A (NOAA-AMSU-A) radiometer for the remote characterization of soil water content. To this aim, a field measurement campaign, lasted about three months (3 March 2010–18 May 2010), was carried out using a portable time-domain reflectometer (TDR) to get soil water content measures over five different locations within an experimental basin of 32.5 km2, located in the South of Italy. In detail, soil moisture measurements were carried out systematically at the times of satellite overpasses, over two square areas of 400 m2, a triangular area of 200 m2 and two transects of 60 and 170 m, respectively. Each monitored site is characterized by different land covers and soil textures, to account for spatial heterogeneity of land surface. Afterwards, a more extensive comparison (i.e. analyzing a 5 yr data time series) was made using soil moisture simulated by a hydrological model. Measured and modeled soil moisture data were compared with two AMSU-based indices: the Surface Wetness Index (SWI) and the Soil Wetness Variation Index (SWVI). Both time series of indices have been filtered by means of an exponential filter to account for the fact that microwave sensors only provide information at the skin surface. This allowed to understand the ability of each satellite-based index to account for soil moisture dynamics and to understand its performances under different conditions. As a general remark, the comparison shows a higher ability of the filtered SWI to describe the general trend of soil moisture, while the SWVI can capture soil moisture variations with a precision that increases at the higher values of SWVI.
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Manfreda, S., T. Lacava, B. Onorati, N. Pergola, M. Di Leo, M. R. Margiotta, and V. Tramutoli. "On the use of AMSU-based products for the description of soil water content at basin scale." Hydrology and Earth System Sciences Discussions 8, no. 3 (May 27, 2011): 5319–53. http://dx.doi.org/10.5194/hessd-8-5319-2011.
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Abstract. Characterizing the dynamics of soil moisture fields is a key issue in hydrology, offering a strategy to improve our understanding of complex climate-soil-vegetation interactions. Apart from in-situ measurements and hydrological models, soil moisture dynamics can be inferred by analyzing data acquired by sensors aboard satellite platforms. In this work, we investigated the use of the National Oceanic and Atmospheric Administration – Advanced Microwave Sounding Unit (NOAA-AMSU) radiometer for the remote characterization of soil water content. To this aim, a field measurement campaign, lasted about three months, was carried out using a portable time-domain reflectometer (TDR) to get soil water content measures over five different locations within an experimental basin of 32.5 km2, located in the South of Italy. In detail, soil moisture measurements have been carried out systematically at the times of satellite overpasses, over two square areas of 400 m2, a triangular area of 200 m2 and two transects of 60 and 170 m, respectively. Each monitored site is characterized by different land covers and soil textures, to account for spatial heterogeneity of land surface. Afterwards, a more extensive comparison (i.e. analyzing a 5-yr data time series) has been made using soil moisture simulated by a hydrological model. Achieved measured and modeled soil moisture data were compared with two AMSU-based indices: the Surface Wetness Index (SWI) and the Soil Wetness Variation Index (SWVI). Both indices have been filtered to account for soil depth by means of an exponential filter. This allowed to understand the ability of each satellite-based index to account for soil moisture dynamics and to understand its performances under different conditions. As a general remark, the comparison shows a higher ability of the filtered SWI to describe the state of the soil, while the SWVI can capture soil moisture variations with a precision that increases at the higher values of SWVI and it may represent a useful and reliable tool to frequently monitor the soil moisture state for flood forecasting purposes.
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Manns, Hida R., Gary W. Parkin, and Ralph C. Martin. "Evidence of a union between organic carbon and water content in soil." Canadian Journal of Soil Science 96, no. 3 (September 1, 2016): 305–16. http://dx.doi.org/10.1139/cjss-2015-0084.
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Soil organic matter, comprising ∼58% soil organic carbon (SOC), is attributed with increased water holding capacity in the surface horizon of agricultural soil. This paper addresses the role of SOC as a component of a common functional unit in soil from analysis within a single field and over multiple fields. Soil data measured on the fields during the SMAPVEX12 satellite prelaunch algorithm development campaign exhibited high correlation among SOC, field-mean soil water content (SWC), bulk density, and soil texture. The analysis extended over a wide range of soil texture and wetness in the top 5 cm of soil over 50 agricultural fields covering ∼400 km2 of southern Manitoba. Data collected over a much smaller area from Ontario silt loam soils at the Elora Research Centre demonstrated a similar correlation between SOC and SWC in intensive field sampling. This intercorrelation of SOC and SWC is examined with partial least-squares regression, principal component analysis, and geostatistical semivariograms. A model is proposed to interpret the feedback process between SOC and SWC to explain the persistent correlation. Further work to substantiate the strengths and limits of the relationship between SOC and SWC may be beneficial for estimating SWC for remote sensing, agriculture, hydrology, and ecosystem function.
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Zhang, Yan, Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, and Chris McLinden. "Continuation of long-term global SO<sub>2</sub> pollution monitoring from OMI to OMPS." Atmospheric Measurement Techniques 10, no. 4 (April 20, 2017): 1495–509. http://dx.doi.org/10.5194/amt-10-1495-2017.
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Abstract. Over the past 20 years, advances in satellite remote sensing of pollution-relevant species have made space-borne observations an increasingly important part of atmospheric chemistry research and air quality management. This progress has been facilitated by advanced UV–vis spectrometers, such as the Ozone Monitoring Instrument (OMI) on board the NASA Earth Observing System (EOS) Aura satellite, and continues with new instruments, such as the Ozone Mapping and Profiler Suite (OMPS) on board the NASA–NOAA Suomi National Polar-orbiting Partnership (SNPP) satellite. In this study, we demonstrate that it is possible, using our state-of-the-art principal component analysis (PCA) retrieval technique, to continue the long-term global SO2 pollution monitoring started by OMI with the current and future OMPS instruments that will fly on the NOAA Joint Polar Satellite System (JPSS) 1, 2, 3, and 4 satellites in addition to SNPP, with a very good consistency of retrievals from these instruments. Since OMI SO2 data have been primarily used for (1) providing regional context on air pollution and long-range transport on a daily basis and (2) providing information on point emission sources on an annual basis after data averaging, we focused on these two aspects in our OMI–OMPS comparisons. Four years of retrievals (2012–2015) have been compared for three regions: eastern China, Mexico, and South Africa. In general, the comparisons show relatively high correlations (r = 0. 79–0.96) of daily regional averaged SO2 mass between the two instruments and near-unity regression slopes (0.76–0.97). The annual averaged SO2 loading differences between OMI and OMPS are small (< 0.03 Dobson unit (DU) over South Africa and up to 0.1 DU over eastern China). We also found a very good correlation (r = 0. 92–0.97) in the spatial distribution of annual averaged SO2 between OMI and OMPS over the three regions during 2012–2015. The emissions from ∼ 400 SO2 sources calculated with the two instruments also show a very good correlation (r = ∼ 0.9) in each year during 2012–2015. OMPS-detected SO2 point source emissions are slightly lower than those from OMI, but OMI–OMPS differences decrease with increasing strength of source. The OMI–OMPS SO2 mass differences on a pixel by pixel (daily) basis in each region can show substantial differences. The two instruments have a spatial correlation coefficient of 0.7 or better on < ∼ 50 % of the days. It is worth noting that consistent SO2 retrievals were achieved without any explicit adjustments to OMI or OMPS radiance data and that the retrieval agreement may be further improved by introducing a more comprehensive Jacobian lookup table than is currently used.
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Turner, D., A. Lucieer, M. McCabe, S. Parkes, and I. Clarke. "PUSHBROOM HYPERSPECTRAL IMAGING FROM AN UNMANNED AIRCRAFT SYSTEM (UAS) – GEOMETRIC PROCESSINGWORKFLOW AND ACCURACY ASSESSMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 24, 2017): 379–84. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-379-2017.
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In this study, we assess two push broom hyperspectral sensors as carried by small (10–15&thinsp;kg) multi-rotor Unmanned Aircraft Systems (UAS). We used a Headwall Photonics micro-Hyperspec push broom sensor with 324 spectral bands (4–5&thinsp;nm FWHM) and a Headwall Photonics nano-Hyperspec sensor with 270 spectral bands (6&thinsp;nm FWHM) both in the VNIR spectral range (400–1000&thinsp;nm). A gimbal was used to stabilise the sensors in relation to the aircraft flight dynamics, and for the micro-Hyperspec a tightly coupled dual frequency Global Navigation Satellite System (GNSS) receiver, an Inertial Measurement Unit (IMU), and Machine Vision Camera (MVC) were used for attitude and position determination. For the nano-Hyperspec, a navigation grade GNSS system and IMU provided position and attitude data. <br><br> This study presents the geometric results of one flight over a grass oval on which a dense Ground Control Point (GCP) network was deployed. The aim being to ascertain the geometric accuracy achievable with the system. Using the PARGE software package (ReSe – Remote Sensing Applications) we ortho-rectify the push broom hyperspectral image strips and then quantify the accuracy of the ortho-rectification by using the GCPs as check points. <br><br> The orientation (roll, pitch, and yaw) of the sensor is measured by the IMU. Alternatively imagery from a MVC running at 15&thinsp;Hz, with accurate camera position data can be processed with Structure from Motion (SfM) software to obtain an estimated camera orientation. In this study, we look at which of these data sources will yield a flight strip with the highest geometric accuracy.
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Hassan, I., S. M. Antao, and J. B. Parise. "Haüyne: phase transition and high-temperature structures obtained from synchrotron radiation and Rietveld refinements." Mineralogical Magazine 68, no. 3 (June 2004): 499–513. http://dx.doi.org/10.1180/0026461046830201.
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AbstractThe structural behaviour of a haüyne with a chemical composition of Na4.35Ca2.28K0.95[Al6Si6O24]- (SO4)2.03, at room pressure and from 33 to 1035°C on heating, was determined by using in situ synchrotron X-ray powder diffraction data (λ = 0.92249(5) Å). The satellite reflections in haüyne are lost at ∼400°C and a true substructure results because of this phase transition. There is a discontinuity in the a unit-cell parameter at ∼585°C. The α parameter increases rapidly and non-linearly to 585°C, but above 585°C, the expansion rate decreases. The percent volume change between 33 and 576°C is 2.0(3)%, and 0.6(3)% between 593 and 1035°C. Between 33 and 1035°C, the Al–O, Si–O and S–O distances are constant. Between 33 and 576°C, the angle of rotation of the AlO4 tetrahedron, jAl, changesfrom 11.5 to 5.8°, while the angle of rotation of the SiO4 tetrahedron, φSi, changesfrom 12.4 to 6.3°. The Al–O–Si bridging angle changesfrom 150.05(2) to 153.08(1)° from 33 to 576°C. Beyond 585°C, φAl and φSi angles remain nearly constant even though the maximum rotation of the tetrahedra is not achieved. Moreover, the Al–O–Si angle continues to increase at a slower rate from 585 to 1035°C by 1.05(2)°. From 33 to ∼585°C, the K atom position migrates at a slower rate than the Na and Ca atoms, and the structure expands at a high rate. Beyond 585°C, all the atomic positions of the interstitial cations (Na+, K+, Ca2+) remain nearly constant and the expansion of the structure is retarded.
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Tilbury, Larry A., Chris J. Clayton, Tim J. Conroy, Giles Philip, Georgia A. Boyd, Glen A. Johnson, Mark A. Rayfield, Lina Hartanto, and Dane P. Lance. "Pluto—a major gas field hidden beneath the continental slope." APPEA Journal 49, no. 1 (2009): 243. http://dx.doi.org/10.1071/aj08015.
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The Pluto gas field, North West Shelf of Australia, was discovered in April 2005. It is located in production licence area WA-34-L some 190 km northwest of Karratha, and is situated beneath the continental slope in water depths of 400–1,000 m. The seabed topography initially hindered the recognition of this field. The presence of large seabed channels and steep dips in the overburden, together with the variable water depth, result in seismic ray-bending effects which reduce the quality of imaging and attenuate amplitudes over the southern and eastern parts of the field. Consequently the depth conversion of seismic data over the Pluto structure has been a key uncertainty for the field definition. Structurally, the trap is a tilted fault block, bounded on the west and north by major bounding faults, and sealed by overlying regionally extensive shales. The Triassic reservoir sequence dips gently to the east, and subcrops against the regional Jurassic Unconformity. Pluto–1 encountered a gross gas column of around 209 m in Triassic sands of the Mungaroo Formation and Tithonian sands, sealed by Cretaceous shales of the Forestier and Muderong formations. Petrophysical analyses of the conventional wireline dataset confirmed an average net porosity of 28% and average gas saturation of 93% for the Mungaroo Formation (Lower E Unit). Production tests proved the high deliverability of the Mungaroo E Unit (46.5 MMscf/d) but showed the Tithonian section to be of poor deliverability (9.5 MMscf/d with possible in-wellbore leakage from the deeper Mungaroo DST). Since the discovery, five appraisal wells (excluding sidetracks) have been drilled to delineate the accumulation, and to target areas of higher quality sand development for optimisation of development well locations. In addition, the Pluto 3D data has been twice processed to a pre-stack depth migration—once, immediately following the Pluto–1 discovery to aid in the appraisal campaign and then again following final investment decision (FID) to take advantage of new and improved techniques for seismic processing which has led to increased confidence in the proposed development well locations. The Xena gas field, a satellite field adjacent to Pluto, was discovered by Xena-1ST1 in September 2006. Since then a further two appraisal wells have been drilled to delineate the structure and define the accumulation. The Triassic reservoir section has been extensively cored, logged and analysed in detail for reservoir characterisation and correlation. The reservoir is composed of thickly developed, amalgamated fluvial multi-valley sandstones of the Mungaroo Formation, and coastal plain sediments (tidal bars and channels, estuarine beach deposits) of the more tidally influenced Brigadier Formation.
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Kieu, Chanh Q., and Da-Lin Zhang. "Genesis of Tropical Storm Eugene (2005) from Merging Vortices Associated with ITCZ Breakdowns. Part I: Observational and Modeling Analyses." Journal of the Atmospheric Sciences 65, no. 11 (November 1, 2008): 3419–39. http://dx.doi.org/10.1175/2008jas2605.1.
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Abstract Although tropical cyclogenesis occurs over all tropical warm ocean basins, the eastern Pacific appears to have the highest frequency of tropical cyclogenesis events per unit area. In this study, tropical cyclogenesis from merging mesoscale convective vortices (MCVs) associated with breakdowns of the intertropical convergence zone (ITCZ) is examined. This is achieved through a case study of the processes leading to the genesis of Tropical Storm Eugene (2005) over the eastern Pacific using the National Centers for Environmental Prediction reanalysis, satellite data, and 4-day multinested cloud-resolving simulations with the Weather Research and Forecast (WRF) model at the finest grid size of 1.33 km. Observational analyses reveal the initiations of two MCVs on the eastern ends of the ITCZ breakdowns that occurred more than 2 days and 1000 km apart. The WRF model reproduces their different movements, intensity and size changes, and vortex–vortex interaction at nearly the right timing and location at 39 h into the integration as well as the subsequent track and intensity of the merger in association with the poleward rollup of the ITCZ. Model results show that the two MCVs are merged in a coalescence and capture mode due to their different larger-scale steering flows and sizes. As the two MCVs are being merged, the low- to midlevel potential vorticity and tangential flows increase substantially; the latter occurs more rapidly in the lower troposphere, helping initiate the wind-induced surface heat exchange process leading to the genesis of Eugene with a diameter of 400 km. Subsequently, the merger moves poleward with characters of both MCVs. The simulated tropical storm exhibits many features that are similar to a hurricane, including the warm-cored “eye” and the rotating “eyewall.” It is also shown that vertical shear associated with a midlevel easterly jet leads to the downshear tilt and the wavenumber-1 rainfall structures during the genesis stage, and the upshear generation of moist downdrafts in the vicinity of the eyewall in the minimum equivalent potential temperature layer. Based on the above results, it is concluded that the ITCZ provides a favorable environment with dynamical instability, high humidity, and background vorticity, but it is the merger of the two MCVs that is critical for the genesis of Eugene. The storm decays as it moves northwestward into an environment with increasing vertical shear, dry intrusion, and colder sea surface temperatures. The results appear to have important implications for the high frequency of development of tropical cyclones in the eastern Pacific.
Dissertations / Theses on the topic "Aspire 400 satellite data unit"
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Hrbek, David. "Data loader pro komplexní testování palubních systémů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2018. http://www.nusl.cz/ntk/nusl-385926.
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This master's thesis summarizes theory on how to perform data load onto on-board computers of aircrafts. Specifically, how automated data load of Honeywell's Aspire 400 satellite data unit is done. First part of the text describes requirements and possible ways of the data load process, including standards that are applicable to this topic in the aeronautical industry. The second part describes the implementation of the data load process on the aforementioned unit.
Conference papers on the topic "Aspire 400 satellite data unit"
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Bannasch, Rudolf, Konstantin Kebkal, Sergey Yakovlev, and Alexej Kebkal. "Fast and Reliable Underwater Communication: Successful Applications of Biologically Inspired Techniques." In 25th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/omae2006-92550.
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The capability of the Sweep Spread Carrier (S2C) technology to overcome even the most crucial problems occurring in noisy ultra-shallow water channels could be shown in a wide range of technical applications. A milestone was the first real time transmission of side-scan sonar data while sea-floor mapping carried out by the AUV HUGIN 1000 running several hundred meters in front of the supply ship at a depth of 100–200 m (water depth ca. 400 m). Data speed was between 20 and 33 kBit/s in this trial. Based on this experience a new protocol providing two communication layers has been developed which allows to interpose high priority messages into an ongoing data stream when ever appropriate. So the S2C modems can be used for the transmission of large data files (measurements, digital images etc.) while serving as a fast and reliable control or command link, simultaneously. Current developments include integrated communication, tracking and positioning (combination with an USBL module) and enhanced networking capability. Various models ranging from high-speed S2C modems for short distance application (up to 72 kBit/s over several hundred metres) to efficient long-range modems became available. One of our latest models, the S2C M 7/17, is currently tested in the German Tsunami warning system in the Indian Ocean. The two directional acoustic link between the ocean bottom unit (OBU in 5000–6000 m depth) and the satellite buoy at the surface will be fast enough to transmit not only pressure data but also the records of 4 high-resolution seismic channels including the pre-history of a given Tsunami event. Via satellite scientists have permanent access to the OBU and can thus analyse any event of interest. This new technology opens many possibilities also for applications in Offshore Mechanics and Arctic engineering. Worthwhile to be mentioned, just the other day also the acoustic data transfer via the mud inside of a drill pipe was managed by using the S2C technique.